Makine Öğrenimi (ML) Jobs

I’m ready to turn a fresh idea into a working MVP and need an AI specialist who can own the end-to-end predictive analytics layer. The single most important outcome is a model that takes my existing data, produces reliable forecasts, and is simple enough to slot straight into a lightweight product demo. Here’s the scope in plain words: • Select and train an algorithm that balances accuracy with speed—feel free to use Python, TensorFlow, PyTorch, or another framework you prefer, so long as the environment is reproducible. • Wrap the model in a small REST or GraphQL API so I can call predictions from a basic front-end. • Hand over deployment instructions for a cloud environment (AWS, GCP, or Azure—your choice) so the MVP runs in a real setting, n...

I'm looking for a skilled machine learning expert to help with my final year university project. The goal is to identify different sleep stages using multimodal data, specifically ECG patterns and blood pressure signals. Key Requirements: - Analyze ECG and blood pressure data - Develop a machine learning model to estimate sleep stages - Utilize existing dataset Ideal Skills and Experience: - Strong background in machine learning - Experience with ECG and blood pressure signal analysis - Proficiency in data processing and model development - Familiarity with sleep stage identification techniques

I’m building a retrieval-augmented generation (RAG) pipeline and need a specialist to stand up the vector database layer for my large-language-model workflow. All content going into the store will be purely textual—think markdown files, knowledge-base articles, and long-form documents—so the schema, chunking strategy, and embedding approach should be optimised for fast, accurate text search. Here’s what I’d like from you: • Recommend and deploy a production-ready vector database (Pinecone, Weaviate, Chroma, Milvus or a comparable option). • Design a text-specific embedding and metadata schema, including parameters such as chunk size, overlap, and namespace strategy. • Build ingestion scripts that batch-process my existing documents, generate em...

Sto avviando un progetto di intelligenza artificiale pensato per gestire e ottimizzare i processi di marketing e vendite. Cerco una figura capace di: • Analizzare i dati esistenti (CRM, campagne, fatturato) per individuare pattern rilevanti. • Automatizzare attività ripetitive, come l’invio mirato di e-mail o la profilazione dei lead. • Generare insight in tempo reale che guidino le decisioni commerciali. • Fornire previsioni sull’andamento delle vendite e sull’efficacia delle iniziative di marketing. Mi interessa una soluzione funzionante end-to-end: dal reperimento e pulizia dei dati alla messa in produzione del modello, con dashboard di reportistica chiara e documentazione di utilizzo. Preferisco tecnologie consolidate (Python, scikit...

- Implement voice-to-task automation in Roman Urdu/Hindi, English, or Arabic. - Develop drawing and toolpath generation based on input dimensions or customer requirement - Create an AI agent for client management and quotation generation. - Set up an end-to-end workflow to handle technical preparation. Experience with AI tools and automation in industrial settings - Proficiency in developing multilingual voice recognition systems - Knowledge of CNC operations and toolpath generation - Ability to integrate client management systems with AI

Project Overview We are looking for an expert AI/Computer Vision developer (or small team) to build a scalable, production-ready AI pipeline for a fashion eCommerce catalog. The goal is to automate product tagging and generate photorealistic on-model images from flat-lay photos. We prioritize cost-effective solutions leveraging state-of-the-art (SOTA) open-source models (e.g., IDM-VTON, OOTDiff, Stable Diffusion XL). 1. Automated AI Product Tagging • Volume: 20,000–40,000 SKUs/year (Batch processing required). • Scope: Fashion only (Apparel, Accessories, Footwear). • Task: Build a CV-based engine to extract attributes (Category, Color, Material, Fit, Pattern, Style, etc.). • Taxonomy: Consultant should help define a scalable tagging structure. • Requirement:...

I want to build an in-house AI system that lets my team drag-and-drop both KYC and Income documents and, in one click, receive a neatly formatted PDF report. The PDF must always include: • Eligibility check (based on the rules I will supply) • Salary details in a clear monthly breakdown table • Current obligations in a similar table • Pending documents list • Pending form details • Probable queries for the credit team All eligibility logic, standard document lists and a library of past queries will be provided so the model can be fine-tuned to our exact policies. Accuracy and consistency matter more than fancy UI; I simply need a reliable back-end that ingests scans or PDFs, extracts the data, applies the rules and returns a single consolidated...

I'm looking for an AI-driven building automation energy analyzer tailored for commercial buildings. The system should have the capability to upload comprehensive building databases and trend files in CSV, Excel, JSON, or Zip formats. Key Requirements: - Analyze overall energy consumption and efficiency ratings - Provide insights on kW consumption versus energy savings - Identify faulty equipment and potential energy savings Ideal Skills and Experience: - Expertise in AI and machine learning - Strong background in energy analysis and building automation systems - Proficiency in handling and analyzing data in CSV, Excel, and JSON formats - Experience with commercial building energy metrics BAS System examples - WebCtrl -Honeywell Niagara -Tridium -Seimens -Alerton Once the database...

I’m evaluating security vulnerabilities in three Arabic-capable language models—Allam, Falcon, and Fanar—by running the Garak prompt-injection suite. My top priority is the technical implementation, with a particular emphasis on translating each of Garak’s 256 English attack prompts into clear, natural Arabic before the tests run. Here’s how the workflow looks: • Build a Python notebook that loads the three models from Hugging Face (PyTorch backend), pipes the Arabic prompts through Garak, captures logits and full responses, and writes everything to tidy CSV files. • Include bilingual testing so the notebook can toggle between the original English prompts and their Arabic counterparts, allowing side-by-side success-rate comparison. • P...

I want a single, turnkey application that watches my CCTV feeds, spots shop-lifters in real time, recognises grocery products on the shelves, and keeps a live head-count of customers. The core model must be YOLO, and I need the exact same code-base to compile and run on both Windows (desktop with NVIDIA GPU) and a Raspberry Pi 4. Video sources vary—some cameras stream RTSP over IP while a few older analog units reach the NVR through a capture card—so the program has to accept either type without manual re-configuration. For product recognition I care only about groceries; no clothing or electronics labelling is necessary. The model should be trained (or fine-tuned) on the most common supermarket items so false positives stay low even when shelves are crowded. Key expecta...

I’d like to turn my stock-market ideas into an AIML pattern–driven trading bot that can watch live prices, analyse them on the fly, and place orders automatically while staying within clear risk limits. The core logic must be written around AIML so that trading rules can be updated simply by editing or adding patterns rather than rewriting code. Scope • Data feed & brokerage connection: connect to reliable real-time stock quotes and an API that allows live order execution. • AIML engine: ingest my pattern files, match market conditions, and trigger buy/sell signals. • Strategy design: please propose robust, back-testable strategies suitable for liquid equities; optimisation and walk-forward testing are expected. • Risk layer: position sizing, st...

I need a seasoned statistician who can move comfortably between classical regression techniques and modern Convolutional Neural Networks. The project centres on predictive analytics: you will build, compare and explain regression-based models, explore where a CNN adds value, and present the insights through clear, publication-ready visualisations created in Python (think pandas, scikit-learn, TensorFlow/Keras, matplotlib, seaborn or Plotly—use what fits best). We will begin with a brief video call so I can walk you through the dataset, the business question and the success metrics. After that, you will take full ownership of data preparation, model selection, training, validation and visual storytelling. Expect to hand back clean, well-commented notebooks and graphics that a non-tec...

I need an expert in Python to help with data analysis and processing tasks, specifically focused on unstructured data such as text or images. The ideal candidate should be proficient in Python libraries and tools designed for handling unstructured datasets. Your role will involve creating scripts or solutions to extract insights, patterns, or other relevant analyses from the data provided. If you have a strong command over libraries like Pandas, NumPy, or specialized tools for text and image processing, I’d love to hear from you.

I need a working proof-of-concept that hardens my wireless network by analysing live traffic and flagging hostile activity the moment it appears. The model must reliably catch the attacks that worry me most: Denial of Service (DoS), Man-in-the-Middle (MitM) intrusions, classic packet sniffing, and ARP spoofing. Everything has to run in real time on a modest on-prem machine, so efficient feature extraction and lightweight inference are a priority. The task breaks down naturally into three parts. First, capture and label representative WLAN traffic—public datasets are fine as a starting point, but I also want a small tool that lets me pipe raw pcap streams into the training set so the system can learn my network's quirks. Second, build and train the detection engine: a well-comme...

I am assembling a full-stack solution that ingests live financial databases, open-source macroeconomic feeds, and user-submitted figures, then turns all of it into forward-looking insights. The core of the product is an AI layer that delivers predictive analytics and runs configurable scenario simulations; the results need to surface instantly inside an intuitive web dashboard where users create and save their own reports and visual layouts. What I need from you is an end-to-end build: • Data layer – connectors that automatically pull structured and unstructured data from the three source categories above, plus a storage design that can scale as historical records grow. • ML & simulation engine – time-series forecasting models, Monte Carlo or agent-based simula...

Proposal using CRISP-DM (not coding): •Describe problem, data, prep, modeling, evaluation •When doing Data analysis, add before and after measurement per company •Use this survey to extract the data structures and the data lookup: •Generate random dataset with 1000 records for the form shown at open-dma link above. Strictly from what the form offers!!! Generate Before and then a After dataset (a separate one with improved results). Save it to excel as and •Process the data in python •Create a function in python that will generate individual reports (word or PDF format) – sample 5 reports (for delivery), not 1000 and produce them as files. •Create visuals for the web report or individual reports as needed. •Elaborate any correlation between ...

Hiring: AI Bot Development Company – Truck Valuation System (AU-Based Company) We are an Australian-based company seeking an experienced AI development company to build an intelligent AI bot capable of performing truck valuations. Project Overview: We require an AI-powered solution that can accurately assess and estimate the market value of trucks based on various data inputs such as make, model, year, condition, mileage, location, and current market trends. Key Requirements: Development of an AI bot capable of automated truck valuations Integration with market data sources and historical sales data Ability to continuously learn and improve valuation accuracy User-friendly interface (web-based or API integration) Secure data handling and compliance with Australian data standards E...

This project will create an end-to-end, AI-powered email delivery system for a U.S. client. All work must be carried out on-site or remotely from New York State; residency is a strict requirement because of data-handling policies. Scope of work The core task is to design, train, and deploy a regression-based machine-learning model that predicts optimal email-send parameters from rich transactional data. I will supply secure access to the historical transaction logs; you will architect the data pipeline, engineer the relevant features, and iterate on model performance until it is production-ready. Once validated, the model should be wrapped in an API and integrated into our existing email infrastructure so it can trigger personalized sends automatically. Key responsibilities • Da...

I need an end-to-end deep-learning model that can pick out identical human faces across images and video in real time. The core requirements are straightforward: • Detect every human face in an image or live stream, draw accurate bounding boxes, then compare each face against a gallery to decide whether it is an identical match. • Serve three environments without extra rewrites: security-grade CCTV feeds, social-media style mobile uploads, and large photo-management archives. • Deliver low latency on a single modern GPU while still running acceptably on CPU-only hardware for lightweight deployments. I’m comfortable with either PyTorch or TensorFlow/Keras; use the framework you know best. A pre-trained backbone such as ResNet, MobileNet, or Vision Transformer is...

We seek collaboration from responsible professionals to develop a tool for our Controls, process automation use () that will be used in conjunction with our websites by our sales folks. We shall own all the work you will develop or use for development. The attachment provides the detailed scope for you. Include some reasonable time for training our folks about your work (so we can maintain) & warranty for 3 months after final acceptance, deployment. Submit relevant response to our JD only with relevant examples of work done in the past by you for satisfied clients. If no relevant examples are submitted, we shall assume you have not done this kind of work (that will not disqualify you). If you intend to use any 3rd party tools (specify now), get approval & provide their source code...

I need a working, proof-of-concept framework that ingests live and historic network traffic logs, learns from them in near-real time, and flags malicious patterns before they escalate. The core must combine traditional threat-intel techniques with machine-learning pipelines so the system continuously adapts as new data arrives. Here’s what success looks like to me: • A modular data-collection layer that can stream pcap, NetFlow, or similar log formats into a preprocessing engine. • Feature-engineering and model-training code written in Python (feel free to leverage Pandas, scikit-learn, TensorFlow, PyTorch—whatever best suits the task). • A detection component that scores incoming traffic and raises alerts via a simple REST API or CLI output. • Cl...

I'm looking for someone to develop an App similar to Cal Ai, SnapCalorie and Qalzy. I work in the fitness industry and would like to sell the app to online customers. If you think you can develop something similar, please reach out and we can discuss the details.

I need a Python-based tool that can scan video files, detect Trees, Road, Infrastructure—and leave room for many more object classes as the project grows—then save every relevant frame straight into a MySQL database. Each stored image must be linked to the corresponding frame number and any detection metadata so I can later query, filter, and analyse the results. Once the data is stored, I want a lightweight viewer that steps through the saved frames in order, overlaying the detection boxes so I can visually confirm accuracy. OpenCV for frame extraction and display is acceptable; YOLO, TensorFlow, or another modern model is fine so long as the code is clean, well-commented, and easy for me to retrain with additional classes. To keep the hand-off smooth, please include: •...

Szukam doświadczonego developera, który stworzy dla mnie bota AI do ultrakrótkoterminowego handlu kryptowalutami. Bot ma uczyć się na danych historycznych oraz bieżącym price action i wolumenie, aby podejmować decyzje w czasie rzeczywistym – wszystko w oparciu o API Binance i napisane w Pythonie. Najważniejszy dla mnie jest rozbudowany moduł zarządzania ryzykiem: automatyczne SL/TP, dzienne limity strat, kontrola wielkości pozycji oraz maksymalne obsunięcie kapitału. Oczekuję pełnego logowania każdej operacji i przejrzystych raportów, dzięki którym łatwo przeanalizuję skuteczność strategii. Chcę, aby proces pracy wyglądał następująco: • Backtest na szerokim zakresie danych historycznych (Bitcoin, ewentualnie altcoiny). • Paper trading na konc...

I'm seeking an experienced NLP developer to build a real-time pipeline that ingests text streams via API in JSON format. The primary purpose is sentiment monitoring. Key requirements: - Classify sentiment and categorize events - Output calibrated confidence levels - Deduplicate and validate data using rules - Log all activities for production Ideal skills and experience: - Proficient in NLP and machine learning - Experience with real-time data processing - Strong knowledge of API integration - Familiarity with data validation and logging techniques Please provide relevant portfolio and experience.

I need an image classification AI model to run on a Raspberry Pi 4. This model will detect whether individuals are wearing PPE kits in static images. The primary application will be in industrial sites. Key Requirements: - The model should accurately classify images as 'PPE' or 'No PPE'. - It needs to be optimized for performance on Raspberry Pi 4. - The input will be static images, not live feeds or videos. Ideal Skills and Experience: - Proficiency in AI and image classification techniques. - Experience with model optimization for edge devices, especially Raspberry Pi. - Background in developing AI solutions for industrial applications is a plus. - Ability to deliver a robust and efficient model within budget constraints.

I need help with a Python exercise focused on data analysis. Key tasks include: - Data cleaning/extraction - Visualization/plotting - Statistical analysis Ideal skills and experience: - Proficiency in Python, especially with libraries like Pandas, NumPy, and Matplotlib - Experience with data cleaning and preparation - Strong data visualization skills - Background in statistical analysis

I have a fully categorical data set and I want to explore a Reinforcement learning approach to achieve Clustering—steering clear of the usual supervised pipelines. The core goal is to let an agent interact with the data space, discover coherent groups, and maximise a reward function that reflects intra-cluster similarity and inter-cluster separation. Here is what I need from you: • Clean, well-commented code (Python preferred) that builds the reinforcement environment around the categorical features, implements the agent, and trains it until a stable set of clusters emerges. • A brief report or notebook showing how the reward signal is defined, how you tuned hyper-parameters, and how the resulting clusters can be interpreted or visualised. • Clear instructions so...

I’m building a smart irrigation setup that links a Raspberry Pi edge server with several ESP32 nodes in the field. Each ESP32 gathers data from soil-moisture probes, compact weather boards (temperature, humidity, barometric pressure), and inline flow meters, then reports everything wirelessly to the Pi for processing. Here’s what I need from you: • Python (Raspberry Pi) and MicroPython/C++ (ESP32) code that ingests the raw sensor streams, pushes them through an on-device model, and decides—within seconds—whether to start or stop the main pump and which solenoid valves to open. • An ML pipeline: training notebooks, a lightweight model (TensorFlow Lite or similar) and the inference wrapper that runs locally. The model must act on current soil-moisture rea...

I have an ongoing structural-optimization study that will be powered by a large language model. Your role is to help me develop and train the machine-learning model, integrate it with my structural analysis routines, and write clean, reproducible code in both Python and MATLAB. The core of the job is model training: we will fine-tune or custom-train an LLM so it can suggest improved structural layouts, then feed those suggestions into an optimization loop that runs finite-element calculations already available on my side. I will supply the data sets, initial scripts, and target performance metrics. You will extend the codebase, implement the training pipeline, and link everything to the optimization module. Deliverables • Python scripts and MATLAB functions that load data, train the...

I'm looking to create an autofish system that reacts to water splash sounds. Requirements: - The system should respond only to water splash sounds. - Input method for sounds should be pre-recorded. - Integration with provided YouTube link audio is necessary (convert to required format if needed). - Also want it to look in chat for the words "Turbo Fishing has procced" if it reads that it'll automatically (or the sound of a firework exploding) It'll automatically click the right click at 20cps for 7 seconds - Some sort of easy GUI Ideal Skills & Experience: - Experience with sound recognition and automation systems. - Proficiency in audio processing and conversion. - Knowledge in fishing technology or related automation. Please include any relevant experienc...

I have a production mobile app built in Flutter that now needs two things at once: a smooth migration to React Native and a fully-featured AI layer. The current codebase performs “average”—solid, but far from the speed, maintainability, and user delight I want to reach. Here’s what I need from you: • First, review the existing Flutter project and outline a clean, low-risk migration path that keeps both iOS and Android parity. • While migrating, weave in a new AI layer that boosts user experience, adds meaningful functionality, and sharpens overall performance. I’m interested in API-based models that support chat-style assistance and data-driven recommendations; prompt design and runtime optimisation will be part of the job. • Once the Reac...

I’m ready to move beyond notebooks and actually ship models, but I’d like to do it the right way, step by step, with an expert by my side. My stack of choice is Python, and we’ll be working on Google Cloud. The part I’m most eager to master is model serving and building production-grade APIs, though I still want you to frame everything in an end-to-end workflow so the pieces fit together. Here’s how I picture our work together: • Pair-programming sessions where we containerise a trained model, push it to Google Cloud (e.g., Cloud Run or Vertex AI), and expose it through a REST or gRPC endpoint. • Walk-through of best practices for versioning, environment management, and automated CI/CD so each new model can be rolled out with minimal friction. ...

The project is to build a Python-based bot that trades equities on NYSE, NASDAQ, and AMEX. It must run end-to-end without manual intervention: gathering live market data, analysing it in real time, placing orders, and continuously enforcing risk limits. Core functionality • Automated trade execution driven by a configurable strategy engine • Real-time market analysis with fast data ingestion (websocket or streaming API) • Built-in risk management: position sizing, max draw-down and stop-loss rules Technical notes Python is mandatory; common libraries such as pandas, NumPy, TA-Lib, and asyncio are expected. The code should be clean, modular, and ready to plug into broker APIs like Interactive Brokers, Alpaca, or Tradier. A lightweight front-end (CLI or simple dashbo...

Want to add custom commands upload to robot and from retroit control execute that commands

I am building an NLP-driven application that can read digital copies of paper medical charts and automatically return accurate ICD-10-CM codes. The records you will be working with come from scanned paper documents that have already been converted to text, and they include the full chart—discharge summaries, progress notes, lab results, essentially every page we receive. The tool must achieve three things in a single workflow: 1. Generate ICD-10-CM codes that reflect the latest official guidelines, AHA Coding Clinic updates, and HCC risk-adjustment requirements. 2. Validate that supporting documentation is present and flag any gaps. 3. Suggest concise, guideline-compliant physician queries when the record lacks the specificity needed for proper risk capture. Because this is h...

1. CONTEXTO Y DESAFÍO REAL Proyecto del sector de la trefilería y el galvanizado con más de 40 líneas de producción activas. El desafío no es la falta de información, sino que el conocimiento crítico es volátil: reside en la experiencia de supervisores y operarios veteranos y se transmite de forma verbal. Cuando surge una solución técnica en planta, esta no se documenta y se pierde para el siguiente turno. Buscamos desarrollar un ecosistema de IA que no solo responda preguntas, sino que capture, valide, estructure y democratice el conocimiento técnico que surge en el día a día, creando una infraestructura de inteligencia industrial sostenible a largo plazo. 2. LA SOLUCIÓN: "THE ...

I need a small application that, once given a set of latitude-longitude boundaries for a desert sector, we can use older maps for any available dates with high resolution. stores it locally, and then runs an object-detection model that flags cars and trucks only. The moment a vehicle silhouette is spotted, the program must return its exact coordinates so rescuers can be dispatched quickly. I’m flexible about the imagery source—NASA, ESA, Google Earth, or any other free feed is fine as long as it delivers cloud-free, high-resolution scenes. You can use the tool to capture screenshots by moving in circles around the selected location. The detector has to work at desert scale, so please build it with an established computer-vision framework (e.g., TensorFlow, PyTorch, YOLO, or ...

Complete Lottery Prediction and Betting Automation System (Focused on Loterías y Apuestas del Estado - Spain) 2. System Features 2.1. Historical Data Collection and Update The system must automatically download complete historical results (drawn numbers, draw dates, prize breakdowns by category, accumulated jackpots) from the first draw of each lottery, directly from or reliable associated sources. Specific sources: Euromillones: (since Feb 13, 2004) La Primitiva: (since Oct 17, 1985 – modern version) El Gordo de la Primitiva: (since Oct 31, 1993) Updates automatic at exactly 00:02 the day after each draw, using ethical scraping (BeautifulSoup/Scrapy) with proper user-agent headers to mimic human behavior. Store data in PostgreSQL (structured) or MongoDB (flex...

We are looking for a highly skilled developer or team to build a professional crypto market analytics and signal platform, similar in concept to: However, our system must deliver significantly higher-quality trading signals, advanced analytics, and scalable infrastructure. Project Scope The platform will provide: Core Features Real-time crypto charts (BTC/USDT and other pairs) WebSocket market data integration (Binance, Bybit, OKX, etc.) Technical indicators: RSI, MACD, EMA/SMA, VWAP, Bollinger Bands AI-powered signal engine (not simple indicator crossover logic) Entry, take-profit, stop-loss suggestions Multi-timeframe analysis Historical backtesting and signal performance metrics User System User authentication & dashboard Premium subscription plans Signal history &...

I need assistance with Hailo Ollama, related to machine learning. I'm unsure if it needs configuration or a fresh install. Requirements: - Expertise in machine learning software - Experience with Hailo Ollama - Quick turnaround is essential Please provide your experience and how soon you can start.

I have a curated dataset of abdominal X-ray images that needs a robust deep-learning model capable of classifying key clinical findings. The end goal is a production-ready Python solution that can consistently score above 90 % accuracy on an unseen validation set. You’ll start with any mainstream framework you prefer—TensorFlow, Keras, or PyTorch—and handle the full pipeline: data preparation and augmentation, model architecture selection, training, hyper-parameter tuning, and evaluation. Please keep the code modular and well-commented so I can retrain or fine-tune later as new data comes in. A concise report that explains your decisions, metrics, and suggestions for future improvements will also be appreciated. To help me choose quickly, focus your proposal on your exp...

I need a complete machine-learning pipeline that can look at medical images—specifically plain-film X-rays—and tell me whether each study is of the chest, abdomen, or an extremity. All input files will be standard hospital exports (mostly DICOM, occasionally PNG/JPEG), so the model must handle typical variations in resolution and contrast. What I’m after is a reproducible, well-documented solution: data preparation, augmentation, model architecture (a CNN in TensorFlow, Keras, or PyTorch is fine), training, and evaluation. Please include class-balanced splits, explain any preprocessing you apply, and show the metrics you achieve on an unseen validation set. Deliverables • Python code with clear comments for preprocessing, training, and inference • Trained ...

I have a collection of X-ray studies and I need a robust deep-learning model that can look at each image and instantly tell me which predefined category it belongs to (e.g., chest PA vs. chest lateral, cervical spine, hand, etc.). The job is strictly about classifying the type of X-ray, not diagnosing any pathology. Here is what I already have and what I expect from you: • A curated folder structure with several thousand labelled PNG and DICOM files that you can download from my secure server. • A preference for Python with either PyTorch or TensorFlow/Keras—use whichever framework you feel will achieve the best accuracy and fastest inference on a modern GPU. • Clean, reproducible code (Jupyter notebook or script) plus a short README that explains environment se...

I need a propensity-modelling software package that plugs directly into our CRM system, website analytics, and sales database, unifying those streams into a clean, continuously updated dataset. On top of that data layer, the build must train, evaluate, and deploy the best-performing predictive models—whether regression, decision-tree, neural-network, or any other technique that proves superior—then surface the results through a lightweight web interface and an API our teams can call in real time. Key deliverables • Automated ETL jobs and data-quality checks for the three sources mentioned above • Modular training pipeline with experiment tracking, lift/ROC reporting, and feature-importance visuals • Scoring service exposed via REST (or GraphQL) endpoints plu...

I’m building a smart irrigation setup that links a Raspberry Pi edge server with several ESP32 nodes in the field. Each ESP32 gathers data from soil-moisture probes, compact weather boards (temperature, humidity, barometric pressure), and inline flow meters, then reports everything wirelessly to the Pi for processing. Here’s what I need from you: • Python (Raspberry Pi) and MicroPython/C++ (ESP32) code that ingests the raw sensor streams, pushes them through an on-device model, and decides—within seconds—whether to start or stop the main pump and which solenoid valves to open. • An ML pipeline: training notebooks, a lightweight model (TensorFlow Lite or similar) and the inference wrapper that runs locally. The model must act on current soil-moisture rea...

I want to bring GitHub Copilot Agents into my own Java-based application so that they can automatically suggest code as developers type. My primary workspace is Visual Studio Code, and the core language throughout the project is Java, so the solution you give must play nicely with both. Here’s what I’m after: • A clear, working path to either connect directly to GitHub Copilot Agents from my application or to build equivalent custom agents that deliver the same real-time suggestion experience. • Code-level examples written in Java that demonstrate how the agent is invoked, passes context, and returns suggestions. • A brief walkthrough (video or written) that shows the integration running inside VS Code so I can replicate the setup on additional machines. I&...

I need to design the workflow for an LLM orchestrator, integrating with various systems. It should call the customer master DB and policy admin to identify existing clients or handle new quotes. For new cases, I'll clearly differentiate based on line of business (P&C personal auto, commercial, travel, life Insurance) . I'll focus on setting up the necessary infrastructure, models, vector DB, middleware, and PoC milestones. Citations will be needed . I’ll ensure everything fits within the architecture, including tool-calling patterns and structured forms. Here’s a concrete, LOB aware architecture you can actually brief to a dev partner or internal team. I want to embed an end-to-end AI layer into my insurance website that can greet visitors, guide them through quo...

​I am seeking a highly skilled AI technician to develop high-fidelity LoRA models for FLUX.1 [dev] and Wan 2.1. The goal is to achieve [insert goal: e.g., high character likeness / a specific artistic style] that remains consistent across both high-resolution images and video generation. ​Required Technical Expertise ​Model Experience: Proven experience training LoRAs for FLUX.1 (Dev/Schnell) and Wan 2.1 (specifically the 1.3B or 14B models). ​Tooling: Proficiency with Ostris AI-Toolkit, Musubi-tuner, or Kohya_ss. ​Dataset Management: Ability to curate and caption high-quality datasets (images for Flux, video clips for Wan). Experience with Danbooru/WD14 tagging or natural language captioning (LLM-based). ​Temporal Consistency: For Wan 2.1, you must be able to demonstrate that the LoR...

I run an internal up-skilling program for fresh graduates who have just joined our team and I’m looking for a trainer who can take them through AI agents, Python programming, and core Machine Learning concepts while walking them through a demo chatbot and one or two small sample applications. The classes will be online on Fridays, Saturdays, and Sundays, any 1–2-hour slot you prefer between 6 pm and 9 pm IST. A strong mix of digital whiteboard explanations, concise PowerPoint slides, and live screen-sharing is essential so the learners can both follow the theory and code along in real time. For each session I will need: • well-structured slide deck or whiteboard notes • the live notebook / script you write during class • a short, working demo project or e...