Notebook lmJobs

I have a github project , its in jupyter notebook , I need to run this code

I want to quantify how recent advances in artificial intelligence are influencing forec...time-series techniques—VAR, ARDL, error-correction, whatever proves statistically sound—provided the approach is fully documented and reproducible in R, Python, or Stata. Along the way, please explain every transformation, stationarity check, and specification test so that the methodology can be defended in an academic setting. Deliverables • Cleaned and commented dataset (CSV) • Script or notebook with all code and step-by-step comments • Forecast outputs plus a concise technical note (≈5 pages) summarising model selection, diagnostics, and the estimated AI impact on future GDP growth. I will review your code for reproducibility and the note for clarity...

I am just getting started with Python...practise writing clear, working code. The main areas I need to master are: • Basic syntax and data types • Control structures and functions • Libraries and modules Please structure the lessons so each concept is demonstrated with short examples, followed by hands-on exercises I can share back for review. I am happy to work in whichever environment you prefer—IDLE, VS Code, Jupyter Notebook—so long as I can replicate the workflow on my own machine. By the end of our time together I should be comfortable writing small scripts, understanding error messages, and knowing where to look next when I get stuck. If this sounds like a good fit, let me know how you would organise the sessions and what materials or...

...REST endpoints are cleanly separated; this will let me expose the following Android-ready APIs later on: live-video analysis, image-file analysis and retrieval of disease-history logs. Deliverables • Python inference engine (TensorFlow/PyTorch + OpenCV acceptable) optimised for Raspberry Pi 5 • Django project with the described role system, templates and REST endpoints • Model-training notebook or script plus labeled dataset reference • Setup script or Dockerfile for one-step deployment on a fresh Pi • Brief README covering install, usage and endpoint documentation Acceptance criteria 1. Live camera stream on the Pi returns disease label and confidence <2 s per frame under normal lighting. 2. Image upload route returns the same JSON str...

We are seeking a professional freelancer to create a 30 second video. This project will include still images, music and a voice over, which will be supplied by the client. The freelancer must be able to understand English. The milestone will be released after the project has been approved by the client. The budget will not go beyond 60 USD. 0.0–3.5 sec Image: Messy desk, old notebook Words on Screen: “I started creating this journal… four years ago.” 3.5–6.5 sec Image: Flip through a stack of drafts Words on Screen: “I thought this would take a few months.” 6.5–8.0 sec On-screen text only Words on Screen: “Draft 69.” 8.0–9.0 sec ⏸ PAUSE (1.0 second) • No voice • Tiny zoom in 9.0–12.5 sec Image: Cros...

...stability, but please keep the core idea intact. OpenCV, NumPy, and scikit-image are the tools I already use elsewhere, so sticking to that stack will make adoption easiest. The code should be clean, modular, and fast enough to process typical 1080p sequences in real time or near real time on a modern CPU (GPU use is optional but not required). Deliverables • A self-contained Python module or notebook that loads the images, computes the score, and can be called from the command line with a folder path argument • Inline documentation and a short README explaining installation, expected folder layout, and the mathematics behind the normalization • A sample run on a small dummy dataset demonstrating that the score remains stable across frames of similar qualit...

...by my Python back-end (JSON is fine) – Handle throttling limits and session renewal gracefully Deliverables 1. Well-commented source code (language is your choice) that exposes functions such as get_market_odds(market_id) and get_market_status(market_id) 2. A short README explaining setup, key dependencies and how to extend to additional sports if needed 3. Proof-of-concept script or notebook that streams live data for at least one market in each listed sport for 10 minutes without disconnecting Acceptance I’ll consider the job complete once the script runs on my VPS, returns the requested fields for all four sports, and passes a 24-hour monitoring period with no authentication or rate-limit errors....

I have a steady stream of plain-...Speed matters: each hourly log is time-stamped and should be processed within the hour so downstream analytics always work with clean data. Your script or small tool should run from the command line, accept a path or file pattern, and write either a scrubbed copy or a parallel “” that my monitoring stack can ignore. Please package the work as follows: • A well-commented script or notebook ready to run • A concise README explaining dependencies and how to execute or schedule it • A short sample run (cleaned file or flagged output) that proves the anomaly filter is catching patterns, not just extreme numbers If you’ve tackled log anomaly detection before, especially on rolling hourly data, I’d love to...

...opened, the other side closed, and top drawers closed Desk with lower desk door opened, desk top opened, both desk sides opened, and top drawers closed Dimension & Technical Shots Desk fully closed, with overall dimensions clearly indicated Desk fully opened, with overall dimensions clearly indicated Usage / Lifestyle Shot Fully staged render demonstrating real-life use: Laptop and working notebook placed on the desk surface File folders placed inside the internal storage shelves Shot should clearly illustrate functionality, storage capacity, and practical use Deliverable Objective The final deliverables should clearly and professionally communicate: The desk’s folding and opening mechanisms All functional configurations Material quality and finishes Usab...

I need all relevant text pulled from a specific website and delivered in a clean, structured file. The so...manipulate later. A small sample first will help confirm we’re on the same page before you run the full extraction. Please use whatever stack you prefer—Python with BeautifulSoup or Scrapy, JavaScript with Puppeteer, or a tool that suits the task best—just be sure to respect and provide the code so I can rerun the process when the site updates. Deliverables: • Re-usable script or notebook with clear comments • Complete dataset containing all extracted text, delivered in my chosen format • Brief read-me explaining setup, execution, and any dependencies I’ll review the sample immediately and give quick feedback so we can kee...

I’m building a Python-based algo...event-driven callbacks for entry, exit and risk checks • Back-testing component producing equity curve and basic performance metrics (Sharpe, max drawdown) • Execution stub capable of paper trading via REST/WebSocket (live trade logic isolated for safety) • README showing setup, sample run for both modes and pointers on adding new strategies or data sources Acceptance: a short screen-capture or notebook proving (1) a back-test on historical data and (2) a live data subscription that feeds the same pipeline, each generating trade logs and summary stats identical in format. (1) pine script base trading copy past script (2) chartink screenerbase ( 3 ) strategy Builder base (4 ) equty and f &o base (5) co...

I’m refining a series of logistic-regression models in Python and would like hands-on guidance from someone who knows SciPy’s stats and optimize sub-modules inside out. My current notebook reaches acceptable accuracy, but I’m running into questions about link-function choices, solver stability, convergence diagnostics, and the best way to structure reusable helper functions. What I’d like from you • Review a short code sample (≈200 lines) that calls for a custom log-likelihood. • Explain, with examples, how to improve numerical stability and interpret the Hessian output for standard-error estimation. • Suggest parameter-regularisation strategies available directly in SciPy or via light dependencies I can bolt on. • Join one...

...frameworks such as PyTorch or TensorFlow, and you know the trade-offs between traditional filters, GAN-based approaches, and modern super-resolution networks. Experience packaging models for CoreML, TensorFlow Lite or similar mobile runtimes will set you apart. I’m most interested in seeing what you’ve already shipped, so please include past work that proves you can take an image-processing idea from notebook to app store. Deliverables • Clean, well-commented Python codebase and • Trained weights with reproducible training scripts • Mobile-ready wrapper (REST, gRPC, CoreML, or TFLite) • README with run instructions and basic quality benchmarks (PSNR/SSIM) Acceptance criteria: pipeline meets agreed-upon quality metrics on our validatio...

... This is a true proof-of-concept, yet the end result must be usable: after you finish I should be able to spin up the model locally, type a health-related question, and receive a sensible response in real time. Ths would be trained on a cloud instance with proper gpu setup (think runpods, lambda) Your task covers the dataset preparation, tokenisation, training, evaluation, and a tiny CLI or notebook demo—while keeping everything strictly open-source. If you believe there is a better public dataset than MedQuAD, propose it first; otherwise stick with MedQuAD. Please walk me through your prior experience with nanochat when you reply, because I need to gauge how quickly you can jump in. Deliverables • Clean, well-commented source code in a Git repo (Python, nanoch...

I will share a raw table of laboratory-measured water-quality parameters (pH, turbidity, dissolved oxygen, heavy-metal readings and severa...(scikit-learn, XGBoost or LightGBM are all acceptable) with solid cross-validation. • Compare its performance against at least one other tree-based approach so I can see the gains. • Deliver a concise report containing the final metrics (accuracy, precision/recall, F1, ROC-AUC) plus a short interpretation of the most influential parameters. • Hand over the cleaned dataset, Python scripts or Jupyter notebook, and the serialized model file so I can reproduce results on my end. Keep the code readable, add comments where decisions might need context, and structure the repository so I can drop in new samples later and get predi...

I’ve compiled six months of raw sales data and now need a sharp statistical mind to transform those numbers into a reliable forecast. The ob...the dataset, then apply time-series or other suitable predictive techniques in Python, R, or a comparable analytics environment. Please visualise the trends in clear charts (Matplotlib, Seaborn, ggplot2, or similar) and summarise your findings in a concise, non-technical narrative that management can act on immediately. Deliverables: • Cleaned and documented dataset • Reproducible analysis notebook or script • Forecast results with confidence intervals and visualisations • Brief report outlining methodology, assumptions, and actionable insights I’m happy to clarify any data quirks or business context yo...

...clean, reproducible Floquet framework that extracts the multipliers for each wavenumber and returns clear stability maps. You are free to work in MATLAB, Python (NumPy/SciPy), or Julia as long as the code is well commented and numerically robust—spectral collocation or a high-order finite-difference approach is fine as long as convergence is demonstrated. Deliverables • A runnable script or notebook that assembles the monodromy matrix for the periodic WIBL coefficients and computes the Floquet multipliers across user-defined parameter grids • Plots that highlight the predicted instability noses and stability islands, ready for publication (vector format preferred) • A concise technical note summarising the formulation, numerical method, verification ...

...clean, reproducible Floquet framework that extracts the multipliers for each wavenumber and returns clear stability maps. You are free to work in MATLAB, Python (NumPy/SciPy), or Julia as long as the code is well commented and numerically robust—spectral collocation or a high-order finite-difference approach is fine as long as convergence is demonstrated. Deliverables • A runnable script or notebook that assembles the monodromy matrix for the periodic WIBL coefficients and computes the Floquet multipliers across user-defined parameter grids • Plots that highlight the predicted instability noses and stability islands, ready for publication (vector format preferred) • A concise technical note summarising the formulation, numerical method, verification ...

...SQLAlchemy), tidy everything, then explore daily, weekly, and monthly patterns. Visualisations in matplotlib or seaborn and a concise written summary (PDF or Jupyter Notebook) will round out the story so stakeholders can quickly grasp how revenue is evolving and where seasonality or anomalies appear. Deliverables • Well-commented SQL scripts that reproduce the dataset • A Python notebook (or .py script) with all transformation and analysis steps • Three to five clear charts illustrating sales trends over time • A short insights report highlighting key findings and next-step suggestions Acceptance criteria The notebook runs end-to-end on my sample database, charts render without manual tweaking, and the report calls out at least two ...

...clean, reproducible Floquet framework that extracts the multipliers for each wavenumber and returns clear stability maps. You are free to work in MATLAB, Python (NumPy/SciPy), or Julia as long as the code is well commented and numerically robust—spectral collocation or a high-order finite-difference approach is fine as long as convergence is demonstrated. Deliverables • A runnable script or notebook that assembles the monodromy matrix for the periodic WIBL coefficients and computes the Floquet multipliers across user-defined parameter grids • Plots that highlight the predicted instability noses and stability islands, ready for publication (vector format preferred) • A concise technical note summarising the formulation, numerical method, verification ...

Need Azure Databricks admin training for interview. The class should start with the essentials—workspace deployment, cluster creation, notebook management and role-based access—but quickly move into the real-world problems we keep hitting, especially the “shuffle”-related errors that derail our Spark jobs. I’d also like practical advice on monitoring, scaling and cost-aware performance tuning so we can keep clusters healthy instead of firefighting after the fact. I’m expecting an interactive format delivered remotely (Teams or Zoom works), with hands-on labs that let attendees follow along in our own tenant. After the session I’d like to walk away with: • Slide deck or reference notes covering setup, troubleshooting and optimisatio...

...efficient, memory-savvy routine (pandas, NumPy, itertools, or any other high-performance approach you prefer) that can churn through roughly one hundred million comparisons without freezing up my workstation. Multithreading, vectorisation, or chunked processing—all are acceptable so long as they keep runtime practical and the output accurate. Deliverables • A well-commented Python script or notebook that performs the permutation matching on text data • A completed Excel file containing every identified match in a clear, tabular layout • A short read-me explaining any required libraries and how to rerun the job on new data I will test the script on my side with a control subset before running the full 10,000 × 10,000 sweep, so please make sure yo...

...Databricks, keeping the business logic intact and portable. No third-party or custom system integration is involved; every task stays within the databases themselves. Deliverables are: 1. Well-commented DDL/DML scripts for each environment. 2. Migration playbook detailing steps, tooling and gotchas. 3. Performance report comparing pre- and post-migration runtimes. 4. A single run-all script (or notebook for Databricks) that builds schema, loads sample data and demonstrates optimized queries. I will validate the work by running your scripts in fresh sandboxes, so clarity, portability and solid documentation are essential. Let me know your estimated timeline and any questions you need answered before we begin....

...bring in SQL for joins or look-ups if it expedites the process. For the analysis itself, I expect visualisations—line graphs, heat-maps, or cohort-style charts—generated in Matplotlib, Seaborn, Power BI, Tableau, or a comparable tool. Choose whichever gives the clearest story and is easiest for me to update later. Deliverables • A cleaned, consolidated dataset in CSV format • An editable notebook or script that reproduces the cleaning and trend calculations • A concise report (PDF or slide deck) explaining the trends, complete with annotated charts and a short narrative of key findings Acceptance criteria • No missing or duplicate customer IDs in the final dataset • All steps fully reproducible from raw CSV import to final visual...

...What I need is a complete analytical workflow: data cleaning, feature engineering, exploratory insights and, most importantly, a predictive model that flags patterns worth acting on. I am comfortable with you choosing proven tools such as Python (pandas, scikit-learn), R, SQL or similar; visual output in Tableau or Power BI is welcome if it speeds up interpretation. Deliverables • A documented notebook or script that ingests the full dataset and produces a trained model ready for deployment • A concise report (slides or PDF) highlighting key drivers behind the forecast and actionable recommendations • Optional dashboard or interactive visual that lets non-technical stakeholders inspect the forecasts Acceptance criteria – Model accuracy validated wit...

... PnL and key signals. • Simple config file for API keys, instrument whitelist, risk caps per trade and per session. Deliverables 1. Python 3.x source with inline comments and docstrings. 2. Quick-start README explaining environment setup, required packages (requests, pandas, numpy, ccxt or native DeltaExchange SDK, whichever you prefer) and example configuration. 3. A short back-test notebook or script that demonstrates the momentum logic on historical exchange data so I can validate its edge before switching to live mode. 4. One short hand-off call or text walkthrough to ensure I can run, tweak and extend the bot on my VPS. If you have already worked with DeltaExchange or a similar crypto venue, let me know; otherwise solid experience with exchange REST/WebSocke...

...All results have to be compiled into a single Excel sheet—one row per case—showing docket number, court, parties, filing and termination dates, outcome classification and the generated summary, with hyperlinks to the downloaded files stored locally or in an S3 bucket. Deliverables • Source code (Python preferred, but I’m flexible) with clear setup instructions • A working executable or notebook that performs the search and produces the Google sheets or Excel report • Sample run demonstrating retrieval of foreclosure cases filed in 2017–2018 and voluntarily discontinued by the lender • Brief README describing how to adjust search parameters and rerun the scrape Accuracy of the summaries and stability of the scrape against N...

...script should mirror ARC’s official rubric so results are directly comparable to the leaderboard. • Track sample efficiency: log compute time, number of queries, and score progression so we can see where improvements come from. • Deliver reproducible runs: a single command should download the data, load the model, run the search, and print the final score. Acceptance criteria •Re-running the notebook with y keys reproduces the accuracy numbers •Plots clearly show defult vs tuned accuracy • Codebase installs with `pip install -r ` and runs on a single GPU. • Clear README explaining how to tweak evolutionary parameters for further experimentation. • document each expirements steps clearly The sooner we can iterate, the better&mda...

I already have each cover design finalised; what I need now is the full creative treatment so the range is ready for any ecommerce shelf. Your job is to turn those flat files into photo-real images of spiral-bound notebooks, then organise those images into A+ content that sells. The renders must clearly look spiral-bound and be supplied in three essential perspectives—front, side and top—so shoppers can judge thickness and build at a glance. Alongside the hero shots, please include close-up crops or call-outs that emphasise material quality, number of pages and paper type. These specification visuals are critical for marketplaces such as Amazon, Flipkart or Shopify because they replace the feel-in-hand experience. I will deliver: • High-resolution cover artwork for every...

...Your first task is to recreate the logic in Python, or C++ back-test it over robust historical data, and present objective metrics—equity curve, max drawdown, Sharpe, win-rate, and any other insights you feel are useful. Deliverables • Clean, well-commented Python script of the strategy will need to have a good command of Quant Connect platform • Comprehensive back-test report (PDF or notebook) showing data sources, parameters tested, and performance stats • Automation module wired to Interactive Brokers, with instructions so I can launch it locally or on a VPS • Short call or video walkthrough to confirm everything compiles, connects, and trades as expected If you’ve worked with pandas, backtrader, zipline Quant Connect platform , o...

I will share a purely categorical dat...classification models. Sound evaluation—accuracy, precision, recall, F1 or any metric you judge relevant—must accompany the models, followed by a concise discussion of the results and why a particular approach performs best. Please highlight your experience with similar projects when you respond; I value demonstrated know-how over long proposals. Deliverables I expect: • A well-commented Jupyter notebook covering EDA, preprocessing, model training, and evaluation • The cleaned dataset (or the code that generates it) • A brief markdown or slide deck that walks through the methodology, findings, and recommended next steps Clarity of explanation is just as important as model accuracy, as the primary goal is l...

I need a Google Colab notebook (Python) that extrcts the main written content from a web page while excluding non-essential elements, so I can consistently analyse primary text across different site types. Scope of work - Deliver a reproducible Google Colab notebook that takes a URL and returns main page text. - Provide extract_main_text(url, N) that returns the key content limited to the first N words/characters. - Prioritise body content and filter boilerplate (nav, headers/footers, sidebars, cookie banners, ads), handling varied page structures (not only <article>). Show less Additional information The notebook should let me enter a URL and N, then output clean, copy/paste-ready text (optionally include the page title).

...(pandas, SciPy, or a comparable library), then weave the statistical interpretation seamlessly into the discussion section. • Ensure every citation, table, and figure aligns with Chicago guidelines and that all references are cross-checked for accuracy. Acceptance criteria • Clean, publication-ready manuscript (tracked-changes + final version) in .docx format. • Reproducible analysis file or notebook with commented code and outputs. • Updated reference list that passes automated Chicago-style validators. • Brief summary (one page) explaining major edits and analytic decisions. If you bring field-specific insight, that’s a bonus, but first and foremost I’m after rigorous structure, airtight argumentation, and flawless presentation. ...

...a comparable tool—that lets non-technical stakeholders explore key performance metrics and trends. • Provide a short written brief highlighting the main findings, risks, and opportunities revealed by the analysis. I’ll supply the dataset, field descriptions, and business context as soon as we agree on the collaboration. Reproducibility is important, so please keep your formulas, queries, or notebook tidy and documented. Timeline and communication We will agree on a realistic schedule together; hitting that deadline and keeping an open line for quick clarifications are critical to me. Acceptance criteria • Cleaned dataset plus reproducible scripts or formulas. • Visually coherent report/dashboard that refreshes when data updates. • Insi...

I would like to reproduce the workflow laid out by Hacker & Ue...step to guarantee stable solutions over long time horizons. I will supply the exact PDE and boundary conditions once we start. Finite-difference, finite-volume, or spectral discretisations are all acceptable as long as the stability matches the paper’s results. The final deliverable should include: • Well-commented source code (Python, MATLAB, or a language you propose) • A short write-up or notebook showing that the implementation reproduces the stable time-dependent behaviour highlighted in the reference paper • Clear instructions so I can rerun the simulations on my own machine If you have experience with stiff ODE solvers, implicit schemes, and Newton iterations, I’d love to he...

I have several raw Excel/CSV files containing sales data that need a thorough clean-up bef...average order values, regional performance, and any other insights you spot. I’d like the findings wrapped into a clear, concise report delivered either as an Excel workbook (with pivot tables and charts) or a ready-to-share Power BI dashboard, whichever you’re more comfortable producing. Deliverables I expect: • Cleaned, fully documented dataset (CSV or XLSX) • Reproducible Python script or notebook • Summary statistics and visualisations highlighting key sales trends • Action-oriented recommendations presented in an Excel or Power BI report Shortlisting will be based mainly on your experience handling similar data analysis projects with Python, so ...

...driven strictly by technical analysis. Your task is to run the numbers, chart the price action, and highlight trading signals that are visible through moving averages only—simple (SMA), exponential (EMA), or both, depending on what the price data suggests. Here is what I need from you: • Clean historical price data (daily & weekly) imported into Excel, Google Sheets, or a lightweight Python notebook—whichever lets you work fastest while keeping formulas transparent. • Clearly labeled MA overlays and crossover points visualised on charts. • A short written commentary (1-2 pages) explaining trend direction, momentum shifts, and any actionable levels you spot (support, resistance, potential breakout areas). • A final file package I can ...

...model architecture itself; I am happy to keep pre- and post-processing simple as long as the neural radiance field you design excels in dim scenes. What I need from you: • A PyTorch (or JAX/TensorFlow if you strongly prefer) implementation of a NeRF variant tuned for low-illumination data. • Training and inference scripts that I can run on a single-GPU workstation. • A concise evaluation notebook that reports PSNR, SSIM and LPIPS on the validation set so I can judge improvements immediately. • Clear instructions on how to add new scenes or fine-tune further. The work is finished when I can clone the repo, point it at my dataset, launch training, and reproduce the metric numbers you provide. If you have ideas such as noise-aware encoding, exposure-base...

I need help debugging and fixing indentation issues in a Jupyter Notebook. The notebook is used for education/teaching purposes. Requirements: - Experience with Python and Jupyter Notebooks - Ability to correct code cell indentation Ideal Skills: - Proficiency in Python - Familiarity with Jupyter Notebook environment - Attention to detail and problem-solving skills Please ensure that the code is properly indented and functional for educational use.

...normalization, so you can dive straight into modelling. Your task is to craft, tune, and ensemble models that out-perform the current leaderboard benchmark, then package everything into a fully reproducible training notebook and a submission-ready inference script. Python with scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch, or TensorFlow are all welcome; pick the stack you believe will squeeze out the highest score. Deliverables • Commented training notebook(s) demonstrating data pipeline, model selection, tuning, and validation • Stand-alone inference notebook/script ready for Kaggle submission • README summarising architecture choices, hyper-parameters, CV strategy, and achieved public LB score • Brief hand-over session or doc...

I’m preparing a new notebook line and need the interior pages set up in Adobe Illustrator so they can go straight to a professional printer. Two interiors are required: • a college-ruled lined page • a matching dot-grid page Both will follow a custom trim size (I’ll provide the exact width and height after we start) with: • precise inside/outside/top/bottom margins • a 0.125" full-bleed zone • a perforation line positioned 0.25" from the binding edge Your task is to build clean, reusable templates with all guides locked on their own layer, stroke weights optimized for offset printing, and color set to CMYK. No raster effects—everything must remain vector so the manufacturer can scale or tweak line thickness withou...

...language is highly nuanced, I’d like you to blend both rule-based and machine-learning techniques: think lexicon cues for idiomatic Telugu alongside a fine-tuned transformer or any other classifier that lifts accuracy. Feel free to draw on pretrained Telugu-BERT, FastText, spaCy, custom dictionaries—whatever combination you believe delivers the most reliable hybrid model. Deliverables • Python or notebook script that ingests raw Telugu text and produces the JSON format • Trained model files (and any custom lexicons) with version control • README explaining setup, dependencies, and how to retrain or update the model • Brief validation report: precision, recall, and overall accuracy on a held-out test set of the same domain Acceptance cri...

I have a set of well-formatted spreadsheets and database exports that I need explored for patterns and overall trends. The task centres on descriptive analysis only—no predictive modelling or causal diagnostics this time. I’ll supply the raw CSV files plus a short data dictionary; you return clean, documented code (Python, R or SQL—whichever you prefer...descriptive analysis only—no predictive modelling or causal diagnostics this time. I’ll supply the raw CSV files plus a short data dictionary; you return clean, documented code (Python, R or SQL—whichever you prefer), a concise write-up that explains the main findings, and a few clear charts that illustrate the key trends. Every step should be reproducible, so please keep scripts, queries and any note...

...of the dog and handler. • For surgery shots you can play with fur colour, lighting, angle or the dog’s position so the scene feels entirely new. Volume & output target Hundreds of originals are waiting, and I need 3–4 solid, publishable variations from every single one. A repeatable pipeline matters more than a one-off batch. What I need from you 1. Prompt templates or a small script/notebook that ingests the existing image and injects your crafted prompt. 2. Clear, step-by-step instructions so I can rerun the process and slot in my manual quality pass where you recommend. 3. A short demo using three sample photos to prove the method works before we roll it out to the full library. If you have a smarter or more creative idea than prompt enginee...

...median, variance, standard deviation, covariance), visualisations that highlight key insights (time-series plots, histograms, perhaps a correlation heat map), and a concise written interpretation of what the numbers show. I’m comfortable with Python, so a Jupyter Notebook built with pandas, NumPy, SciPy and Matplotlib or Seaborn is ideal. If you prefer R or MATLAB, that’s fine too—just keep the code readable and reproducible. Deliverables • Cleaned data file in the same structure as the original • Well-commented analysis notebook or script • Exported graphs (PNG or PDF) • Short report (1-2 pages) summarising findings and highlighting anything unexpected No machine-learning modelling is required; this is purely a statistica...

...up being text, numerical tables, or even images—I’m still finalising input formats—so I’m open to whichever workflow you recommend. The tech stack is flexible: whether you prefer Python with Pandas/NumPy, R and tidyverse tools, or a well-structured MATLAB script, propose the environment you’re most productive in and explain why it suits the task. Deliverables • A fully reproducible script or notebook with clear, in-line comments • The processed dataset in an agreed format (CSV, Parquet, or similar) • A concise README covering setup, execution, and a summary of each processing step Acceptance criteria • All steps run end-to-end on a fresh machine after installing listed dependencies • Output dataset passes basic sanit...

...Please tidy the CSVs, resolve missing values and duplicates, and engineer any features you feel will sharpen the insights. From there, apply clustering or an equivalent technique you trust (K-Means, Hierarchical, RFM, or another you can justify) to uncover distinct groups in the data. Once the segments emerge, I’ll need two concrete deliverables: • Reproducible code: a well-commented Python notebook or R script plus a brief read-me so my in-house analyst can re-run everything without hand-holding. • Insights pack: a concise visual report or lightweight dashboard that names each segment, explains its defining traits, and highlights the commercial opportunities it opens up. Acceptance criteria are straightforward: the pipeline runs end-to-end on my sample data,...

I need a small, reliable Python script that will take raw data from my existing Excel files and turn it into finished...code just has to populate it, apply my basic formatting, and save the final workbook to a chosen folder. You are free to use pandas, openpyxl, xlwings, or a comparable library—whatever delivers a fast, maintainable solution. Once the script is in place, I want to trigger it with a single command and receive a new, fully-formatted report every time. Deliverables • A well-commented .py file (or notebook) that performs the automation • Any necessary installation or setup notes in a short README • A brief hand-off call or recorded demo so I see the workflow in action The solution should run on Windows 10 with the latest mainstream versio...

...the first four assignments in my course. Each task is a Jupyter Notebook built around matplotlib and seaborn. All I want back is a clear numeric or letter score for every notebook—no margin comments or extensive feedback, just straightforward grading based on what you’d expect in a standard undergraduate data-viz class. You’ll open the notebooks, run every cell, confirm the plots render correctly, and judge code quality and completeness against the assignment prompts. When you’re done, return the notebooks untouched and include a simple summary sheet listing Assignment 1-4 with the grade you’ve assigned to each. If a notebook will not run, just flag it so I can correct it before you proceed. Tools in play are Jupyter Notebook, ...

...Accuracy, Precision, Recall, and False-Alarm Rate. Because the project will eventually guard a sensitive site, I’m aiming for a solution that can move from laptop to field hardware without major rework. Python, PyTorch, and standard CV/RF libraries are expected; please keep your code clean, well-commented, and reproducible. Deliverables: • Trained YOLOv8 weights and training notebook • Trained RF-CNN model and training notebook • Fusion module with documented logic or architecture • End-to-end inference script that ingests live or recorded video plus I/Q data and outputs detection events • Performance report covering the four metrics above, including confusion matrices and a short discussion of failure cases Timeline is tight&mda...