Unsupervised Model for Anomaly Detection

@tadinhkien

Greetings, Thank you for considering my application for this project. As an AI Engineer and Python Developer with over 8+ years of experience, I bring a wealth of knowledge and expertise in the field of Python, Deep Learning. I have carefully reviewed the project description and am eager to discuss your specific needs and requirements in more detail. My commitment is to provide dedicated support and consistent follow-up throughout the project's lifecycle. Please feel free to reach out to me to further discuss how I can contribute to the success of your project. Looking forward to the opportunity of working together. Best regards, KuroKien

@koolvishruth

Hi, I have prior 7 years of experience in Machine learning engineering and worked on Unsupervised model development. Let's connect

@ashrafsbai6655

Hi there, I checked your requirements and guarantee you that i have relevant experience in Python,AI and data science it's gonna be done within the highest quality . Let's contact via chat so that I can start work immediately

@snbhanja

Hi, I have worked on different timeseries anomaly detction for both univariate and multi variate anomaly detection with plots indicating anomalous points. There are many ways to do unsupervised anomaly detction, I will use appropriate algo for your usecase. I will use all required libraries like pandas, scikit learn, matplotlib/pyplot etc. Let's connect.

@KestanWriters

I HAVE THE SAME PAPER DONE. IT USES MACHINE LEARNING METHODS FOR ANOMALY DETECTION. With a name like Double Q, my work guarantees quick and quality results. I have a strong background in machine learning coupled with excellent data analysis and processing skills. Notably, I am proficient in using Python libraries such as pandas, numpy, scikit-learn, and matplotlib which are essential for this project. Offering an extensive breadth of knowledge and experience, I am confident that I can deliver the anomaly detection model you need to streamline your processes. For your project, you need someone with hands-on experience in handling multiple CSV datasets—an area where I excel. Having worked on numerous data-driven projects in the past, including working extensively with unsupervised learning techniques, I possess skills that are tailor-made for your requirements. My commitment to delivering satisfactory results has always been a trademark of my services. This means you can expect me to give utmost attention to detail in each step of the project from data preprocessing to developing the final model. With me, not only will you get an unsupervised anomaly detection model built using cutting-edge techniques but also someone who understands the value of timely delivery without compromising on quality. With my assistance on this project, we can identify and tackle anomalies within your datasets effectively and efficiently.

@HASEEB1803

Hello, I have a strong background in machine learning and Python development, with hands-on experience in building unsupervised models for anomaly detection. In my previous project, I worked on a Python-based pipeline that handled multiple CSV datasets, performed preprocessing, and applied algorithms like Isolation Forest and DBSCAN for detecting unusual patterns. My Approach: +Data Handling – Load and merge multiple CSV datasets using pandas & numpy, ensuring proper preprocessing (missing values, scaling, normalization). +Model Development – Apply unsupervised anomaly detection techniques such as: -Isolation Forest -Local Outlier Factor (LOF) -One-Class SVM +Visualization – Use matplotlib to create intuitive plots that highlight anomalies vs. normal data points. +Evaluation & Deliverables – Provide a clean, reproducible Python script or notebook, along with visualizations, and a short README for setup and usage. Why Me: +Proficient in pandas, numpy, scikit-learn, and matplotlib +Strong experience in unsupervised learning & anomaly detection +Skilled in data preprocessing and visualization to make insights clear My last project was also a Python ML script, and if you’d like, I can share more details about it in inbox.

@RaksAd1512

As a decision and ML scientist I have good experience in delivering machine learning use cases with accuracy and efficieny.I understand the intricate nature of your project, and my specialty in MLOps and Data Science, with over a decade's worth of experience, makes me the perfect fit. Being proficient in pandas, numpy, scikit-learn, and matplotlib is second nature to me, as I have successfully designed and deployed various unsupervised models for anomaly detection using these Python libraries. My expertise also extends to handling and processing multiple CSV datasets which aligns directly with your project requirements. Moreover, I place great emphasis on data preprocessing and visualization as these steps are crucial in uncovering hidden patterns and anomalies. What sets me apart from other freelancers is my ability to integrate the power of AI into decision-making processes. This skill allows me not only to build robust models but also to deliver actionable insights that optimize decision workflows. In short, my focus is not just on creating an unsupervised model for anomaly detection, but on transforming your data into actionable intelligence that enhances your decision-making capability. So let's team up and take your project to new heights using state-of-the-art AI techniques!

@railsmind

I have solid experience building unsupervised machine learning models for anomaly detection using Python libraries such as pandas, numpy, scikit-learn, and matplotlib. I can help you preprocess and combine multiple CSV datasets, engineer relevant features, and implement techniques like Isolation Forest, DBSCAN, or clustering-based approaches to accurately detect anomalies. To make insights actionable, I’ll also provide clear visualizations and performance metrics, so results are both technically sound and easy to interpret. In a recent project, I developed an unsupervised anomaly detection pipeline for financial transaction data, which successfully identified unusual spending patterns and reduced false positives compared to rule-based detection

@prakhars653

Hello, I would be glad to assist you in building a robust unsupervised anomaly detection model using Python. With a strong foundation in machine learning and hands-on expertise in pandas, numpy, scikit-learn, and matplotlib, I can help you process multiple CSV datasets, clean and transform the data, and apply appropriate algorithms to detect anomalies effectively. My approach will include: Data Preprocessing – loading, cleaning, and structuring CSV data for modeling. Exploratory Data Analysis & Visualization – identifying patterns, distributions, and potential outliers. Unsupervised Anomaly Detection – applying methods such as Isolation Forest, One-Class SVM, DBSCAN, or clustering-based approaches, depending on dataset characteristics. Model Evaluation & Visualization – interpreting anomaly scores and presenting results through clear, intuitive plots. Having also completed the Deloitte Data Analytics Virtual Internship Certificate and worked on multiple Python-based data analysis and ML projects, I bring both technical rigor and attention to detail. I ensure the workflow will be well-structured, reproducible, and easy to extend for future datasets. Looking forward to collaborating and delivering a solution tailored to your needs. Best regards, Prakhar Shukla

@Sinergiavitalsas

i would help u more info with cv included inside freelancer or in any web browser by ceo name greet fully john jairo sanabria sarmiento ceo sinergia vital sas

@Aliakseizal

I can do that for you. We will use statics to build an algorithm detecting anomalies, after that you can delete them automatically or edit manually

@rabbia39

Hi, I’m great with Python (pandas, numpy, scikit-learn, matplotlib) and have strong experience in unsupervised learning. I can build your anomaly detection model, preprocess the CSVs, and deliver clear visualizations with clean, easy-to-follow code. Ready to get this done for you. Cheers, Rabbia

@divyam12345

Dear Sir/Madam, I have experience in writing research papers, thesis works and textbooks and course materials, matlab coding. I can build an unsupervised anomaly detection model using matlab for data handling, scikit-learn for modeling, and matplotlib for visualizations. I will process , perform necessary cleaning, and apply techniques like Isolation Forest, DBSCAN, or PCA-based detection depending on data structure. The workflow will include preprocessing, model training, anomaly scoring, and visualization of detected anomalies. Let’s connect in the chatbox to discuss the project further, including the budget and timeline. To know more about my experience, let's talk in a freelancer call, and I can share more details and sample works in the chatbox.

@tufailm3

I’d be glad to assist in developing a robust unsupervised anomaly detection pipeline tailored to your datasets. With expertise in machine learning, unsupervised algorithms, and data preprocessing, I can help you detect unusual patterns or outliers effectively. Relevant Skills & Experience: Unsupervised Learning: Hands-on experience with Isolation Forest, One-Class SVM, Local Outlier Factor, and clustering-based anomaly detection (KMeans, DBSCAN). Python Libraries: Proficient with pandas, numpy, scikit-learn, matplotlib, and seaborn for preprocessing, modeling, and visualization. Data Handling: Skilled in cleaning and processing multiple CSV datasets, merging, handling missing values, scaling, and feature engineering. Visualization: Strong ability to build interpretable plots (distribution plots, scatter plots, anomaly highlighting) for clear insights.

@saicharankadaru

Hi, i have read the project details and I have all the skills that are required to complete this project with all the specifications and i can deliver the project on time..

@prathambiradar12

Hello, I have knowledge of machine learning and can build an unsupervised anomaly detection model using techniques like clustering (K-Means/DBSCAN) or autoencoders. The model can detect unusual patterns in your data without prior labels, helping identify outliers or fraud effectively. I can also preprocess and clean the dataset, visualize anomalies, and deliver a working notebook/code with clear explanation

@Bhavna245

I'm ready to build your unsupervised anomaly detection model. Using key Python libraries like pandas, scikit-learn, and matplotlib, I will handle and process your multiple CSV datasets to find hidden outliers. My approach involves developing a robust model and creating clear visualizations that help you understand the detected anomalies. With my background in machine learning and data preprocessing, I am confident I can deliver a project that provides deep, actionable insights. I'm excited to get started and help you uncover those unusual data points.

@areebat90

Hello, I would love to assist you in building an unsupervised anomaly detection model tailored to your needs. With solid experience in Python and hands-on use of pandas, NumPy, scikit-learn, and matplotlib, I can design a clean, reproducible pipeline that processes multiple CSVs and highlights anomalies effectively. ? My Approach: Preprocess and combine multiple CSV datasets Exploratory analysis + visualization for outliers/trends Implement unsupervised models (Isolation Forest, One-Class SVM, clustering-based approaches) Evaluate and visualize anomalies with clear plots/metrics ? Past Projects: --> Adult Income dataset ML project (Random Forest & XGBoost) --> Amazon product reviews -LSTM --> Stock price prediction with time-series ML models --> CNN for image recognition (MNIST, 97%+ accuracy) ? Deliverables: Jupyter Notebook Visual anomaly detection outputs & plots Clear instructions for reproducibility I can get started immediately and ensure the final solution is accurate, transparent, and easy to extend. Best regards, Areeba Tahir

@bunnysaini504

I am skilled analyst with experience of 1.8 year in IT field ,and Do easily both supervisor and unsupervised machine learning project

@drashti800

Hello, I am highly interested in working on your anomaly detection project. I have hands-on experience in both supervised and unsupervised machine learning, with a strong background in Python and its libraries including pandas, numpy, scikit-learn, and matplotlib. During my internships, I worked on projects involving customer segmentation using K-means clustering, stock price prediction, and data preprocessing tasks, which required handling multiple datasets, feature engineering, and performance evaluation. For your project, I can develop an unsupervised anomaly detection model tailored to your datasets, ensuring accurate detection of outliers. I will provide visualizations of detected anomalies using matplotlib and seaborn.I will deliver clean, well-documented code and provide explanations so that you can easily understand and extend the solution in the future. Looking forward to collaborating with you on this project. Thank you