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I have a collection of CSV and Excel files filled with purely numerical columns that I need turned into clear, actionable insight. Your task is to take these raw tables all the way from initial cleaning through to a succinct set of findings, visualisations and recommendations that I can present to non-technical stakeholders. The workflow I expect is straightforward: import the files, tidy up missing or inconsistent values, run the exploratory statistics that uncover patterns or anomalies, then build concise plots (Python / pandas / NumPy / Matplotlib or similar) so the story of the data is obvious at a glance. If meaningful, a simple predictive model or correlation analysis would be welcome as well, but only if it genuinely adds value. Deliverables • A reproducible notebook or scr...

I need a customized GPT model to provide basic profiling data insights. Key focus areas include: - Basic profiling metrics: Spend, balance, risk metrics, industry, tenure, etc. Ideal Skills & Experience: - Experience with GPT customization - Strong background in data analytics and profiling - Familiarity with financial metrics and industry standards - Ability to deliver clear, actionable insights

Looking for someone who can complete my Google Gen AI APEC Codelabs and MCQ tests Looking for a fast and reliable person, I'm busy with some other work and can't complete these tasks. Your Goal is to complete these codelab tasks and MCQ test so that I can stay ahead in this Hackathon. Below I'm attaching a image also for your reference with deadline etc deadline : 9 June 11:30 PM not more that that You will get paid only after successful submission and submission accepted by the platform I will provide you login details etc. whatever is required Fixed Budget : ₹650 It's easy task for a experienced person. Looking forward to quality bids Start your bid with GenAI

The project centres on building an AI-powered customer-relationship-management platform where data analytics integration shapes every decision. Advanced personalisation remains a key theme, yet the first milestone is a robust analytics layer able to ingest multi-channel customer data, surface predictive insights in real time, and feed them back into the CRM for automated, highly targeted experiences. To guarantee a product users love, the plan also calls for continuous A/B testing and structured user-feedback analysis. Results from each experiment will loop straight into the design backlog so that UX refinements happen quickly and are always evidence-based. Key deliverables • Analytics engine connected to the CRM database and external data sources, producing actionable dashboa...

Sr. Data Science Engineer Experience: 4–6 Years Location: Remote Shift: 1:30 PM – 10:30 PM IST Role Overview: We are seeking a skilled Sr. Data Science Engineer with expertise in Python, AWS, machine learning, and statistical modelling. The ideal candidate will drive end-to-end ML development, perform advanced data analysis, build scalable data pipelines, and deploy models in cloud environments. Key Responsibilities: Design, build, and deploy ML models using Python and AWS SageMaker. Perform exploratory data analysis (EDA) and generate actionable business insights. Develop and maintain ETL pipelines, data ingestion, transformation, and validation processes. Manage model versioning and experiment tracking using MLflow. Collaborate through GitHub code reviews and maintain hig...

Launch of the King of Data Science Competition in the HAGO Community Today marks the launch of the King of Data Science competition within the HAGO Community. This is a special competition designed to test members’ skills in the field of data science through a series of daily questions. The competition will run for 20 days, with questions posted daily inside the community. At the end of the competition, the winning contestant will receive a cash prize, in addition to being promoted within our community and on the community’s official page on X – formerly Twitter. In the future, we will also launch competitions for Python projects, with the goal of building strong teams of data scientists within the HAGO Community. Team Formation Idea Each member has the right to crea...

I have a raw set of patient records and want to turn it into a functional medicine-recommendation engine built in Python. The system should read symptom text typed by a user, run it through a pre-trained machine-learning model, and return a ranked list of suitable medications. Scope and key tasks • Data pipeline: remove duplicate records and normalise numeric or categorical values so every observation is model-ready. • Feature selection & training: experiment with at least Random Forest and Logistic Regression; pick the best model using accuracy, precision and recall. • Evaluation report: include confusion matrices and a short note explaining why the chosen model performs best. • Lightweight dashboard: a simple Flask or Streamlit interface with one free-tex...

I need a fully-functional stock-trading bot that I can adapt to my own strategies. The core requirement is clear: it must connect to a live equities brokerage, execute trades automatically, and let me plug in—or easily edit—my own trading algorithms without touching the underlying execution code. Here’s what I have in mind: • Trading scope: stocks only; no crypto or forex integrations are required. • Broker/API: I’m open to your suggestion (Interactive Brokers, Alpaca, Tradestation, etc.) as long as the API supports real-time order placement and data retrieval. • Strategy layer: the bot should separate the execution engine from the logic layer so I can swap, tweak, or A/B test multiple algorithms. Think simple function hooks, a JSON config, or a...

Pet Intelligence Founder & Concept Creator: Jasna Kuburic Core Platform Pet Intelligence is an AI-powered pet intelligence ecosystem designed for dog and cat owners, breeders, veterinarians, researchers, and animal organizations. The platform combines: * Health tracking * Behaviour tracking * Breed intelligence * Geographic intelligence * Lineage tracking * Genetics and DNA insights * AI-powered guidance Main Modules Pet Profiles Create detailed profiles for dogs and cats. Health Intelligence Track conditions, medications, vaccinations, surgeries, allergies, and wellbeing, owner types symptoms for different level of educational and not medical advice: monitor, visit vet soon or emergency Behaviour Intelligence Track temperament, trainability, a...

I’m looking for an experienced researcher–author to co-develop, write, and successfully submit a skin-disease–detection paper to a genuine, APC-free SCI-indexed journal and takes acceptance guarantee. Scope • Craft a manuscript that introduces and validates a brand-new detection algorithm. • Build experiments around whichever deep-learning model is currently most promising—CNN, transformer, hybrid, or any other trending architecture—so long as the results outperform or clearly benchmark against existing methods. • Handle all stages from dataset curation, model training, result analysis, and figure/table preparation through to journal formatting, cover letter, and submission. • Guide the paper through peer review until acceptance. ...

I want to consistently attract qualified home-buyer leads for my real estate business by harnessing AI. The core of the job is to design and run a data-backed system that blends predictive analytics, natural language processing, and other machine-learning algorithms to pinpoint people who are ready to purchase property, capture their contact information, and deliver those leads to me in an actionable format. Here is what I need from you: • Define or source the data you will feed the models (market listings, consumer-behaviour data, social signals, etc.) and outline how you will keep it refreshed. • Build or fine-tune the models, explain the logic behind your feature selection, and show how the three techniques named above complement one another. • Set up an automated w...

Responsibilities: Guide me on how to use Snorkel AI or Snorkel Flow for my training task Help design and implement labeling functions Assist with data labeling strategy and weak supervision setup Explain how to prepare data for model training Help train, evaluate, and improve the model workflow Provide hands-on support through screen sharing or step-by-step guidance Review my current dataset and recommend the best Snorkel approach Required Skills: Strong experience with Snorkel AI, Snorkel Flow, or open-source Snorkel Experience with weak supervision and programmatic labeling Python experience Machine learning model training experience Experience with classification, NLP, text labeling, or data annotation workflows Ability to explain clearly and guide someone step by step Deliverables:...

I’m kicking off a predictive analytics programme for an IT-focused business unit in Pune and need an experienced AI consultant who can wear the architect’s hat from day one. You’ll guide the full lifecycle: shaping the use-cases with stakeholders, auditing our existing data assets, then designing a scalable machine-learning stack that can move from PoC to production without rewrites. I expect you to be comfortable choosing the right mix of Python, scikit-learn, PyTorch or TensorFlow, setting up automated training pipelines, and wiring everything into a cloud environment (AWS, Azure or GCP—whichever best fits the roadmap we draft together). Strong MLOps habits, version-controlled experiments and CI/CD for models are must-haves because this project must be repeatable...

Dont bid indian and pakistan. only seeking American or European I’m looking to connect with experienced AI Engineers who are interested in collaboration opportunities related to the U.S. tech job market. Requirements: - Strong experience in AI, ML, LLMs, RAG, agents, or backend AI systems - Good software engineering foundation - Strong English communication skills, preferably C1 level or above - Reliable, professional, and open to long-term collaboration If you’re interested, please feel free to contact me. I’d be happy to share more details and discuss possible collaboration opportunities.

I'm seeking an experienced programmer to create spatio-temporal diffusion transformers (ST-DiT) for video generation. The project involves: - Generating new videos from scratch - Enhancing existing videos - Transforming videos based on input prompts Requirements: - Proficiency in PyTorch or python - Experience with ST-DiT models -- some experience - Ability to assist in acquiring necessary datasets Ideal candidates should have a some background in machine learning, particularly in video generation and diffusion models.

I am in the middle of my master’s thesis and need a capable partner to handle the coding side of a deep-learning project on mammogram images. The core task is to build a robust model for breast-cancer diagnosis; once the network architecture is in place I can take care of statistical write-ups and broader discussion, but I need you to get the codebase production-ready and well-documented. Here’s what the collaboration will look like: • Data: I will supply the curated mammography dataset and any preprocessing scripts I have so far. • Model building: Using Python with either TensorFlow or PyTorch (whichever you work fastest with), you will design, train and fine-tune a CNN or transformer-based pipeline that targets breast-cancer detection specifically. • Resu...

I want to learn how to use ai for data engineering project

I’ve built an AI algorithm that shows real promise, yet it has never been put through a proper test run. My end-game is academic: I want to validate the model rigorously, benchmark it against established baselines, and steer it toward a publishable research paper. To get there, I’m seeking a collaborator who thrives on algorithm development. You’ll dive into my existing codebase, stress-test the logic, refine any weak spots, and help translate the results into clear, defensible findings. Along the way we can discuss experimental design, datasets, and suitable evaluation metrics so the work meets journal or conference standards. If you enjoy turning raw, untested ideas into defensible research—and you’re happy to share authorship and intellectual credit&m...

We are looking for a Python developer with experience to build a robust, local pipeline that processes Binance Futures historical data into an ML-ready dataset. The goal is to ingest public data from Binance Vision (aggTrades, all klines, and bookDepth) and output clean, normalized, lookahead-bias-free features stored in Parquet format or DuckDB. Scope of Work & Deliverables 1. Ingestion & Database Setup (Core Foundation) Data Source: Programmatic downloading of historical daily/monthly ZIP files from public (specifically aggTrades, all klines [1m], and bookDepth for BTCUSDT, ETHUSDT, SOLUSDT, XRPUSDT, BNBUSDT). Storage Architecture: Set up a local storage solution using DuckDB or Parquet to handle millions of rows without memory issues. Alignment: Parse and align different ...

We are reaching out regarding a paid strategic collaboration opportunity focused on legacy engineering assets for enterprise AI training initiatives. We are actively looking to procure: Private production-grade code repositories Historical development and operational data Multi-language enterprise applications with long-term commit history We particularly value repositories with real-world business usage, scalable architecture, engineering workflows, documentation, tickets, and collaboration data. This is a high-value, long-term engagement, with commercial opportunities ranging from ₹20,000 to ₹50 lakhs based on repository quality, historical depth, maintainability, and dataset volume. Final valuation is conducted by our technical evaluation team. We ensure: Strict NDA and confiden...

We are looking for a Python developer with experience to build a robust, local pipeline that processes Binance Futures historical data into an ML-ready dataset. The goal is to ingest public data from Binance Vision (aggTrades, all klines, and bookDepth) and output clean, normalized, lookahead-bias-free features stored in Parquet format or DuckDB. Scope of Work & Deliverables 1. Ingestion & Database Setup (Core Foundation) Data Source: Programmatic downloading of historical daily/monthly ZIP files from public (specifically aggTrades, all klines [1m], and bookDepth for BTCUSDT, ETHUSDT, SOLUSDT, XRPUSDT, BNBUSDT). Storage Architecture: Set up a local storage solution using DuckDB or Parquet to handle millions of rows without memory issues. Alignment: Parse and align different ...

We are looking for a Python developer with experience to build a robust, local pipeline that processes Binance Futures historical data into an ML-ready dataset. The goal is to ingest public data from Binance Vision (aggTrades, all klines, and bookDepth) and output clean, normalized, lookahead-bias-free features stored in Parquet format or DuckDB. Scope of Work & Deliverables 1. Ingestion & Database Setup (Core Foundation) Data Source: Programmatic downloading of historical daily/monthly ZIP files from public (specifically aggTrades, all klines [1m], and bookDepth for BTCUSDT, ETHUSDT, SOLUSDT, XRPUSDT, BNBUSDT). Storage Architecture: Set up a local storage solution using DuckDB or Parquet to handle millions of rows without memory issues. Alignment: Parse and align different ...

We are looking for a Python developer with experience to build a robust, local pipeline that processes Binance Futures historical data into an ML-ready dataset. The goal is to ingest public data from Binance Vision (aggTrades, all klines, and bookDepth) and output clean, normalized, lookahead-bias-free features stored in Parquet format or DuckDB. Scope of Work & Deliverables 1. Ingestion & Database Setup (Core Foundation) Data Source: Programmatic downloading of historical daily/monthly ZIP files from public (specifically aggTrades, all klines [1m], and bookDepth for BTCUSDT, ETHUSDT, SOLUSDT, XRPUSDT, BNBUSDT). Storage Architecture: Set up a local storage solution using DuckDB or Parquet to handle millions of rows without memory issues. Alignment: Parse and align different ...

I have a raw customer dataset that needs to be translated into clear, actionable insights about how people actually behave—purchasing habits, engagement trends, repeat-buy triggers, churn signals, and any other meaningful patterns you discover. The scope is straightforward: clean the data, choose the right statistical or machine-learning techniques, visualise the findings, and give me a concise written summary of the key behaviour patterns uncovered. I’m comfortable with whichever toolset you prefer—Python (pandas, scikit-learn, seaborn), R (tidyverse, caret), or a BI platform such as Power BI or Tableau—as long as the final output is reproducible and easy for me to explore. To gauge fit, please attach examples of past work where you turned customer data into ...

I have a sizeable set of customer demographic data—age ranges, locations, genders, income brackets and the like—and I want to turn it into clear, actionable business insights. The objective is straightforward: explore the dataset, surface meaningful patterns, and present findings that can guide our marketing and product decisions. You will receive the raw CSVs in a secure S3 bucket. Feel free to work in Python with Pandas, scikit-learn, seaborn—or any comparable stack that lets you move quickly and keeps the process fully reproducible. I’m especially interested in: • Segmenting high-value or high-growth customer groups • Highlighting correlations between demographic traits and purchasing propensity • Visualising trends in a way executives can ab...

Build Master Historical Database from Binance USDT-Margined Futures Data (2019–2026) for BTC, ETH, SOL, BNB, XRP We need an experienced data engineer / Python developer to create a single master database from Binance public historical futures data. Symbols: BTCUSDT, ETHUSDT, SOLUSDT, BNBUSDT, XRPUSDT (USDT-margined perpetual futures) Link to data: Deliverables: - Automated or semi-automated scripts to download all required daily .zip / .csv files. - Clean, merge, and store everything into one well-structured master database. - Proper timestamp alignment, data quality checks, handling of missing days, compression, and indexing for fast querying. - Clear documentation + scripts so we can update the database in the future. - Final database schema explanation and sample queries. &bu...

I’ve built an AI algorithm that shows real promise, yet it has never been put through a proper test run. My end-game is academic: I want to validate the model rigorously, benchmark it against established baselines, and steer it toward a publishable research paper. To get there, I’m seeking a collaborator who thrives on algorithm development. You’ll dive into my existing codebase, stress-test the logic, refine any weak spots, and help translate the results into clear, defensible findings. Along the way we can discuss experimental design, datasets, and suitable evaluation metrics so the work meets journal or conference standards. If you enjoy turning raw, untested ideas into defensible research—and you’re happy to share authorship and intellectual credit&m...

I need a formally structured expert-opinion letter that speaks with authority on the application of data science in healthcare. The exact sub-topic—whether predictive analytics, patient data management, or AI-driven diagnostics—will be confirmed with you once we connect, so please feel comfortable drawing on whichever of these domains best matches your own credentials. The letter will be shared with senior decision-makers, so it must be: • Written in clear, non-promotional language that balances technical depth with accessibility. • Backed by current literature, relevant guidelines, and any regulatory frameworks that apply (HIPAA, GDPR, FDA, MHRA, etc., as appropriate). • Signed with your professional title, affiliation, and contact details, plus a brief bi...

I need a formally structured expert-opinion letter that addresses how modern CRM, artificial-intelligence techniques and wider digital-transformation practices can be applied to a specific business scenario I will share once we start. The document should be concise—roughly 1,500 – 2,000 words—yet authoritative enough to satisfy executives, auditors and, if required, a regulator. Please draw on recognised frameworks, current market benchmarks and recent case studies to support your views. I expect clear, referenced reasoning around: • The strategic role of CRM in strengthening customer engagement • Practical AI uses (e.g., predictive analytics, automated customer service) with measurable benefits and known limitations • The organisational changes, t...

expert to design, and develop, a System Dynamics Model to strengthen its capacity for forward-looking micro-prudential supervision and forecasting. The model will provide supervisors with a dynamic tool to better understand how financial sector risks evolve in response to macroeconomic changes, policy shifts, and institutional behaviour. The primary objective is to develop a model that: • Simulates key banking sector risk indicators, including capital adequacy (CAR), liquidity, profitability, non-performing loans (NPLs), and leverage. • Integrates key macroeconomic variables such as GDP growth, interest rates, inflation, and fiscal policy changes, allowing supervisors to assess their influence on institutional risk profiles. • Provides scenario-based early warning functional...

I want a cross-platform Flutter application that acts as my digital “CA Diary,” focused exclusively on managing client information. The core flow should let me open the app, find any client instantly, and see everything relevant to our work together in one place. Key functional areas I must have: • Client profiles – basic details, PAN/GST numbers, contact data and custom tags. • Document storage – upload, view and categorize files against each client. PDF and image formats are enough for now. • Interaction history – a simple timeline showing calls, emails or in-person meetings so I can track what happened and when. • GST & IT Return modules – record returns filed, due dates and status. • Service tracking –...

Need an experienced Python Quant Developer to build a backtesting and research engine for a crypto futures trading strategy (BTC and ETH perpetual futures). This is a Phase 1 research project only. I am NOT looking for a live trading bot at this stage. The objective is to validate the strategy using historical data, realistic execution assumptions, fees, slippage and performance analysis before considering live deployment.

I’m ready to send you a raw Parquet-formatted financial time-series dataset and I need it returned fully cleaned and model-ready. The work centres on four specific steps: • Handling missing values • Scaling and normalisation • Feature engineering • Producing a consolidated master database for model training Please retain the native frequency and time index, document every transformation, and return both the processed file (CSV or Parquet—whichever keeps the structure intact) and the reproducible code or notebook you used. If you’ve tackled stock or crypto data before, this should be straightforward and quick. Once I verify the dataset loads smoothly into our existing notebooks, the job is done.

I have a daily stock-price dataset that already contains the open, close, high, and low values for each trading session. I need a fully reproducible AutoGluon time-series model that can forecasts price movement.

I have a sizeable, time-stamped collection of vehicle telematics that combines three rich streams: • GPS data • Engine data • Driving behavior data My sole objective is to turn these inputs into an accurate, production-ready regression model that can predict and ultimately improve fuel efficiency across our fleet. The data already sits in clean CSV batches, each trip keyed by vehicle ID and timestamp; your job is to move from raw files to actionable predictions. What I need from you • Build an end-to-end data pipeline that ingests, cleans, and engineers features from the three datasets above, handling missing values and synchronizing timestamps. • Select and compare appropriate regression techniques—linear, elastic-net, gradient boosting, or any ...

I have designed an algorithm that tackles a very specific data-analysis challenge and now need it translated into clean, efficient code. The underlying logic is settled; what I need from you is a production-ready implementation, thorough inline documentation, and a compact demo script that proves it works on a small sample dataset. Language is flexible—Python, R, or MATLAB all fit the brief—so pick the one you are most comfortable using while ensuring the final deliverable is easy for me to maintain and extend. I will share the mathematical formulation and sample data once we start; you will convert that into well-structured functions or classes, add comments that make each step clear, and provide a short README explaining inputs, outputs, dependencies, and how to run the demo...

I'm looking for an experienced developer to create an AI trading bot specifically for the stock market. The bot should leverage advanced technical analysis strategies to make informed trading decisions. Key Requirements: - The bot must operate in the stock market exclusively. - It should utilize various technical analysis tools and indicators. - The bot should be capable of executing trades autonomously based on predefined algorithms. Ideal Skills and Experience: - Strong background in AI and machine learning. - Extensive experience in stock market trading and technical analysis. - Proven track record in developing trading bots or similar financial software. - Ability to provide a detailed project proposal is essential. Please include a detailed project proposal in your application...

I’m working on my graduate-level capstone and have chosen to build a full-fledged recommendation system using a publicly available dataset (e.g., MovieLens, Amazon Reviews, Goodreads—whichever fits best once we outline the approach). The end goal is to demonstrate solid grasp of modern recommender techniques, from data preprocessing through model training, evaluation, and an easy-to-showcase demo. Scope of work The project has three pillars: 1. Data pipeline – ingest, clean, and transform the chosen public dataset so it’s ready for modelling while remaining fully reproducible (Python, pandas, SQL or Spark if scale requires). 2. Modelling – experiment with at least two algorithms that illustrate contrasting paradigms, for example matrix factorization (Su...

Project Title: Budget Estimation & Development of an AI Agent for School Decision Support (1,450 Students) Project Description: Hello, We are currently in the feasibility study and budgeting phase for a school project. We aim to build a Custom AI Agent that acts as a Decision Support System (DSS) for school administration. We need a professional developer/data scientist to provide us with a realistic financial quotation (development cost), estimated monthly operational costs (API & Hosting), and a timeline for execution based on the following scope and technical requirements: 1. Project Objective To build a School Management Decision Support AI Agent that analyzes historical and daily-updated student data, extracts behavioral and academic patterns, and provides actionable recom...