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Muhammad A.

@AhmadXpert2410

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5.0
23

5.0

5.0

94%

Data Scientist | ML & NLP | GenrativeAI | Python

$10 USD / Hour

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Flag of

Pakistan (4:02 PM)

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Joined on May 17, 2024

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1 Recommendation

$10 USD / Hour

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👋 Hi, I’m Ahmad, a passionate Data Scientist expert in Machine Learning, NLP, and Generative AI. I help startups and businesses transform their raw data into clear insights, predictive models, and smart automation systems that directly improve decision-making and efficiency. 🔍 What I Deliver • Machine Learning & NLP: Predictive analytics, classification, regression, and text analysis using Python, Scikit-learn, TensorFlow, and PyTorch. • Generative AI: Fine-tuning LLMs (GPT, LLaMA, Mistral) for chatbots, summarization, and content automation. • Data Apps & Dashboards: Interactive dashboards and data APIs built with FastAPI, Flask, or Streamlit — ready for production and cloud deployment. 💡 Why Clients Choose Me ✔️ Reliable & On-time Delivery – I respect your deadlines and project scope. ✔️ Crystal-Clear Communication – Frequent updates, no surprises. ✔️ Business-Driven Mindset – Every model I build aligns with your real goals and ROI. I’ve completed 30+ projects across healthcare, finance, e-commerce, and telecom, consistently earning 5⭐ feedback for quality and professionalism. Let’s discuss how I can help you extract value from your data and bring AI-powered intelligence into your business. — Ahmad

Verifications

On time

100%

On budget

100%

Accept rate

93%

Repeat hire rate

12%

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Portfolio

Portfolio

13051963
? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

13051925
? Bitcoin as an Inflation Hedge: A Comprehensive Econometric Analysis (2010–2025) ? Project Overview Analyzed whether Bitcoin functions as an inflation hedge using 14.5 years of monthly data (Aug 2010–Feb 2025). Compared Bitcoin's behavior to gold, stocks, and bonds through robust econometric methods. ? Key Responsibilities and Methods Collected 175 monthly observations from CPI, Yahoo Finance, and crypto sources. Applied ADF tests to ensure data stationarity. Used OLS regression and extended models with inflation dummy variables. Modeled volatility via EGARCH(1,1); found persistent, asymmetric shocks. Performed Granger causality tests (lags 1–4) and segmented time analysis (pre/post-COVID). ? Findings Bitcoin showed no consistent hedge behavior—negative inflation coefficient, high volatility, and positive correlation with stocks. Hedge-like traits appeared only during COVID-19. Bitcoin acts more like a speculative asset than a defensive hedge.

Bitcoin as an Inflation Hedge

? Bitcoin as an Inflation Hedge: A Comprehensive Econometric Analysis (2010–2025) ? Project Overview Analyzed whether Bitcoin functions as an inflation hedge using 14.5 years of monthly data (Aug 2010–Feb 2025). Compared Bitcoin's behavior to gold, stocks, and bonds through robust econometric methods. ? Key Responsibilities and Methods Collected 175 monthly observations from CPI, Yahoo Finance, and crypto sources. Applied ADF tests to ensure data stationarity. Used OLS regression and extended models with inflation dummy variables. Modeled volatility via EGARCH(1,1); found persistent, asymmetric shocks. Performed Granger causality tests (lags 1–4) and segmented time analysis (pre/post-COVID). ? Findings Bitcoin showed no consistent hedge behavior—negative inflation coefficient, high volatility, and positive correlation with stocks. Hedge-like traits appeared only during COVID-19. Bitcoin acts more like a speculative asset than a defensive hedge.

Bitcoin as an Inflation Hedge

? Bitcoin as an Inflation Hedge: A Comprehensive Econometric Analysis (2010–2025) ? Project Overview Analyzed whether Bitcoin functions as an inflation hedge using 14.5 years of monthly data (Aug 2010–Feb 2025). Compared Bitcoin's behavior to gold, stocks, and bonds through robust econometric methods. ? Key Responsibilities and Methods Collected 175 monthly observations from CPI, Yahoo Finance, and crypto sources. Applied ADF tests to ensure data stationarity. Used OLS regression and extended models with inflation dummy variables. Modeled volatility via EGARCH(1,1); found persistent, asymmetric shocks. Performed Granger causality tests (lags 1–4) and segmented time analysis (pre/post-COVID). ? Findings Bitcoin showed no consistent hedge behavior—negative inflation coefficient, high volatility, and positive correlation with stocks. Hedge-like traits appeared only during COVID-19. Bitcoin acts more like a speculative asset than a defensive hedge.

Bitcoin as an Inflation Hedge

? Bitcoin as an Inflation Hedge: A Comprehensive Econometric Analysis (2010–2025) ? Project Overview Analyzed whether Bitcoin functions as an inflation hedge using 14.5 years of monthly data (Aug 2010–Feb 2025). Compared Bitcoin's behavior to gold, stocks, and bonds through robust econometric methods. ? Key Responsibilities and Methods Collected 175 monthly observations from CPI, Yahoo Finance, and crypto sources. Applied ADF tests to ensure data stationarity. Used OLS regression and extended models with inflation dummy variables. Modeled volatility via EGARCH(1,1); found persistent, asymmetric shocks. Performed Granger causality tests (lags 1–4) and segmented time analysis (pre/post-COVID). ? Findings Bitcoin showed no consistent hedge behavior—negative inflation coefficient, high volatility, and positive correlation with stocks. Hedge-like traits appeared only during COVID-19. Bitcoin acts more like a speculative asset than a defensive hedge.

Bitcoin as an Inflation Hedge

Bitcoin as an Inflation Hedge

12076958
The analysis of noise generated by UAV propellers with varying blade spacing angles and axial offsets. The primary goal of this project was to investigate the impact of these variations on the noise levels, providing insights that could lead to quieter UAV designs. Objectives: To measure and analyze the noise generated by UAV propellers. To study the effect of different blade spacing angles and axial offsets on the noise levels. To utilize advanced data analysis techniques, including FFT and A-weighting, to derive meaningful insights from the collected data.

Analyzing UAV Propeller Noise

The analysis of noise generated by UAV propellers with varying blade spacing angles and axial offsets. The primary goal of this project was to investigate the impact of these variations on the noise levels, providing insights that could lead to quieter UAV designs. Objectives: To measure and analyze the noise generated by UAV propellers. To study the effect of different blade spacing angles and axial offsets on the noise levels. To utilize advanced data analysis techniques, including FFT and A-weighting, to derive meaningful insights from the collected data.

Analyzing UAV Propeller Noise

Analyzing UAV Propeller Noise

11923935
In this project, I analyzed real estate price volatility across different ZIP codes over the past five years, focusing on identifying the ZIP codes with the highest and lowest price fluctuations. Using Zillow's Observed Rent Index (ZORI) and Home Value Index (ZHVI), along with economic and demographic data from Altus Group, I achieved the following: Created lists of the top 10 most and least volatile ZIP codes. Determined the key factors contributing to the volatility for the year 2022. Applied data science and statistical techniques to validate findings. Organized and documented the methodology to ensure clarity and reproducibility. Skills Utilized: Data science and statistical analysis Data merging and manipulation using Pandas Econometrics and machine learning Visualization of volatility trends Clear documentation and reporting of results Outcome: The project provided insights into the dynamic nature of real estate markets, highlighting areas of stability and volatility, and ident

Price volatility analysis from year 2000 to 2022

In this project, I analyzed real estate price volatility across different ZIP codes over the past five years, focusing on identifying the ZIP codes with the highest and lowest price fluctuations. Using Zillow's Observed Rent Index (ZORI) and Home Value Index (ZHVI), along with economic and demographic data from Altus Group, I achieved the following: Created lists of the top 10 most and least volatile ZIP codes. Determined the key factors contributing to the volatility for the year 2022. Applied data science and statistical techniques to validate findings. Organized and documented the methodology to ensure clarity and reproducibility. Skills Utilized: Data science and statistical analysis Data merging and manipulation using Pandas Econometrics and machine learning Visualization of volatility trends Clear documentation and reporting of results Outcome: The project provided insights into the dynamic nature of real estate markets, highlighting areas of stability and volatility, and ident

Price volatility analysis from year 2000 to 2022

Price volatility analysis from year 2000 to 2022

Price volatility analysis from year 2000 to 2022

11964520
This analysis processes gene sequence data to identify and visualize amino acid substitutions between resistant and susceptible populations. Using Sanger sequencing data, it performs nucleotide to protein translations, aligns sequences, and identifies mutations. Resistant sequences are aligned with susceptible pairs, allowing for detailed comparison. Mutation information is extracted and visualized through a heatmap, highlighting the frequency of specific amino acid changes at different positions. The heatmap focuses on the first 20% of positions for enhanced readability, providing a clear representation of mutation patterns associated with herbicide resistance in the acetolactate synthase gene.

Analysis and Visualization of Amino Acid Substitutions

This analysis processes gene sequence data to identify and visualize amino acid substitutions between resistant and susceptible populations. Using Sanger sequencing data, it performs nucleotide to protein translations, aligns sequences, and identifies mutations. Resistant sequences are aligned with susceptible pairs, allowing for detailed comparison. Mutation information is extracted and visualized through a heatmap, highlighting the frequency of specific amino acid changes at different positions. The heatmap focuses on the first 20% of positions for enhanced readability, providing a clear representation of mutation patterns associated with herbicide resistance in the acetolactate synthase gene.

Analysis and Visualization of Amino Acid Substitutions

This analysis processes gene sequence data to identify and visualize amino acid substitutions between resistant and susceptible populations. Using Sanger sequencing data, it performs nucleotide to protein translations, aligns sequences, and identifies mutations. Resistant sequences are aligned with susceptible pairs, allowing for detailed comparison. Mutation information is extracted and visualized through a heatmap, highlighting the frequency of specific amino acid changes at different positions. The heatmap focuses on the first 20% of positions for enhanced readability, providing a clear representation of mutation patterns associated with herbicide resistance in the acetolactate synthase gene.

Analysis and Visualization of Amino Acid Substitutions

Analysis and Visualization of Amino Acid Substitutions

Analysis and Visualization of Amino Acid Substitutions

11904977
Client's Goal for the Project: The client's objective was to conduct a comprehensive arrhythmia study leveraging a high-quality dataset sourced from PhysioNet The dataset consisted of 12-lead Electrocardiogram (ECG) recordings obtained from patients with various cardiac conditions. The primary goal was to analyze the dataset to derive actionable insights into arrhythmias and contribute to the advancement of cardiac health research.

An In-Depth Look at ECG Data for Analysis and Detection

An In-Depth Look at ECG Data for Analysis and Detection

An In-Depth Look at ECG Data for Analysis and Detection

13051963
? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

? Project Overview Elysium is a full-stack, web-based platform built to automate the data preprocessing pipeline for data scientists, analysts, and engineers. The solution tackles common issues like missing values, duplicates, outliers, and inconsistencies using AI and machine learning, significantly reducing manual effort and improving data quality. ? Core Features & Technical Responsibilities Data Profiling & Cleaning: Automated identification and treatment of data issues with user-driven intervention. Logs every action for full reviewability. Feature Engineering & Reduction: Includes tools for transformation, encoding, PCA, and custom engineering to improve model readiness. Feature Sensitivity Analysis: Uses methods like SHAP values to explain model predictions, enhancing interpretability. Data Visualization: Offers interactive charts (bar, scatter, histograms, heatmaps) to explore structure, trends, and correlations. Export Pipeline: Finalized data can be exported

Elysium – Smart Data Prep Platform

13051925
? Bitcoin as an Inflation Hedge: A Comprehensive Econometric Analysis (2010–2025) ? Project Overview Analyzed whether Bitcoin functions as an inflation hedge using 14.5 years of monthly data (Aug 2010–Feb 2025). Compared Bitcoin's behavior to gold, stocks, and bonds through robust econometric methods. ? Key Responsibilities and Methods Collected 175 monthly observations from CPI, Yahoo Finance, and crypto sources. Applied ADF tests to ensure data stationarity. Used OLS regression and extended models with inflation dummy variables. Modeled volatility via EGARCH(1,1); found persistent, asymmetric shocks. Performed Granger causality tests (lags 1–4) and segmented time analysis (pre/post-COVID). ? Findings Bitcoin showed no consistent hedge behavior—negative inflation coefficient, high volatility, and positive correlation with stocks. Hedge-like traits appeared only during COVID-19. Bitcoin acts more like a speculative asset than a defensive hedge.

Bitcoin as an Inflation Hedge

? Bitcoin as an Inflation Hedge: A Comprehensive Econometric Analysis (2010–2025) ? Project Overview Analyzed whether Bitcoin functions as an inflation hedge using 14.5 years of monthly data (Aug 2010–Feb 2025). Compared Bitcoin's behavior to gold, stocks, and bonds through robust econometric methods. ? Key Responsibilities and Methods Collected 175 monthly observations from CPI, Yahoo Finance, and crypto sources. Applied ADF tests to ensure data stationarity. Used OLS regression and extended models with inflation dummy variables. Modeled volatility via EGARCH(1,1); found persistent, asymmetric shocks. Performed Granger causality tests (lags 1–4) and segmented time analysis (pre/post-COVID). ? Findings Bitcoin showed no consistent hedge behavior—negative inflation coefficient, high volatility, and positive correlation with stocks. Hedge-like traits appeared only during COVID-19. Bitcoin acts more like a speculative asset than a defensive hedge.

Bitcoin as an Inflation Hedge

? Bitcoin as an Inflation Hedge: A Comprehensive Econometric Analysis (2010–2025) ? Project Overview Analyzed whether Bitcoin functions as an inflation hedge using 14.5 years of monthly data (Aug 2010–Feb 2025). Compared Bitcoin's behavior to gold, stocks, and bonds through robust econometric methods. ? Key Responsibilities and Methods Collected 175 monthly observations from CPI, Yahoo Finance, and crypto sources. Applied ADF tests to ensure data stationarity. Used OLS regression and extended models with inflation dummy variables. Modeled volatility via EGARCH(1,1); found persistent, asymmetric shocks. Performed Granger causality tests (lags 1–4) and segmented time analysis (pre/post-COVID). ? Findings Bitcoin showed no consistent hedge behavior—negative inflation coefficient, high volatility, and positive correlation with stocks. Hedge-like traits appeared only during COVID-19. Bitcoin acts more like a speculative asset than a defensive hedge.

Bitcoin as an Inflation Hedge

? Bitcoin as an Inflation Hedge: A Comprehensive Econometric Analysis (2010–2025) ? Project Overview Analyzed whether Bitcoin functions as an inflation hedge using 14.5 years of monthly data (Aug 2010–Feb 2025). Compared Bitcoin's behavior to gold, stocks, and bonds through robust econometric methods. ? Key Responsibilities and Methods Collected 175 monthly observations from CPI, Yahoo Finance, and crypto sources. Applied ADF tests to ensure data stationarity. Used OLS regression and extended models with inflation dummy variables. Modeled volatility via EGARCH(1,1); found persistent, asymmetric shocks. Performed Granger causality tests (lags 1–4) and segmented time analysis (pre/post-COVID). ? Findings Bitcoin showed no consistent hedge behavior—negative inflation coefficient, high volatility, and positive correlation with stocks. Hedge-like traits appeared only during COVID-19. Bitcoin acts more like a speculative asset than a defensive hedge.

Bitcoin as an Inflation Hedge

Bitcoin as an Inflation Hedge

12076958
The analysis of noise generated by UAV propellers with varying blade spacing angles and axial offsets. The primary goal of this project was to investigate the impact of these variations on the noise levels, providing insights that could lead to quieter UAV designs. Objectives: To measure and analyze the noise generated by UAV propellers. To study the effect of different blade spacing angles and axial offsets on the noise levels. To utilize advanced data analysis techniques, including FFT and A-weighting, to derive meaningful insights from the collected data.

Analyzing UAV Propeller Noise

The analysis of noise generated by UAV propellers with varying blade spacing angles and axial offsets. The primary goal of this project was to investigate the impact of these variations on the noise levels, providing insights that could lead to quieter UAV designs. Objectives: To measure and analyze the noise generated by UAV propellers. To study the effect of different blade spacing angles and axial offsets on the noise levels. To utilize advanced data analysis techniques, including FFT and A-weighting, to derive meaningful insights from the collected data.

Analyzing UAV Propeller Noise

Analyzing UAV Propeller Noise

11923935
In this project, I analyzed real estate price volatility across different ZIP codes over the past five years, focusing on identifying the ZIP codes with the highest and lowest price fluctuations. Using Zillow's Observed Rent Index (ZORI) and Home Value Index (ZHVI), along with economic and demographic data from Altus Group, I achieved the following: Created lists of the top 10 most and least volatile ZIP codes. Determined the key factors contributing to the volatility for the year 2022. Applied data science and statistical techniques to validate findings. Organized and documented the methodology to ensure clarity and reproducibility. Skills Utilized: Data science and statistical analysis Data merging and manipulation using Pandas Econometrics and machine learning Visualization of volatility trends Clear documentation and reporting of results Outcome: The project provided insights into the dynamic nature of real estate markets, highlighting areas of stability and volatility, and ident

Price volatility analysis from year 2000 to 2022

In this project, I analyzed real estate price volatility across different ZIP codes over the past five years, focusing on identifying the ZIP codes with the highest and lowest price fluctuations. Using Zillow's Observed Rent Index (ZORI) and Home Value Index (ZHVI), along with economic and demographic data from Altus Group, I achieved the following: Created lists of the top 10 most and least volatile ZIP codes. Determined the key factors contributing to the volatility for the year 2022. Applied data science and statistical techniques to validate findings. Organized and documented the methodology to ensure clarity and reproducibility. Skills Utilized: Data science and statistical analysis Data merging and manipulation using Pandas Econometrics and machine learning Visualization of volatility trends Clear documentation and reporting of results Outcome: The project provided insights into the dynamic nature of real estate markets, highlighting areas of stability and volatility, and ident

Price volatility analysis from year 2000 to 2022

Price volatility analysis from year 2000 to 2022

Price volatility analysis from year 2000 to 2022

11964520
This analysis processes gene sequence data to identify and visualize amino acid substitutions between resistant and susceptible populations. Using Sanger sequencing data, it performs nucleotide to protein translations, aligns sequences, and identifies mutations. Resistant sequences are aligned with susceptible pairs, allowing for detailed comparison. Mutation information is extracted and visualized through a heatmap, highlighting the frequency of specific amino acid changes at different positions. The heatmap focuses on the first 20% of positions for enhanced readability, providing a clear representation of mutation patterns associated with herbicide resistance in the acetolactate synthase gene.

Analysis and Visualization of Amino Acid Substitutions

This analysis processes gene sequence data to identify and visualize amino acid substitutions between resistant and susceptible populations. Using Sanger sequencing data, it performs nucleotide to protein translations, aligns sequences, and identifies mutations. Resistant sequences are aligned with susceptible pairs, allowing for detailed comparison. Mutation information is extracted and visualized through a heatmap, highlighting the frequency of specific amino acid changes at different positions. The heatmap focuses on the first 20% of positions for enhanced readability, providing a clear representation of mutation patterns associated with herbicide resistance in the acetolactate synthase gene.

Analysis and Visualization of Amino Acid Substitutions

This analysis processes gene sequence data to identify and visualize amino acid substitutions between resistant and susceptible populations. Using Sanger sequencing data, it performs nucleotide to protein translations, aligns sequences, and identifies mutations. Resistant sequences are aligned with susceptible pairs, allowing for detailed comparison. Mutation information is extracted and visualized through a heatmap, highlighting the frequency of specific amino acid changes at different positions. The heatmap focuses on the first 20% of positions for enhanced readability, providing a clear representation of mutation patterns associated with herbicide resistance in the acetolactate synthase gene.

Analysis and Visualization of Amino Acid Substitutions

Analysis and Visualization of Amino Acid Substitutions

Analysis and Visualization of Amino Acid Substitutions

11904977
Client's Goal for the Project: The client's objective was to conduct a comprehensive arrhythmia study leveraging a high-quality dataset sourced from PhysioNet The dataset consisted of 12-lead Electrocardiogram (ECG) recordings obtained from patients with various cardiac conditions. The primary goal was to analyze the dataset to derive actionable insights into arrhythmias and contribute to the advancement of cardiac health research.

An In-Depth Look at ECG Data for Analysis and Detection

An In-Depth Look at ECG Data for Analysis and Detection

An In-Depth Look at ECG Data for Analysis and Detection

5.0 · 23 Reviews
Reviews
S

Comprehensive PCA on CSV Data • €30 EUR

Ahmad delivered an outstanding PCA project with clear and insightful analysis. His work demonstrated strong data science skills and a deep understanding of dimensionality reduction. The results were well-presented, making complex concepts easy to grasp

Santiago .

@shakebe03

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Flag of

Majadahonda, Spain

•

10 days ago

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Data analytics • ₹18,000 INR

Good work done. I will give more

Mohemmed N.

@mohemmedniyaz

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coimbatore, India

•

3 months ago

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Looking for Full-Stack AI Developer Next + Supabase + AI agent • $250 USD

I strongly advise to consider carefully to hire this freelancer. He said he would do his best, but after award, he said to work only part-time at night. He didn't touch 2 days. His skill was terrible; he spent days trying to understand a small code and made only one function can be done a few hours a week. His attitude was also bad. When I raised my concerns, he told me not to pressure him and insisted it was fair for our budget, despite accepting it earlier. I lost a week and felt devastated.

Former Client (inactive)

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API Creation for Business Analytics Machine Learning • ₹50,000 INR

It was a pleasure collaborating on this data analysis API project! The freelancer ultimately delivered a solid, well-architected solution that fully met our requirements. Although there were some delays along the way, every challenge was resolved with care, and the end result was both robust and reliable. I truly appreciated their technical skills, willingness to engage, and persistence in getting things right.

Mohemmed N.

@mohemmedniyaz

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Flag of

coimbatore, India

•

5 months ago

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power Bi project -- 2 • $30 USD

Great experience working together on this project. Delivered quality work on time and was very responsive to feedback and requirements throughout the process

Bhoomika S.

@bhoomi093

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Saint Augustine, United States

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6 months ago

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Experience

Data Scientist

Jun, 2025 - Present

•

5 months

Now Software

Jun, 2025 - Present

•

5 months

Working on SQL scripts, data collection, and predictive modeling techniques to design and optimize machine learning pipelines. Focused on transforming raw data into actionable insights, enabling stakeholders to make data-driven decisions with greater accuracy and confidence.

Flag of

Islamabad, Pakistan

Jun, 2025 - Present

•

5 months

Education

National University of Computer and Emerging Sciences

2020 - 2024

•

4 years

Bs(computer science)

Flag of

Pakistan

2020 - 2024

•

4 years

Qualifications

Foundation of Data Science

2024

Google

I've successfully completed the Foundations of Data Science course through Google! This course has provided me with essential skills in data analysis, effective communication, project management, and teamwork within a data-driven environment. I'm now equipped with a solid foundation to advance further in the field of data analytics.

2024

INTRO TO STATISTICS IN PYTHON

2023

DATA CAMP

From understanding the fundamentals to applying statistical concepts in Python, the course has equipped me with the skills to analyze data, make informed decisions, and derive valuable insights. Key takeaways: Exploring descriptive statistics and data visualization techniques. Mastering hypothesis testing and understanding p-values. Gaining proficiency in correlation, regression, and more. Excited to apply this knowledge in real-world data analysis projects.

2023

INTRO TO NUMPY

2023

Data camp

NumPy, a fundamental package for numerical computing in Python, plays a crucial role in data science and machine learning projects. This course provided a comprehensive understanding of its functionalities and how to leverage its powerful features for efficient data manipulation and analysis. Key Takeaways: ✅ Understanding NumPy arrays and their operations ✅ Broadcasting and vectorized operations for efficient computation ✅ Exploring data manipulation techniques

2023

Certifications

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