Notebook lm jobs

...Python demo that: • Takes user-generated text prompts from the command line or a minimal UI and feeds them to the tongyi-mai-turbo endpoint. • Returns the generated image and saves or displays it. • Offers simple customization—mainly size and basic colour tweaks—so I can judge latency and output quality when minor parameters change. Keep the code lightweight: preferably a single script or notebook, plus a concise README covering setup, dependencies, and any required keys or environment variables. Clean error handling and at-a-glance logging are enough. Acceptance criteria – Runs locally with a fresh virtual environment in one pass of the README instructions. – Generates an image from any prompt I type. – Respects the simpl...

...should give good class balance and enough samples per disease category. Once the data is in place, walk through exploratory data analysis, preprocessing and augmentation inside a Jupyter notebook. From there, build and tune a convolutional neural network (TensorFlow / Keras or PyTorch are both fine) and report the usual metrics plus a confusion matrix so I can judge class-wise performance. When the model is satisfactory, save it and wrap inference in a clean Streamlit app where a user uploads a single image and instantly sees the predicted disease name along with a confidence score. Deliverables • Notebook (.ipynb) with data loading, EDA, preprocessing, training and evaluation • containing the Streamlit interface ready to run with streamlit run • Ser...

I need an 8- to 10-page conference paper that presents a hybrid machine-learning Security Information and Event Management (SIEM) framework combining Random Forest and Isolation Forest for network-threat detection. The manuscript must...Deliverables 1. Editable source files (Word / LaTeX plus figures). 2. A compiled PDF ready for direct submission. 3. A short README outlining dataset links, Python version, and command line to reproduce results. Acceptance criteria • Conforms to Springer or Scopus template without formatting warnings. • Plagiarism-free, originality score ≤ 5 %. • Experiments reproducible with the included notebook or script. Deadline: 07 March 2026. Please keep periodic checkpoints so I can review drafts, figures, and the reference...

...with OCR and map it straight into the corresponding key; if a value is missing, leave the field blank rather than guessing. Any reliable stack is acceptable. Python with Tesseract, EasyOCR, Google Vision, or a comparable engine will work as long as the final script is easy for me to install and modify. Reliability and clean code matter more than raw speed. Deliverables • A runnable script or notebook that ingests JPEG invoices and produces JSON output in my template’s structure • A concise README covering setup, dependencies, and how to add or tweak mapping rules • Sample output generated from the test images I will provide Acceptance criteria: when I run the script on the supplied sample invoices, the resulting JSON must populate every field that ap...

...downgrades, initiating-coverage notes) straight out of my one-year email archive • Parse each file, detect the company it belongs to, and save it in a dedicated Drive folder for that company—no mix-ups • Pass every saved document into NotebookLM and spin up a fresh notebook per company, ready for question-answering inside NotebookLM • Sit inside Microsoft Teams as a bot so I can type, for example, “Create notebook for HDFCBANK” or “What did the latest downgrade say about margins?” and get a reply on the spot • Turn any notebook into a podcast episode, then push the audio straight to my private YouTube channel Also automatically update notebooks whenever you there are any new documents on our emails or new resul...

...confirm the exact categories before you begin, but expect the usual high-traffic areas (Electronics, Real Estate, Automobiles) to be included. Data points • Vendor name • All available contact details (phone, email, WhatsApp, or any other channel the site exposes) Delivery You’ll give me: 1. The Excel file, one sheet per category, neatly labeled and deduplicated. 2. The script or notebook you used (Python with requests / BeautifulSoup, Scrapy, or a comparable tool is fine) so I can rerun the scrape later. Quality checklist (acceptance criteria) • Every row contains at least a vendor name plus one working contact detail. • No obvious duplicates. • File opens in current Excel without conversion warnings. If captcha handling...

...Weekly payments Long-term collaboration for consistent recruiters TARGET REGION Latin America only. Candidates may speak: Spanish (preferred) Basic English (not mandatory) CANDIDATE REQUIREMENTS Candidates must: Be 18–25 years old Verify ID to confirm legal age (mandatory) Be comfortable on camera Provide full contact information Have access to: Smartphone (mandatory) Tablet, PC or Notebook (preferred) Earphones/headphones Have stable internet connection Have a private space with no external noise for streaming...

...long as they integrate cleanly with the existing Python | Pandas | NumPy | Scikit-learn stack and can be surfaced through the current Streamlit front-end. Key points you should address • Re-examine preprocessing and feature selection only if it directly supports a higher F1-score; the interface and general UX can remain untouched. • Provide well-commented, reproducible code and a concise notebook or markdown explaining your methodology, hyperparameter tuning strategy, and why the new model outperforms the baseline on unseen data. • Update the Streamlit app so users can choose the improved model in real time, then redeploy (Heroku/Streamlit Cloud) or supply clear deployment instructions. Acceptance criteria 1. End-to-end run on my dataset yields a materi...

I need a complete, production-ready design for a 100 W LED luminaire that will serve as the main light source in a living-room set...smart-home protocol. 6. Project timeline with clear milestones and an itemised cost estimate for prototype and small-batch production. Acceptance criteria • Prototype must pass a 48-hour continuous burn-in at rated power with junction temperature < 85 °C. • Smart control should function with at least one major platform (e.g., Alexa or Google Home) out of the box. • Total system efficacy ≥ 120 lm/W measured at ambient 25 °C. • All files delivered in editable formats; documentation clear enough for another engineer to reproduce results. Clear, prompt communication and adherence to the agreed schedule are esse...

...16 $7.52 $0.23 $7.29 $0.73 $8.02 28-Oct-2022 Notebook $3.03 26 $78.78 $3.94 $74.84 $7.48 $82.33 28-Oct-2022 Clipboard $2.49 21 $52.29 $2.61 $49.68 $4.97 $54.64 29-Oct-2022 Ball Point Pen $0.30 26 $7.80 $0.23 $7.57 $0.76 $8.32 29-Oct-2022 Gel Pen $1.40 22 $30.80 $1.54 $29.26 $2.93 $32.19 29-Oct-2022 Eraser $1.12 29 $32.48 $1.62 $30.86 $3.09 $33.94 29-Oct-2022 Marker $0.77 20 $15.40 $0.46 $14.94 $1.49 $16.43 29-Oct-2022 Calculator $7.39 9 $66.51 $3.33 $63.18 $6.32 $69.50 29-Oct-2022 Highlighter $1.02 24 $24.48 $1.22 $23.26 $2.33 $25.58 29-Oct-2022 Glue $5.49 25 $137.25 $6.86 $130.39 $13.04 $143.43 29-Oct-2022 Sticky Notes $0.47 15 $7.05 $0.21 $6.84 $0.68 $7.52 29-Oct-2022 Notebook $3.03 20 $60.60 $3.03 $57.5...

...making it easy for non-technical stakeholders to see root causes at a glance. Deliverables 1. Processed dataset with all transformation scripts documented. 2. Diagnostic report (PDF or slide deck) covering sales trends over time, customer purchasing behaviour and product performance analysis, each supported by clear visuals and commentary on underlying drivers. 3. Interactive dashboard or notebook that lets us filter by date range, customer segment and product line to test scenarios ourselves. 4. Brief hand-off call or video walkthrough so our analysts can maintain and extend the work. Accuracy, transparency and clear reasoning trump flashy charts; every number must reconcile with the source data. If that aligns with your approach, I’m ready to provide sample extr...

...scikit-learn, TensorFlow, or similar—so long as it runs reproducibly on a standard Linux environment. I will supply sample data and outline the business questions once we start; from there I expect you to design and code the pipeline, select suitable algorithms, train and validate any models, and document every step clearly. Deliverables • Well-structured, commented source code • A script or notebook that executes the complete analysis end-to-end • Exported results (CSV/JSON) and a short report explaining the findings Acceptance criteria • Code runs without modification on my machine • Results replicate on a hold-out dataset within agreed performance thresholds • Documentation is thorough enough for a junior analyst to reproduce...

...regression, and K-Nearest Neighbours. I need accuracy, precision/recall, ROC where appropriate, and confusion matrices, followed by: • A 2-component PCA projection with each classifier’s decision boundary overlaid. • A short discussion of how the dimensionality reduction affects separability and model bias/variance. Deliverables (acceptance criteria) 1. Reproducible Python 3.x code (Jupyter notebook or script) that runs end-to-end. 2. Commented derivations in LaTeX, compiled into a well-structured PDF report containing figures, tables of results, and concise interpretation. 3. Source files and a brief README explaining required packages (scikit-learn, NumPy, SciPy, matplotlib, seaborn, pandas are my usual stack). If any assumption needs clarification, l...

I need assistance combining two halves of a Green's function in a Mathematica notebook and plotting it. Key Requirements: - Combine Green's function halves, possibly with a particular solution. - Generate 2D plots. - Work within a Mathematica notebook. Ideal Skills: - Proficiency in Mathematica - Strong understanding of Green's functions - Experience with mathematical plotting in 2D

I have a Mathematica notebook that is nearly complete, but I need assistance with one specific plot. The plot consists of two halves, which I can currently plot separately. However, I need help combining these two halves into a single function for further plotting and calculations. The relevant plot appears at Out[456], which should be helpful for reference. This task should be straightforward for someone experienced with Mathematica.

I’m sitting...historical insights, then build an optimization or scenario-based model that prescribes concrete actions (e.g., portfolio rebalancing, cost-cutting levers, revenue-boost initiatives). Python with pandas, NumPy, scikit-learn—or R with tidyverse—is fine as long as the workflow is fully reproducible and the logic is transparent. Deliverables • Cleaned dataset with documented preprocessing script/notebook • Visual and written summary of the historical performance • Prescriptive model code plus a brief, plain-English explanation of how it works • Final report outlining recommended actions, expected impact, and any scenario simulations Accuracy, clarity, and well-commented code are must-haves. If this matches your skill set, I&...

I need a clean, one-off scrape of a large online retailer (I’ll share the exact store and URLs once ...under the radar. Please build the script with Python—BeautifulSoup, Scrapy, Playwright, or any reliable stack is fine—as long as it can be rerun on my side without extra fees or licences. Deliverables • A single Excel workbook.  – One sheet per category or URL I provide  – Columns: Product identifier (ASIN/SKU/URL), Price, Delivery Time, Offer Type • The well-commented source code or notebook used to collect the data • Quick readme explaining prerequisites and how to execute the scrape locally This is a one-time run, so no scheduling is necessary. Let me know your proposed approach, estimated turnaround, and how y...

...run the analysis in Python or R using standard libraries such as pandas/NumPy or dplyr/tidyverse. If you prefer SQL-heavy exploration first, that’s fine too; the goal is to surface findings in a format that’s easy to digest. Deliverables • A concise written report (PDF or Markdown) summarising key insights, supported by clear visuals (plots, charts or dashboards). • The reproducible code/notebook used for the analysis, with comments so it can be rerun on updated data. • A short hand-over call or recording walking through the main results and how to reuse the scripts. Acceptance criteria • All queries and scripts execute without error on my environment. • Visuals match the results described in the report. • Findings answer th...

...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...

The assignment centres on taking live immigration feeds from government databases and shaping them into a continually updated knowledge graph, with a ...embeddings, context windows, and response ranking will all be part of this stage. Key expectations • Clean, well-documented code (Python). • Container-ready deployment scripts (Docker + Compose or Helm). • Continuous ingestion tests that confirm freshness and integrity. • A short README explaining how to spin up the stack locally and how to execute sample queries. • For Phase 2, a demo notebook or endpoint that shows at least three successful Graph-RAG queries returning correct, reference-verified answers. If you thrive on data engineering, graph schemas, and cutting-edge RAG workflows, this proj...

I have an MP4 made up of 18 static frames that currently carries the “Notebook LM” logo and Google’s default colour palette. I need each frame professionally cleaned up so the logo is completely removed — no blur, no replacement, just seamless removal — and then recoloured to match my brand identity. My brand palette is led by #0066FF, with supporting tones of #818181, #1E5BFF, #272727, and #FEFFF9. Please apply these consistently so the final output feels cohesive and unmistakably on-brand. Important: I do not need timing or animation preserved. I will handle timing and sequencing myself in Adobe. What I need is the individual frames delivered in a continuous MPEG format (or equivalent frame sequence) that I can easily reassemble and time my...

...statistics, and showcasing real-world use-cases that busy professionals can relate to immediately. I would like you to weave in hands-on demos with Python, basic Jupyter notebooks, and quick visualizations so participants leave each class with something they can try at work the next day. What I’ll need from you • A concise course outline (6–8 sessions) with learning objectives • Slide deck or notebook for each session, shared 48 h beforehand • Live instruction, Q&A, and brief post-class recap videos • Short quizzes or mini-projects for reinforcement • A final feedback summary on learner progress Tools we already use: Zoom, Google Workspace, Slack, Python 3.x, pandas, matplotlib/Seaborn. If you prefer other mainstream tools, tha...

...algorithms such as Random Forest, SVM, or a lightweight deep-learning variant if it boosts accuracy). Explain why the chosen approach suits multi-class attack detection. • Evaluate performance with accuracy, precision, recall, and confusion matrices, then include short commentary on any class-imbalance handling. • Package the inference pipeline so it runs from the command line and a simple Jupyter notebook, making it easy for examiners to execute and see live predictions. • Provide well-commented source code, a , and step-by-step instructions that go from environment setup to final evaluation. Deliverables: 1. Full Python source and trained model files 2. The processed version of the dataset plus scripts that generate it from raw data 3. A concise PD...

I need every product on a single e-commerce site captured quickly and cleanly. For each item please pull the product name, SKU, price, full description, and all image URLs (or download the images into a neatly organised folder if that is easier for you). The finished da...loss of detail. Pagination, lazy-loaded images, and variant handling should all be accounted for so the output stays complete and consistent. Acceptance criteria • CSV contains one row per product with columns: Name, Price, Description, Image_URLs • No blank or duplicate rows
 • All images reachable via the URLs provided (or physically included if you choose to download them) • Script or notebook supplied so I can rerun the scrape later, with clear instructions for any environment varia...

...generation, chain-of-thought and similar techniques. • You are comfortable architecting or extending agentic frameworks that can plan, reason and act autonomously. • Clean, reproducible Python is your default; tools such as LangChain, Hugging Face, OpenAI / Azure OpenAI, vector DBS, and orchestration frameworks are familiar territory. Deliverable for each engagement 1. A clearly documented notebook or repo with runnable code. 2. A short read-me detailing model choices, experiment setup, results and next-step recommendations. 3. If integration is part of the scope, an API or service hook demonstrating the workflow in action. I value transparent communication, rapid experimentation and well-reasoned technical decisions. If you thrive on exploring the edge of ...

...a mainstream deep-learning framework you are comfortable with—OpenCV, TensorFlow, PyTorch, or a comparable library is fine—as long as the final code runs on Windows and can be triggered from a simple command line. The model can be pre-trained (e.g., a RetinaFace or MTCNN backbone) provided you fine-tune or post-process it so false positives stay minimal. Acceptance criteria 1. A script or notebook that takes an input folder path, processes every image, and outputs: image-level JSON/CSV with face count and, when possible, basic demographic tags. 2. Cropped face thumbnails stored in a parallel folder for quick visual checks. 3. README that explains environment setup and how to rerun the analysis on new folders. That’s the whole scope—detect faces...

...parts, measurements, and joinery details. 2. Instruction engine: structure output into logical build phases, dynamically adjusting steps for different skill levels. 3. Image generation: create clear assembly visuals and cut-lists; any proven solution—Stable Diffusion, Midjourney, or similar—works as long as results are coherent and label-ready. 4. Front-end demo: a lightweight web page or notebook showcasing the two input modes and the polished, illustrated output. 5. Documentation: succinct setup guide plus comments in code so I can iterate later. Tech flexibility I’m comfortable with Python, so staying within that ecosystem (PyTorch, TensorFlow, OpenAI APIs, etc.) keeps hand-off smooth. If another stack dramatically improves performance, let’s...

...uncover the most value. Feel free to work in Python (pandas, scikit-learn), R, SQL, or any tool you prefer; just be ready to walk me through the workflow so I can reproduce it later. I can supply the data in whichever format you find most convenient—CSV, Excel, or a direct database export. Let me know your preference up front. Deliverables • Cleaned and well-documented dataset • Analysis notebook or script with comments • Visual summaries (charts or dashboards) that a non-technical stakeholder can grasp quickly • Brief written report highlighting key findings, recommended actions, and any limitations I’m happy to structure the work in milestones (e.g., initial data audit, exploratory analysis, final report) so you’re paid as ea...

I need a robust data-engineering workflow built on Databricks that connects directly to our existing data lakes. The work covers everything from ingesting raw files, through transformation and enrichment, to delivering well-structured Delta Lake tables ready for downstream analytics and machine-learning teams. The ideal flow will • autoload new ...compaction, • include notebooks or jobs scripted in Python or Scala, • leverage Databricks Workflows for orchestrated runs, and • generate basic quality metrics and logging to our chosen monitoring solution. Deliverables will be considered complete when the pipelines run end-to-end in our workspace, process a sample data-lake folder successfully, and produce clean Delta tables with documented notebook code and...

Offline Consulting Copilot Toolchain (OpenClaw + LM Studio + Ingestion Pipeline) Purpose I am looking to hire a freelancer to remotely (via Windows Remote Desktop) install and configure the local AI stack required to reach the target system described in the “Offline Consulting Copilot Project Brief”: an offline, evidence-first consulting copilot that ingests meeting recordings and turns them into a searchable, citeable knowledge base. 1) Context & Target Outcome The workstation is a dedicated Windows 11 Pro machine (RTX 5090, Intel Core Ultra 9, 64 GB RAM). All processing must run locally (no cloud). End state: LM Studio serves a local LLM via an OpenAI-compatible API (localhost). OpenClaw is installed and configured to use the local LLM endpoint and orch...

...job revolves around: • Cleaning and augmenting the dataset . • Selecting or designing the most suitable CNN/transformer architecture in TensorFlow or PyTorch. • Training and validating the model, then fine-tuning until it meets or exceeds 92 % F1 on my held-out test set. • Packaging the finished model plus reproducible training scripts and clear inference instructions (Docker image or notebook is fine). .If possible integrating back end Acceptance criteria 1. Trained model file(s) ready for GPU or CPU inference. 2. Python code that re-creates the final weights from raw images. 3. Evaluation report showing precision, recall and confusion matrix for each disease class. 4. Brief hand-off call or document to walk me through usage and future ret...

...uncover the most value. Feel free to work in Python (pandas, scikit-learn), R, SQL, or any tool you prefer; just be ready to walk me through the workflow so I can reproduce it later. I can supply the data in whichever format you find most convenient—CSV, Excel, or a direct database export. Let me know your preference up front. Deliverables • Cleaned and well-documented dataset • Analysis notebook or script with comments • Visual summaries (charts or dashboards) that a non-technical stakeholder can grasp quickly • Brief written report highlighting key findings, recommended actions, and any limitations I’m happy to structure the work in milestones (e.g., initial data audit, exploratory analysis, final report) so you’re paid as ea...

Simple & Easy Audio Generation from PDFs Using Notebook LM (Gemini Pro – Jio SIM Access) Job Description I am looking for a reliable and detail-oriented freelancer to generate audio from PDF documents using Notebook LM (Pro). The task is very simple, easy, and mostly automated. Audio generation in Notebook LM is single-click based, and the work can be done by running multiple accounts in parallel across different browser windows. Because of this setup, the entire project can be completed quickly with minimal manual effort. Notebook LM Pro access is available through Google Gemini Pro, which is currently offered to Jio SIM users only. For this reason, the freelancer must have 4–5 active Jio SIM cards to access multi...

...the full set—line, candle, and spread—into a dated folder (PNG and interactive HTML preferred) 3. Event & calendar layer The routine must scan the critical-note text, detect dates of upcoming maintenance or flow changes, and write them both to: • a CSV/JSON calendar file • a visual calendar plot or Gantt-style chart so I can see what’s coming Acceptance criteria • Reproducible Jupyter notebook or .py script with clear function blocks • Sample charts for at least one complete delivery month and one spread pair • All raw and processed data saved to DataFrames and pickled/CSV’d • README explaining set-up, dependencies, and how to point the code at new data paths Libraries I normally work with are pandas, nump...

...and storage growth are visible in one place. Finally, I need a capacity and cost projection model. It should tell me, in plain numbers, how much compute, storage, network, and monthly spend we should expect when the platform serves 50, 100, 200, 500, and 1,000 users. Feel free to pull data from AWS pricing APIs, existing CloudWatch metrics, or any sizing heuristics that make sense. A Jupyter notebook or well-documented spreadsheet is fine as the deliverable, as long as I can tweak input assumptions later. Acceptance criteria: • Unified instrumentation active on all listed jobs and services, verified in our monitoring console. • New EC2 instances show identical metrics within five minutes of launch. • Front-end database metrics appear alongside existing data...

Hello, I am looking for commission marketer,I have digital product on sellfy platform,you will earn 30 in 100 of the product,it is a Digital notebook and before it's over,of course,peace be upon you

...intelligence) becomes more sidespread. Be sure to identify the determinant in your explanation. FORMAT & SUBMISSION FORMAT: You can cut and paste the questions into a word document and then write and type your responses directly into the document and upload as a PDF or take a photo of the completed pages and upload as a PNG. Otherwise, you can cut and paste (or rewrite) the questions in your notebook (please make sure that your responses are correctly numbered), answer them, and upload as a PDF or take a photo with your phone and upload. Please prepare these these assignments long hand so that you do not spend too much time formatting, and so that you can easily show all of the necessary graphing details. SUBMISSION: When you have completed the QR, please return to ...

...understand its underlying structure through several classic unsupervised techniques—density estimation, Gaussian Mixture Models trained with the Expectation–Maximisation algorithm, PCA for dimensionality reduction, and at least one clustering approach of your choice (K-means, spectral, or another solid alternative). Here is what I need from you: • Write original, well-commented Python code (Jupyter notebook or modular .py files) that loads the data, implements each method from scratch or with scikit-learn where appropriate, and keeps functions neatly separated. • Generate clear visual outputs: likelihood curves for EM, PCA component plots, cluster label overlays, and any other plots that make results intuitive at a glance. • Compare model fit and ...

I need the full membership ...You may use the scraping stack you prefer—Python with BeautifulSoup or Scrapy, Node with Puppeteer, a headless browser, etc.—as long as the result is complete and well-structured. I will provide the target URL and any login credentials immediately after we start. Deliverables • CSV file containing one row per member with separate columns for each contact field found • The scraper script or notebook so I can rerun it later if the site layout stays the same Acceptance criteria • All visible members captured (spot-checked against the live site) • No duplicate rows • File opens without errors in Excel and Google Sheets If you’ve handled similar directory or membership scrapes before and can turn this...

...geographic spreads, and any other high-level patterns hiding in plain sight. You may work in Excel, Python (pandas, matplotlib, seaborn), R, or a BI tool such as Tableau or Power BI; choose whichever environment lets you move fastest while keeping results transparent and reproducible. Deliverables • A cleaned, well-documented version of the original customer data • A concise report (PDF or notebook) explaining methods and key descriptive findings • Clear visualisations that make the numbers easy to digest (charts, tables, dashboards) • A brief hand-off call or notes so I can repeat or extend the analysis later All insights must stem from descriptive analysis only; no forecasting or prescriptive modelling is required at this stage. If anything in t...

...geographic spreads, and any other high-level patterns hiding in plain sight. You may work in Excel, Python (pandas, matplotlib, seaborn), R, or a BI tool such as Tableau or Power BI; choose whichever environment lets you move fastest while keeping results transparent and reproducible. Deliverables • A cleaned, well-documented version of the original customer data • A concise report (PDF or notebook) explaining methods and key descriptive findings • Clear visualisations that make the numbers easy to digest (charts, tables, dashboards) • A brief hand-off call or notes so I can repeat or extend the analysis later All insights must stem from descriptive analysis only; no forecasting or prescriptive modelling is required at this stage. If anything in t...

I want a set of AI-powered agents, hosted in a GitHub repository, that focus on data analysis while re...as Pandas, spaCy, or LangChain would fit well; feel free to propose alternatives if they serve the same purpose. Everything should live in a well-organised GitHub repo, complete with clear commit history and a README that lets me spin the agents up in minutes. Deliverables • Fully functional agent code in GitHub • Setup instructions and dependency file • Sample dataset plus demonstration notebook or script • Brief usage guide showing how new semi-structured files flow through the system and end in an analysed state Once I can pull the repo, run a single command, and watch the agents clean, structure, and analyse a fresh batch of data, the work will b...

...explore it with whichever tools you prefer—Excel, SQL, Python (Pandas, Matplotlib, Seaborn) or a BI platform such as Power BI or Tableau—as long as the final insights are easy for a non-technical stakeholder like me to grasp. Statistical jargon is fine in the notebook or appendix, but the main findings need plain-English explanations. Deliverables I expect: • A short written report (PDF or slide deck) summarising revenue trends, customer demographics and product performance, supported by clear charts. • A reproducible working file (notebook, .pbix, .twbx, or Excel workbook) so I can refresh the analysis with new data later. • The cleaned dataset you used, saved separately. I will provide the raw data as soon as we start; please keep it co...

...keep the approach modular and scalable. Because the pages sit behind authentication, the username and password can be hard-coded directly in the script; no interactive prompts or external files are necessary this time. Anti-blocking tactics (session persistence, realistic headers, controlled request pacing, etc.) are mandatory—I want to be able to run the notebook repeatedly without getting shut out. Deliverables • A Jupyter notebook (.ipynb) containing the login routine, table-parsing function, and an example call that exports a CSV • Any helper modules or requirements listed in a so I can recreate the environment quickly When you bid, share a concise example of past scraping work that proves you can handle authentication-gated content and large ta...

...multichannel wave files, synchronised physiological traces (ECG, EDA and respiration) and a draft protocol for train-test splits. What I still need is the deep-learning firepower to turn this into a working model, coded cleanly in Python with TensorFlow or PyTorch, complete with training scripts, inference wrapper and clear documentation. I’ll share the data dictionary, baseline metrics and an annotated notebook outlining some early experiments. From there, I’d like you to refine preprocessing, design an appropriate architecture (e.g., CNN-RNN or transformer fusion), implement cross-validation and deliver a model that meets or beats the current baseline F1. Deliverables • End-to-end training code, neatly commented • Saved model weights plus an inferenc...

...better insights ## Tools & Technologies * Python * Pytrends (Google Trends API Wrapper) * Pandas * NumPy * Matplotlib * Seaborn * Jupyter Notebook ## Project Structure ``` ├── google data analysis # Main notebook ├── # Project documentation ``` ## Key Analysis * Interest over time (trend analysis) * Country-wise keyword comparison * Related queries and keywords analysis * Data visualization using line charts and bar plots ## How to Run 1. Clone the repository 2. Install required libraries: ```bash pip install pytrends pandas matplotlib seaborn ``` 3. Open the Jupyter Notebook 4. Run the cells step by step ## Results & Insights The project reveals how search interest varies by country and time, highli...

I have a large collection of raw text documents and images that I need turned into clear, actionable insights. The job centres on exploratory data analysis rather than predictive modelling: I want to understand patterns, themes and relationships hidden inside both formats. Here is what I expect at the end of the engagement: • A well-commented Python (or R) notebook that walks through preprocessing, cleaning and exploratory techniques applied to the text and image sets. • Concise visual summaries—charts for the text, heat-maps or feature plots for the images—exported in high-resolution formats I can drop straight into presentations. • A short written report (PDF or Markdown) highlighting key findings, unusual correlations and any recommendations that...

...analysis—think clear statistics, trends, and visual snapshots—without venturing into predictive modelling or prescriptive optimisation. All raw data will arrive as comma-separated files. You are free to use Python (pandas, NumPy, Matplotlib, Seaborn), R, Excel Power Query, or a comparable toolkit, as long as the workflow is reproducible and well-documented. Deliverables: • A concise cleaning script or notebook that imports each CSV, handles missing or inconsistent entries, and outputs a tidy dataset • A written summary (PDF or Markdown) of key descriptive metrics—averages, distributions, correlations, outliers—tailored to a finance context • At least three intuitive visualisations (e.g., time-series plots, bar charts, heatmaps) ready f...

...weekday versus weekend • month by month I’m interested in concrete, data-backed stories: which products spike on Saturdays, whether certain customer segments shop more mid-week, seasonal category swings, ticket size trends, and anything else you spot that helps me fine-tune promotions and staffing. Deliverables • A merged, tidy dataset ready for future modelling • A well-commented Jupyter notebook showing the full analysis pipeline and visualisations • A concise PDF or slide deck highlighting key findings, charts, and actionable takeaways • A short README with environment details so I can reproduce results Acceptance Results must run end-to-end on a fresh environment (Python ≥3.9). All figures should be labelled and formatted for d...

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