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Machine Learning (ML) is a subset of artificial intelligence that enables computers to learn and make decisions without being explicitly programmed. This cutting-edge technology has a wide range of applications, from fraud detection to natural language processing and image recognition. By hiring Machine Learning Experts, clients can harness the power of ML to streamline processes, optimize operations, and gain valuable insights from complex data. Here's some projects that our expert Machine Learning Experts made real:
The possibilities for integrating Machine Learning into a wide range of projects are vast and constantly evolving. Freelancer.com hosts a community of skilled ML professionals ready to tackle challenging tasks, whether it's implementing an advanced deep learning algorithm or streamlining data analysis pipelines.
Post your project today and tap into the expertise of our talented Machine Learning Experts on Freelancer.com. Harness the power of ML to drive your business or idea forward, unlocking new levels of innovation, efficiency, and competitiveness. Don't miss out on the benefits that Machine Learning can bring to your venture - join thousands of satisfied clients who have successfully unlocked the potential of ML with the help of Freelancer.com!
Na podstawie 87,101 opinii klienci oceniają nas na Machine Learning Experts 4.9 na 5 gwiazdek.Machine Learning (ML) is a subset of artificial intelligence that enables computers to learn and make decisions without being explicitly programmed. This cutting-edge technology has a wide range of applications, from fraud detection to natural language processing and image recognition. By hiring Machine Learning Experts, clients can harness the power of ML to streamline processes, optimize operations, and gain valuable insights from complex data. Here's some projects that our expert Machine Learning Experts made real:
The possibilities for integrating Machine Learning into a wide range of projects are vast and constantly evolving. Freelancer.com hosts a community of skilled ML professionals ready to tackle challenging tasks, whether it's implementing an advanced deep learning algorithm or streamlining data analysis pipelines.
Post your project today and tap into the expertise of our talented Machine Learning Experts on Freelancer.com. Harness the power of ML to drive your business or idea forward, unlocking new levels of innovation, efficiency, and competitiveness. Don't miss out on the benefits that Machine Learning can bring to your venture - join thousands of satisfied clients who have successfully unlocked the potential of ML with the help of Freelancer.com!
Na podstawie 87,101 opinii klienci oceniają nas na Machine Learning Experts 4.9 na 5 gwiazdek.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 on a daily cadence. You are welcome to mix sources when one is fresher than another. The detector has to work at desert scale, so please build it with an established computer-vision framework (e.g., TensorFlow, PyTorch, YOLO, or a similarly...
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...
INGENIERO SENIOR DE IA: SISTEMA RAG MULTIMODAL ON-PREMISE CON APRENDIZAJE CONTINUO 1. CONTEXTO Y DESAFÍO REAL proyecto del sector de la trefilería y el galvanizado con más de 40 líneas de producción activas. 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 y democratice el conocimiento técnico que surge en el día a día. 2. LA SOLUCIÓN: "THE KNOWLEDGE LOOP" B...
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...
I am seeking an experienced academic researcher to deliver a complete, journal-ready research paper on Explainable AI (XAI) for predicting and interpreting student academic performance. The study must use multiple academic data sources (exams & quizzes, assignments & projects, and class participation records), which I will provide in CSV format. Scope of work: • Clean, preprocess, and align datasets using student IDs and time frames • Perform relevant feature engineering • Build at least one strong predictive model (with optional comparisons) • Apply explainability techniques such as SHAP, LIME, decision trees, or equivalent, with clear justification • Evaluate predictive performance and interpretability • Produce publication-quality visualizat...
I’m preparing a research paper that demonstrates how explainable AI can predict and interpret student academic grades using a mix of exams and quizzes, assignments and projects, plus class participation records. I already have raw datasets in CSV form; what I need is the complete experimental pipeline and a well-structured manuscript ready for journal submission. Here’s what I’m expecting: • Clean and engineer the three data sources so they align on student IDs and time frames. • Build at least one solid predictive model—feel free to compare alternatives—but tie every result back to a clearly articulated explainability layer (e.g., decision trees, SHAP, LIME or any other method you justify). • Evaluate accuracy and, just as important, hig...
I have a draft research proposal that needs a careful editorial pass before submission. The document is complete in terms of content, but I want it to read smoothly, follow academic conventions, and convince reviewers of its merit. The proposal is related to machine learning, security, and wireless. So, you must be in the area. What I expect from you: • Line-by-line editing for clarity, concision, and scholarly tone • Consistent formatting of headings, citations, tables, and figures to match standard style guides (APA or Chicago—whichever best fits the context you identify) • Light re-organization where paragraphs or sections could flow better • A tracked-changes file plus a clean, ready-to-submit version I’m open to suggestions on strengthen...
I have a cleaned dataset containing donor health information and I want a lightweight web app that predicts the likelihood of a person making a future donation. When a visitor submits their details, the model should output a single prediction score on screen—no extra charts or recommendations—then quietly trigger an automatic email with the same score to the user and a copy to me for tracking. Here is the flow I’m after: 1. Train a supervised ML model on the provided health-related features. Accuracy is important, but keep the pipeline transparent so I can retrain it later if we add more data. 2. Wrap the model in a simple website (Python Flask or Django, React, or any stack you are comfortable with). The form collects the required health inputs, calls the model, and...
Necesito estructurar un proyecto de emprendimiento pensado para estudiantes de secundaria que combine un servicio y un catálogo de productos, ambos 100 % digitales. La idea debe ser lo bastante sencilla para implementarse en el aula, pero lo bastante sólida para mostrar cómo se vinculan creatividad, viabilidad económica y tecnología. Lo que espero recibir es un documento guía que incluya: • Concepto del negocio y propuesta de valor. • Descripción clara del servicio digital principal (ej.: tutorías en línea, micro-cursos, suscripciones a contenido). • Listado de productos digitales complementarios (plantillas, e-books, recursos descargables). • Público objetivo, canales de venta y estrategia de ...
AI & Full-Stack Tech Client Acquisition Partner Needed (Commission-Based) I am an experienced Full-Stack AI & Software Engineer with strong hands-on expertise in building production-ready systems, including: AI / LLM Development (OpenAI, Gemini, LangChain, RAG, AI Agents) Machine Learning & Data Science (Python, Pandas, NumPy, Scikit-learn) Backend Development (Python, Node.js, REST APIs) MERN Stack (MongoDB, Express, React, Node.js) DevOps & Deployment (Docker, CI/CD, Cloud hosting) Automation & AI Chatbots (WhatsApp, Web, CRM integrations) I deliver scalable, high-quality solutions with clear communication and on-time execution. Role: Client Acquisition Partner I’m looking for a motivated, reliable partner who can bring genuine AI / software development proj...
Looking for AI Expert and Engineer who has good experience in using different AI tools available like chatgpt claude etc Must be able to create AI agent and Automation Also expert in AI Content creation and Marketing
I'm seeking an experienced AI developer to create a computer vision model focused on detecting people. The model will need to function effectively in both indoor and outdoor environments. Key Requirements: - Primary function: Object detection with a focus on people - Adaptable to both indoor and outdoor settings - High accuracy and reliability Ideal Skills and Experience: - Expertise in AI and machine learning - Strong background in computer vision, particularly in object detection - Experience with datasets and training models for varied environments - Proficiency in programming languages such as Python, and familiarity with libraries like TensorFlow or PyTorch Please provide examples of similar projects you've completed.
I need a senior-level specialist to harvest product data from several e-commerce sites and deliver it in a single, well-structured CSV file. The task demands production-ready techniques—think Scrapy spiders hardened with rotating proxies, Selenium or Playwright for dynamic content, and solid anti-bot countermeasures. The information I’m after is very specific: product names, prices, pictures, and SKU. Nothing less, nothing more. Your solution must run reliably at scale, cope with frequent layout changes, and leave no trace that could trigger blocks. Python is the preferred stack, but if you have a proven alternative that meets the same bar, I’m open to hearing it. To be considered, include in your proposal: • At least one example of a comparable e-commerce scrapi...
I want to enrich my online shoe store with an AI-powered recommendation engine that studies each shopper’s purchase history and instantly serves up the pairs they are most likely to buy next. The model can draw on three data streams—user account data, my e-commerce platform records, and any third-party customer datasets I supply—to build a unified profile and surface truly personal suggestions. Here is what the finished job looks like from my side: • A trained model (Python preferred, TensorFlow or PyTorch are both fine) that ingests the above data sources, updates itself regularly, and outputs ranked product recommendations in real time. • An API or embeddable snippet I can drop into the product and home pages to display “You might also like” sh...
I’m looking for a data scientist based anywhere in Latin America to help me create reliable predictive models for a finance-focused project. You’ll start with large historical datasets stored in SQL and deliver models that accurately forecast key financial indicators. I work mainly with Python, so you’ll find Pandas, NumPy, Scikit-learn and, when deep learning is justified, TensorFlow already in place. If you prefer R for certain tasks, that’s perfectly fine as long as the final workflow remains reproducible. The end-user needs to consume insights through Power BI, so once the model is validated I’ll ask you to craft intuitive dashboards that highlight drivers, confidence ranges and any red-flag anomalies the model detects. Solid statistical grounding is esse...
We have a platform that requires user to do a face capture, means user will take a live picture of themselves The goal is to ensure that only real users use our system. Let me know if you have done anything like this or capable
## Full Project Plan – Sports Prediction Mobile App ### Product Goal Develop a data-driven mobile application that provides real-time sports match predictions using advanced statistical models and AI. The app will deliver professional insights, personalized notifications, and operate under a VIP subscription model. --- ## Supported Sports (MVP) - Football (Soccer) - Basketball --- ## Real-Time Sports Data The application will integrate with a third-party sports data API (to be selected by the developer) in order to display: - Live match scores - Team lineups before games - Key match events such as goals, fouls, substitutions, and other major incidents - Live match statistics --- ## Prediction Model The prediction system will be based on a combination of...
I want a production-ready Python algorithm that can scan the Nifty 50 throughout the session, weigh profit opportunities against downside risk, and fire off intraday orders several times a day when the reward-to-risk profile is attractive. Core logic • Fuse three data streams in real time: historical price series, live technical-indicator feeds that you compute on the fly, and sentiment or headline signals drawn from the latest market news. • Use that blended input to generate probabilistic forecasts, then translate those forecasts into position sizing that keeps risk in check while still pursuing upside. • The system must be able to trigger, modify, and exit trades automatically during market hours—no end-of-day batching. I code in Python myself, so please kee...
Seeking an experienced full-stack/ML developer to build a secure, cloud-based web platform for analyzing anonymized dental X-rays. The tool enables upload of DICOM files, automatic anonymization (strip all metadata/identifiers), AI-driven detection & annotation of pathologies (caries, periodontal disease, bone loss, cysts, etc.), visual overlays, confidence scores, and report generation—all with strict patient privacy, no storage of originals, and human oversight required. Key Requirements: • Clean React/ frontend with drag-and-drop upload, DICOM viewer (e.g., ), annotation overlays & heatmaps. • Python backend (FastAPI preferred) + secure auth, encrypted file handling, and cloud storage (AWS S3/GCP). • PyTorch/TensorFlow ML models (fine-tune YOLO/U-Net/M...
I’m putting together a series of college-level workshops and need an expert who can both design and deliver engaging, lab-style sessions on AI, NLP, and machine learning. The audience will be under-grad and post-grad students who already code in Python but have limited exposure to real-world AI pipelines. Scope The program should span three core tracks—an approachable “Introduction to AI & ML,” a set of “Hands-on NLP Projects” that let students build something tangible, and a closing block on “Advanced Machine Learning Techniques” that shows them what’s possible beyond the basics. Because the colleges have explicitly asked for hands-on labs rather than slide-only lectures, your material needs to revolve around live coding, intera...
Hi. I need personal AI for coding, I need complete website for login , signup - I need saas admin dashboard, user dashboard - I need we can tell personal ai to make any website through prompt and it make complete and each database table he make unique table for each project with : ai generate roadmap, analyse project, build architect memory, load schema, sync files - so if we ask related to this project he can reply accordingly and make changes etc in it - I need option to upload our any existing code of vb6, delphi, php, or any language , this ai will analyse it and make the changes and remove the error and make it 1 click installation. - if we upload and project he can able to make it 1 click installation , may be it for website or for desktop app, he can make it for installation setup. ...
We are looking for a freelance marketing / lead generation professional who can bring IT projects and client requirements for our company. Our service offerings include AI/ML, .NET, Java, and Python development, along with digital marketing services such as SEO and Meta (Facebook/Instagram) Ads. We work across domains including logistics, e-commerce, retail, and mobile & web applications. You will not be responsible for development or execution. We already have in-house developers and a digital marketing team. Your role is to identify, approach, and convert clients/projects and hand them over to us. Compensation can be commission-based, per-project, or retainer + commission, depending on results. If you have proven experience in IT project marketing, B2B lead generation, or client...
I need a robust workflow that taps directly into the Sentinel satellite constellation to track current-day forest loss across tropical regions. The end goal is near-real-time monitoring: a clear indication, week by week, of where fresh clearing is happening so I can flag hotspots and act quickly. Scope of work • Acquire and pre-process the latest Sentinel imagery for my specified AOIs in the tropics (cloud masking, atmospheric correction, seamless mosaicking). • Run an automated change-detection routine that distinguishes new clear-cuts from seasonal or spectral noise. • Output intuitive products—shapefiles, GeoTIFFs, and a simple dashboard or web map—that visualise forest-loss polygons with dates, area statistics, and confidence scores. Acceptance cr...
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I want to build a Windows-only application that watches the live screen, detects people—including stylised in-game characters—in real time, and immediately drives a game controller so the crosshair locks onto and tracks that target as it moves. The workflow I picture is straightforward: the program captures frames, an AI model spots the person, and a virtual stick signal (XInput, vJoy or a comparable driver) nudges the aim every frame so it stays centred. Smoothness and speed are critical. On a 1080p feed I’m aiming for roughly 60 fps with no more than 40–50 ms end-to-end latency, so techniques such as YOLOv8, TensorRT or a lightweight custom network combined with OpenCV screen capture should fit. You’re free to choose Python, C++, or another language as long...
More details: What type of fashion tech MVP are you looking to build? virtual try on with fit prediction What key features do you want in your virtual try-on system? Size and fit prediction What type of size and fit prediction functionality do you need? Measurement-based predictions, User profile customization
CLOUD-NATIVE SUPTECH PLATFORM Developer Implementation Master Specification (PoC Build Pack) 1. PURPOSE OF THIS DOCUMENT This document provides the complete technical build specification for developers implementing the Cloud-Native Regulatory System (CNRS) — a supervisory technology platform for central bank supervision, risk analytics, compliance monitoring, early-warning systems, fraud detection, and stress testing. The platform is cloud-native (AWS), modular, AI-enabled, and supports regulatory analytics aligned with Basel III, AML/CFT, and Risk-Based Supervision frameworks. 2. SYSTEM OBJECTIVES The system must: Ingest regulatory data from financial institutions securely Validate, store, and process supervisory datasets Compute prudential ratios and compliance rules Detect fraud...
I already have a working object-detection pipeline written in Python, and I now need that same logic moved into a cleaner, better-structured Python codebase that’s easy to maintain and integrate into a larger application. Think of it as a conversion/refactor: exact same model, exact same results, but with modern syntax, clear separation of concerns, and thorough inline comments. You’ll start from my original scripts and checkpoints, preserve every bit of accuracy, and hand back a fully functioning module (including a simple demo script) that can be installed with pip-installable requirements. Feel free to streamline library calls—TensorFlow, PyTorch, OpenCV, or whatever is currently in place—so long as the final inference output matches the reference I provide. De...
I’m in the development phase of an Azure Machine Learning project and need a seasoned practitioner to mentor me through model training and evaluation. The workspace is set up and the data is in place; what I’m looking for now is practical, hands-on coaching that will leave me confident about every line of code I run. Using Python and the Azure ML SDK, you’ll help me: • Refine and execute training scripts, choose the right compute targets, and organise experiments. • Build an evaluation workflow that logs metrics, registers the best model, and makes results easy to visualise and share. We’ll work through shared sessions(need to check if this can be shared) and brief code reviews, with you explaining the reasoning behind each step so I can replicate the pr...
I have a small batch of images—fewer than one-hundred—that need clean, consistent object-detection labelling. For each image you will draw tight, non-overlapping bounding boxes around every instance of the target classes I will supply once we start. Accuracy matters more than speed; missed objects or sloppy boxes will be rejected. Preferred workflow is any modern tool that can export to COCO JSON or Pascal-VOC XML, as these formats plug straight into my training pipeline. If you normally use LabelImg, CVAT, Supervisely, or similar, that’s perfect. Deliverables • Annotated dataset in COCO JSON or Pascal-VOC XML (your choice, just stay consistent). • A quick text report summarising class counts and any edge cases flagged during labelling. I will run a...
I already have a working Python script that identifies stripe-like patterns in still images, but it needs to move from “proof-of-concept” to a polished, deployable module. The current model does a reasonable job on simple samples, yet its accuracy drops with noisy backgrounds, it only understands a handful of stripe geometries, and it processes large batches slower than I’d like. The brief is straightforward: • Improve accuracy: fine-tune the existing algorithm—or replace it—so it handles challenging lighting and mixed-texture scenes without a spike in false positives. • Add more pattern types: extend recognition beyond the basic horizontal/vertical stripes to oblique, curved, or irregular banding the current code ignores. • Optimize perfor...
I have safety sector time-series dataset that combines three synchronized streams: sensor imagery, textual maintenance logs, and high-frequency numeric readings. The objective is to forecast future values—not merely detect anomalies—so grid operators can anticipate demand, equipment stress, and renewable supply fluctuations. Because this is a research-level effort, I’m not looking for an off-the-shelf CNN, RNN, or simple transformer stack. I need a genuinely novel architecture (or a rigorously justified adaptation of cutting-edge multimodal papers) that fuses image, text, and numeric signals into a single forecasting pipeline and demonstrably outperforms strong baselines. Key expectations • End-to-end experimentation code (Python, PyTorch or TensorFlow) with clea...
I have a kaggle dataset containing colored images and thermal image .. do feature extraction and then combine them and the do feature extraction on it
I have safety sector time-series dataset that combines three synchronized streams: sensor imagery, textual maintenance logs, and high-frequency numeric readings. The objective is to forecast future values—not merely detect anomalies—so grid operators can anticipate demand, equipment stress, and renewable supply fluctuations. Because this is a research-level effort, I’m not looking for an off-the-shelf CNN, RNN, or simple transformer stack. I need a genuinely novel architecture (or a rigorously justified adaptation of cutting-edge multimodal papers) that fuses image, text, and numeric signals into a single forecasting pipeline and demonstrably outperforms strong baselines. Key expectations • End-to-end experimentation code (Python, PyTorch or TensorFlow) with clea...
I need a production-ready object detection model built, trained, and packaged so it runs smoothly on iOS and Android devices, in a modern web browser, and as a lightweight desktop application. The same model should power every platform to keep accuracy and behaviour consistent. You are free to choose the framework you are most comfortable with—TensorFlow, PyTorch, YOLOv8, Detectron2, or another proven library—as long as the final artefacts meet these requirements: • Mobile: optimised builds (e.g. TensorFlow Lite, Core ML, or ONNX) that hit realtime speeds on mid-range phones. • Web: WebAssembly/WebGL or implementation that loads in under three seconds on a standard connection. • Desktop: a small executable or Python app with GPU support when available and ...
I am embarking on a full-stack build of a humanoid companion robot whose number-one mission is caring for an infant from birth through age five. Beyond the usual chore-support and graceful household navigation, the robot must excel at three core caregiving abilities: • Feeding – from bottle to basic solids, with portion control, temperature checks, and spill detection. • Diaper changing – autonomous removal, cleaning, and secure re-diapering, tracked in a hygiene log. • Health monitoring – continuous vitals, posture, and environmental safety checks, with instant mobile alerts. Rich, natural interaction is essential. The robot should talk and sing lullabies, entertain with simple games, and read stories or show age-appropriate educational content...
I already have two live avatars that mirror real people as they speak to one another, yet the current pipeline adds several seconds of lag. I need your help driving total end-to-end latency (mouth movement, facial animation, and generated voice) down to a hard ceiling of one second while keeping everything completely self-hosted—no paid APIs or usage-based services. The finished solution must plug straight into my existing platform and remain free for the public to use. You will begin by profiling the present stack, spotting where frames or audio buffers pile up, then redesign the generation and streaming loop so that speech-to-text, text-to-speech, facial blend-shape synthesis, and video compositing all run in near real time. GPU acceleration, WebRTC, low-level ffmpeg calls, on-dev...
The project centres on building a production-ready text-classification pipeline that leverages modern deep-learning techniques. I have a labelled dataset and need end-to-end code that ingests the text, handles cleaning and tokenisation, and trains an accurate classifier. Python is the preferred language; using PyTorch, TensorFlow or another mainstream framework is fine as long as the solution is reproducible and easy to extend. Key deliverables: • Well-commented source code (data loading, model, training loop, evaluation) • Clear instructions to run training on a fresh machine (README or notebook) • Metrics report showing accuracy, precision, recall and F1 on a held-out set • Exported model weights and a small inference script or API endpoint for batch prediction...
I need a partner who can walk me through the full process of quantifying and explaining feature importance across several classic models—specifically Linear Regression, Decision Trees and Support Vector Machines—using Python. The goal is to compare and contrast interpretability techniques such as SHAP, LIME, PDP and ICE, then package the findings so that non-technical stakeholders can easily understand why each feature matters. What I expect from you • Well-structured, reproducible Python code (preferably in Jupyter notebooks) showing how each model is trained and how the above interpretability methods are applied. • Clear visualisations and narratives that highlight where and why the different methods agree or diverge. • At least one live session (Zoom, M...
We are launching a gamified, project-based platform that empowers teams to solve environmental, social, and economic challengese. To move from concept to scalable reality, we hands-on AI project an architect who can help us implement our AI strategy. The ideal resource will be a MEAN stack/Python developer. You will be helping us create and implement the following: • An adoption roadmap that ties specific AI capabilities to each stage of our workflow and project milestones, showing where automation, prediction, or generative content delivers the most value. • A reasoned “why this, not that” selection of tools—think Hugging Face transformers versus OpenAI GPT-4, TensorFlow or PyTorch for model training, spaCy for NLP, Vision APIs for image tasks—plus ra...
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