Tensorflow trabalhos

...nutra leads, atualize o funil, envie follow-ups e alerte a equipe sobre oportunidades críticas. 3) Análise de dados – preciso de um módulo capaz de coletar métricas de performance, descobrir padrões de compra e sugerir ações de otimização. Disponibilizarei acesso às APIs REST e webhooks dos sistemas que uso (CRM, loja virtual e marketing). Fico flexível quanto às tecnologias (Python, Node, TensorFlow, OpenAI, AWS, GCP, etc.), desde que contemplem processamento de linguagem natural, reconhecimento de voz e aprendizado de máquina, garantindo escala e manutenibilidade. Entregáveis esperados: • Código-fonte versionado e comentado • Modelos treinados + scr...

...Análise com IA; -Identificação de padrões usando Machine Learning (TensorFlow, PyTorch ou similar). -Ajuste de sensibilidade para níveis diferentes de risco. -Cálculo de probabilidade e taxa de acerto. Alertas Inteligentes; -Notificações push, som ou pop-up quando um padrão atingir a taxa de confiança definida. -Filtro por tipo de aposta (Jogador, Banqueiro, Empate, Empates Específicos). Gestão de Banca; -Configuração de stake fixa ou percentual. -Simulação de evolução de banca. -Relatórios de ganhos/perdas. Interface; -Painel responsivo e intuitivo (Web + Mobile). -ÁRea de login e personalização das preferênc...

...desenvolvedor Android (freelancer) com experiência sólida em Kotlin, Jetpack Compose e integração com modelos de inteligência artificial e OCR (reconhecimento óptico de caracteres), para dar continuidade a um aplicativo Android já funcional voltado à leitura automatizada de dados visuais em tempo real. Tecnologias já implementadas: Kotlin + Jetpack Compose (Material 3) Clean Architecture + MVVM TensorFlow Lite + ML Kit (OCR) Modelos do tipo YOLO (formato TFLite) CameraX / Camera2 API Retrofit + OkHttp + DataStore Escopo da Atuação: Manutenção e evolução do projeto existente Aprimoramento da precisão da leitura visual (OCR/IA) Integração com APIs ...

...Objetivo do Freelancer: O freelancer será responsável por desenvolver, implementar e otimizar um algoritmo/módulo de IA para rastreamento de objetos (aeronaves) em streams de vídeo em tempo real provenientes de câmeras. Requisitos Técnicos Essenciais: Linguagens de Programação: Python (preferencial), C++. Frameworks de IA/Deep Learning: Experiência comprovada com pelo menos um dos seguintes: TensorFlow, PyTorch, Keras. Bibliotecas de Visão Computacional: Forte domínio de OpenCV para processamento de vídeo e imagens. Algoritmos de Tracking: Experiência com algoritmos de rastreamento de objetos (ex: CSRT, KCF, SORT, DeepSORT, YOLO com tracking, etc.). Detecção de Objetos: ...

...dados • Gestão de notificações push • Cadastro de profissionais (optometristas, técnicos) • Integração com sistemas internos (ERP óptico, laboratório etc.) ⸻ 4. RECURSOS TECNOLÓGICOS RECOMENDADOS • Frontend Mobile: Flutter ou React Native • Backend: Node.js ou Python (Django) com API REST • Banco de Dados: PostgreSQL ou MongoDB • Reconhecimento facial / IA óptica: OpenCV + TensorFlow/MediaPipe (para medição) • Hospedagem: AWS ou Firebase (recomendado para escalabilidade) ⸻ 5. ITENS DIFERENCIAIS • Tecnologia própria de medição óptica por selfie • Monitoramento visual automatizado por IA &...

...they upload their information and pitch decks. Scalability: Ensure the platform is scalable to handle thousands of users and large amounts of data, especially as the platform grows. Multilingual Support: Consider adding support for multiple languages to cater to a global audience. Technical Requirements: Backend: AI/ML models to drive the matchmaking and pitch grading system (e.g., TensorFlow, PyTorch, or similar). Frontend: Modern and responsive frontend (React.js or similar) for a clean and efficient user experience. Database: Cloud-based, scalable database (e.g., PostgreSQL, MongoDB) to store user data securely. Authentication: Secure login system (OAuth, JWT, or similar) to protect user accounts and data. Cloud Hosting: Use cloud services like AWS, Googl...

...Top Scorers, etc.) 2. Technologies and APIs SportMonks API: The SportMonks API will be the primary data source. The freelancer will need to integrate this API into the website to ensure that all data, such as live scores, odds, and team/player statistics, is always up-to-date. AI Training (Machine Learning): Python will be the preferred language for training the AI, utilizing libraries like TensorFlow or scikit-learn. Historical data provided by the SportMonks API will be used to train the AI based on previous match results, odds, team form, and other relevant statistical factors. The AI should be trained to predict game outcomes, aiming for a minimum accuracy rate of 85%. The system should be capable of learning from new matches and adjusting predictions based on the most...

...CertiK, Hacken e Solidity Finance. ✅ Rastreamento de carteiras suspeitas e detecção de movimentações suspeitas. ✅ Dashboard para visualização das operações em tempo real. ✅ Automação de estratégias de venda (Trailing Stop Loss, Take Profit). ? Requisitos Técnicos: ✅ Linguagem principal: Python (ou Node.js se preferível). ✅ Banco de dados: PostgreSQL ou MongoDB. ✅ Machine Learning e IA: TensorFlow ou PyTorch. ✅ Dashboard: React.js, Vue.js ou outro framework web. ✅ Deploy em servidor VPS para operação 24/7. ? Requisitos do Desenvolvedor: ✔ Experiência comprovada em automação de trading e integração com APIs de exchanges. ✔ Conhec...

...(Ubuntu Server recomendado) ✔️ Configurar acesso SSH seguro e permissões adequadas 2️⃣ Implementação de Segurança e Performance ✔️ Configurar firewall e regras de proteção (UFW, IPTables) ✔️ Implementar fail2ban para prevenção de ataques ✔️ Otimizar a performance com Docker ou Kubernetes 3️⃣ Configuração do Ambiente de Processamento ✔️ Instalar Python, bibliotecas de machine learning (PyTorch, TensorFlow) ✔️ Configurar GPU drivers (se necessário) ✔️ Integrar API de comunicação para interação com a plataforma 4️⃣ Deploy e Testes ✔️ Criar container Docker para isolamento e escalabilidade ✔️ Implementar banco de dados (PostgreSQL, MongoDB ou Redis) ✔️ Testar latência, re...

...dataset. Treinamento de Modelo de Linguagem: Ajustar um modelo pré-treinado (como GPT ou similar) ao estilo do jornalista. Testes e Validação: Avaliar e refinar a qualidade dos textos gerados. Entrega e Documentação: Implementar o modelo em uma interface simples (API ou ferramenta online) para uso futuro. Tecnologias Preferenciais (não obrigatório): Frameworks: Hugging Face Transformers, PyTorch ou TensorFlow. Modelos: GPT, BERT, ou outros adequados para geração de texto. Estou aberto a sugestões sobre metodologias, ferramentas e melhores práticas para alcançar o resultado desejado. Se você tem experiência em PLN, treinamento de modelos de linguagem ou projetos similares, ficarei feliz...

...obtidos durante o treinamento, preparando-o para uso em ambiente móvel. Integração Móvel: Prepare o modelo para ser integrado em um aplicativo de smartphone, permitindo detecção e inferência em tempo real utilizando a câmera do dispositivo. Requisitos: Experiência comprovada em desenvolvimento de modelos de machine learning, especialmente em visão computacional. Proficiência em frameworks como TensorFlow, PyTorch ou similares. Conhecimento em otimização de modelos para dispositivos móveis (Android e/ou iOS). Capacidade de documentar o processo e fornecer orientações para a integração no aplicativo móvel. (Opcional) Experiência em desenvolvimento ...

...criando matrizes de avaliações e tratando valores ausentes. ● Modelagem: Implemente um algoritmo de recomendação colaborativo ou um algoritmo híbrido, combinando informações colaborativas e baseadas em conteúdo. ● Vídeo explicativo: Grave um vídeo apresentando seu projeto, explicando as etapas realizadas, os desafios encontrados e os resultados obtidos. ● Dica: Sugiro que utilizem bibliotecas como TensorFlow ou PyTorch para implementar os algoritmos de recomendação. Fontes de Pesquisa Primária: 1. MovieLens Dataset: Um dos conjuntos de dados mais utilizados para sistemas de recomendação, disponível no Kaggle, que oferece uma vasta coleção de avaliaç...

Escopo do Projeto: Substituição da Câmera Nativa: Desenvolver uma aplicação que se registre como uma câmera disponível no sistema Android Integrar a câmera virtual para que seja selecionável em qualquer aplicativo que utilize a câmera nativa. Interação com Aplicações: Garantir que a câmera ...técnicas de ataque adversarial. Modificação da imagem para enganar algoritmos de reconhecimento facial, se necessário. Captura de dados do acelerômetro e giroscópio. Simulação de movimento da câmera com base nos dados dos sensores. 3. Tecnologias e Ferramentas: Linguagem de Programação: Java/Kotlin. IDE: Android Studio. Bib...

...de Progresso: Permitir que os usuários acompanhem seu progresso emocional ao longo do tempo. Aplicar técnicas de aprendizado de máquina para ajustar as recomendações de tratamento. Tecnologias a Serem Utilizadas: Frontend: HTML, CSS, JavaScript para criar uma interface de usuário responsiva. Backend: Node.js ou Python para lidar com lógica de negócios e integração de IA. IA: Frameworks como TensorFlow ou PyTorch para modelos de aprendizado de máquina. Banco de Dados: MongoDB ou SQL para armazenar dados de usuários e interações. Considerações Éticas: Garantir a confidencialidade e a segurança dos dados dos usuários. Estabelecer limites claros para ...

Me ajudem por favor com uma ultima parte do meu modelo para que possa entregar na graduação. Preparei minha sequencia de processamento, coloquei os parametros de correção. mas quando tento dar "fit" ocorre um erro que não consigo avançar.

Deve ser realizado em TensorFlow O problema Consiste em: 6 forças (antagónicas em pares), 1 caminho (2 valores):

Construção de plataforma self service para criação de ChatBot semelhante a chatfuel ou manychat. O usuário poderá entrar na plataforma e desenhar o seu proprio fluxo de conversa do seu chatbot e também conectar o chatbot nas plataformas como Facebook, instagram, sites e outras redes sociais. É necessário construir o frontend, backend e conectar a a mesma em plataformas de intelige...service para criação de ChatBot semelhante a chatfuel ou manychat. O usuário poderá entrar na plataforma e desenhar o seu proprio fluxo de conversa do seu chatbot e também conectar o chatbot nas plataformas como Facebook, instagram, sites e outras redes sociais. É necessário construir o frontend, ...

...build from scratch: data prep, training, packaging, deployment, and a quick monitoring stub, with code hosted in a clean Git repo I can reference later. • Short homework tasks between calls so I cement what we covered and come prepared with questions. If you have experience turning Jupyter prototypes into scalable production services on GCP using Python frameworks such as FastAPI, Flask, or TensorFlow Serving, I’d love to hear how you can guide me. Clear explanations, screen-sharing while you code, and the ability to leave me with reusable scripts or templates are essential....

...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 a similarly robust model) and output the findings in both human-readable (an image with bounding boxes or a simple web map) and machine-readable form (CSV/GeoJSON with lat/long, time stamp, confidence score). Once I apply the tool to a new location and receive a list of car and truck pictures and coordinates automatically reflected on the map, n...

...dashboards (heatmaps, multi-lottery support). 3. Detailed Implementation 3.1. Data Structure: DB schemas for lotteries (rules/ranges/draw days), full history (indexed), user settings (no credentials). 3.2. Draw Day Changes: internal API with official validation & calendar sync. 3.3. Cost Calculation: dynamic Python functions + jackpot scraping & EV. 3.4. Prediction: train RNN/LSTM (PyTorch/TensorFlow), combinatorial generation (itertools), Genetic optimization. 3.5. Backtesting: parallel scripts (multiprocessing), no bet limits, model cross-validation. 3.6. Automation: as in 2.5, with execution logs and real-time UI feedback. 4. Conclusion System developed for exclusive personal use, integrating data collection, multi-model AI optimization, supervised secure au...

...those classes, it must immediately push an alert to my back-end (REST webhook is fine) and simultaneously initiate recording on the camera stream. Speed is critical: I’m targeting sub-100 ms inference per frame on an Nvidia Jetson Xavier, yet I still need accuracy good enough to avoid nuisance alerts in busy scenes. You’re free to choose the framework you prefer—YOLOv8, Faster R-CNN, or a custom TensorFlow / PyTorch implementation—as long as the final package runs headless in Linux and can be containerised (Docker) for deployment. Please include: • A fully trained model with reproducible training pipeline • Real-time inference script that ingests RTSP feeds and exposes JSON alerts • Simple unit test clips proving correct detection and...

...subscription plans Signal history & performance tracking Alerts via Telegram, email, webhook, or mobile push Admin System Signal monitoring dashboard Strategy performance analytics User & subscription management Technical Stack (Flexible) We are open to: Frontend: React / / Vue Backend: Node.js, Python, or C# (.NET) Data: WebSocket market feeds + historical OHLCV storage AI/ML: TensorFlow, PyTorch, or equivalent Infra: Scalable cloud architecture, API-first design Budget High budget — We prioritize quality, performance, and long-term scalability over cost. TRADE LOGIC sample • [TREND] Channel trend: Downtrend • [MSB] 3 out of the last 5 MSBs are Bearish pattern breakouts • [MSB] Price near the last MSB level (0.17%) - Resistance &bu...

...An example water module plus at least one non-water module (finance, social media, or marketing—your pick) • Concise user documentation and a short video or GIF that walks through the hand-off / execution / result flow The simpler the tech stack the better, but I’m fine with Python, Node.js, or a small Rust service if you feel performance demands it. Lean on well-supported libraries such as TensorFlow, PyTorch, scikit-learn, or OpenAI’s function-calling API—whichever speeds you toward a clean, repeatable release. I’ll sign off once I can: 1. follow your README to spin up the app on my own machine, 2. assign a sample water job plus an unrelated business task, and 3. see both completed autonomously with logs confirming each step. If tha...

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 y...

...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 model weights ready for deployment • A short report ...

...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 setup, training commands, and how to run inference on a single file or a batch. • A trained model file and a simple inference function/CLI th...

...open-source tools (MediaPipe / TensorFlow Lite / OpenCV / YOLO, etc.) • Demonstrate: 1. Live head tracking 2. Auto zoom in real time 3. Stable performance (≥15 FPS) Deliverables • Full source code • Build instructions • Short demo video showing real-time performance • Explanation of how this will later integrate with a custom camera SDK Once validated, this prototype will be integrated into our production system. Target Platform (Future Integration) Our production system will be: • Android-based smart mirror • Wi-Fi camera input (custom SDK) • C/C++ (NDK) + Java/Kotlin • Video resolution: up to 4K • P2P local streaming (no cloud) So experience with embedded/mobile video pipelines is important. Preferred Skills • C...

...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 readings and short-term weather data, while also generating three forward-looking insights: predicted soil moisture over the next 6–24 h, likely weather changes in that window, and the water volume the system will probably consume. • Cont...

...back-office system. • Flag high-risk clients to underwriters with an explanation score so they can override or request extra documentation. • Present all of this via a REST/JSON API that my current React front end can call, and expose a lightweight Python-based admin dashboard where underwriting managers can adjust thresholds and retrain models on fresh data. I work mainly with a Python solution (TensorFlow, PyTorch, or scikit-learn—whichever you feel is best) will plug in cleanly. The customer-facing chatbot or form assistant can be built with a service such as Rasa or a fine-tuned OpenAI model as long as it routes seamlessly into the same risk engine. Acceptance criteria 1. A reproducible training pipeline with clear data-schema docs. 2. Dockerised API...

...continually scouting, testing, and refining state-of-the-art models in three core areas: text generation, sentiment analysis, and machine translation. Scope of work — Track current research and emerging repositories (Hugging Face, arXiv, GitHub) to spot promising architectures and training techniques. - klaud8 / hrm ai / chat gpt / claude — Spin up controlled experiments in Python using PyTorch/TensorFlow, comparing baseline performance with fine-tuned variants on representative datasets. — Optimise inference speed, memory footprint, and prompt-engineering workflows so models transition smoothly from notebook to production API. — Document findings in concise experiment reports and integrate successful models into our existing CI/CD pipeline. De...

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 outp...only the prediction score. 3. Implement email automation (SMTP or a trusted API such as SendGrid) that fires immediately after each prediction. Deliverables: • Trained model file and reproducible training script • Source code for the web app with clear setup instructions • Brief README explaining how to retrain and change email credentials If you have prior work with scikit-learn, TensorFlow, Flask, Django, or similar tools, please mention it. I look forward to seeing a working demo deployed on a free tier (Heroku, Render, or comparabl...

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 ...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 yo...

...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” shoes, along with a lightweight admin panel where I can adjust thresholds and view basic ...

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 ...

...junior AI engineers and contribute to technical leadership • Conduct research and implement state-of-the-art AI techniques • Ensure data quality, security, and model performance optimization Required Skills & Qualifications: • 10+ years of experience in AI/ML or Software Engineering roles • Strong proficiency in Python and data processing libraries (NumPy, Pandas) • Hands-on experience with TensorFlow, PyTorch, Scikit-learn • Strong understanding of Deep Learning, NLP, Computer Vision • Experience with Model Deployment & MLOps pipelines • Experience working with Cloud platforms (AWS / Azure / GCP) • Strong knowledge of Data Engineering & Big Data tools • Experience with REST APIs and Microservices • Excellent ana...

...code in Python myself, so please keep the architecture transparent: well-named modules, docstrings, and a that pins every dependency. Back-tests on at least two years of 5-minute data, a walk-forward validation segment, and a short README outlining how to reproduce the results will be my acceptance criteria. If you already have experience with pandas, NumPy, scikit-learn or TensorFlow, and you know how to talk to Indian broker APIs via REST or websockets, this should feel familiar. Let me know the models or reinforcement-learning frameworks you think best suit intraday equity trading and how you will protect against over-fitting....

...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/MONAI on open dental datasets) for multi-label detection/segmentation. • Mandatory: Full anonymization on upload (pydicom/deid), end-to-end encryption, audit logs, compliance-ready (HIPAA/GDPR/APP principles), ethical transparency (e.g., explainability features). • Cloud deployment (AWS/GCP/Azure, serverless ideal). NDA required. ...

...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, interactive notebooks, and short build-and-test cycles. Required expertise • Solid command of Python, scikit-learn, TensorFlow or PyTorch, plus NLP libraries such as spaCy or NLTK. • An educator’s mindset: you can explain core concepts clearly, scaffold complexity, and troubleshoot student code in real time. • Proven history of running workshops—either academic or corporate—within tight timelines. Deliverables 1. Detailed session plan (3 tracks, 8...

I need an expert to improve the accuracy of a histopathologic cancer detection model. The current model needs enhancement, and I prefer using algorithm enhancement for this task. Key Requirements: - Improve the m...enhancement for this task. Key Requirements: - Improve the model's accuracy in detecting cancerous tissues. - Use advanced techniques and methodologies for algorithm enhancement. Ideal Skills and Experience: - Expertise in machine learning and deep learning - Strong background in medical image analysis - Experience with histopathological images - Proficiency in Python and relevant libraries (TensorFlow, Keras, PyTorch) - Familiarity with model evaluation and performance metrics Please provide examples of similar work and a detailed approach to how you would tackl...

...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. Deliverables • Refactored Python package replicating the current predictions on a supplied test set • README covering setup, dependencies, and usage • Quick comparison report showing identical mAP or better against t...

...beyond the basic horizontal/vertical stripes to oblique, curved, or irregular banding the current code ignores. • Optimize performance: refactor the pipeline for faster image loading, GPU-aware inference, and leaner memory use so it remains responsive on large datasets. Everything runs in Python, so please stay within that ecosystem. You are free to introduce OpenCV, scikit-image, PyTorch, TensorFlow, or other libraries, provided the final solution installs cleanly with a and runs from a single entry-point script or Jupyter notebook. Input will be folders of images; no video or live feed integration is required at this stage, but laying groundwork for future expansion is a plus. I will supply a labeled image set for benchmarking and expect a short report showing accurac...

...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 clear data loaders for each modality • Custom model implementation with commented rationale for design decisions • Reproducible training scripts, hyper-parameter configs, and a validation notebook that plots forecast accuracy against standard baselines • Final technical report summarizing methodology, results, and potential publication avenues ...

...push actionable alerts through a cloud-hosted pipeline. Later phases will weave in IoT sensors, GPS data and public-transport schedules, but for now cameras take centre stage and all processing happens in the cloud. Here’s what I need from you: • A complete stream-to-insight workflow: camera feed ingestion → cloud message bus → analytics micro-service. • Computer-vision models (OpenCV, YOLO, TensorFlow—your call) that flag incidents with >90 % precision/recall on my test clips. • A REST API that surfaces live traffic state and returns diversion routes in real time. • Extension hooks so I can sync bus, train and metro timetables and forward delay alerts to commuters. • Containerised or serverless deployment scripts so I c...

...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 clear data loaders for each modality • Custom model implementation with commented rationale for design decisions • Reproducible training scripts, hyper-parameter configs, and a validation notebook that plots forecast accuracy against standard baselines • Final technical report summarizing methodology, results, and potential publication avenues ...

...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 CPU fallb...

... Secondary expectations include light cooking, everyday chores, and fluid, human-like movement so the machine blends safely into family life. I am looking for an end-to-end solution covering: • Hardware: anthropomorphic frame, compliant actuators, force-torque sensors, depth & RGB cameras, and medical-grade vitals sensors. • Software: ROS-based control stack, SLAM for navigation, TensorFlow/PyTorch models for vision and speech, and a secure mobile dashboard. * Ability to learn and adapt. * Chatgpt integration. * Human-like skin and features. * Ability to ship to usa. Ability for owner to pack in a box and ship to Philippines easily. • Safety & compliance: redundant fail-safes, IEC/ASTM child-safety standards, and a hygiene-certifiable ...

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 pre...

...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 rapid prototypes that prove the choice. • Drop-in reference implementations or micro-services that slot straight into our existing Node/Express back end. • Plain-language docs and two-minute screen-share videos so community groups, national NGOs, and global...

...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 CPU fallb...

...levels—Admin, Standard user and Guest—each with appropriate permissions for running detections, reviewing results and managing data. Please structure the code so that REST endpoints are cleanly separated; this will let me expose the following Android-ready APIs later on: live-video analysis, image-file analysis and retrieval of disease-history logs. Deliverables • Python inference engine (TensorFlow/PyTorch + OpenCV acceptable) optimised for Raspberry Pi 5 • Django project with the described role system, templates and REST endpoints • Model-training notebook or script plus labeled dataset reference • Setup script or Dockerfile for one-step deployment on a fresh Pi • Brief README covering install, usage and endpoint documentation Ac...