Tensorflow jobs

...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...

...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 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 can point the script to a new polygon and receive a list of car and truck coordinates every 24 hours—fully automated, no ...

...STACK ──────────────────────────────────────── ### Backend • Node.js (NestJS) OR Laravel • REST + WebSockets • PostgreSQL • Redis ### Fleet Core • Fleetbase (extended via plugins) ### Frontend (Web Dashboards) • React.js or • Tailwind CSS • Mapbox or OpenStreetMap ### Mobile Apps • Flutter (preferred) OR React Native ### AI & Analytics • Python • FastAPI • Pandas • Scikit-learn / TensorFlow (later phase) ### Payments • Stripe SDK • PayPal SDK • CMI API ### DevOps • Docker • CI/CD • Cloud hosting (AWS / GCP / Azure) ### Design • Figma (mandatory) • Design System • UX focused on minimal interaction ──────────────────────────────────────── 13. PROJECT EXPECTATI...

...triggering audible deterrents on-site. Here’s the shape of the work: • System architecture: advise on the right combination of sensors (camera, PIR, ultrasonic, mic), onboard processing (Raspberry Pi, Jetson, or similar), and wireless protocols so the robot can run edge-based computer-vision without relying on the cloud. • Detection pipeline: develop or integrate a lightweight model—OpenCV or TensorFlow-Lite is fine—that reliably flags human intrusion in low-light and daylight conditions, minimising false positives from pets. • Alert mechanism: build the software bridge to push break-in alerts through a companion mobile app/API along with timestamped snapshots or short clips. A local siren should activate simultaneously. • Navigation ...

...and renters. At its core the app must let a property manager add, edit, and remove listings (images, price, availability, basic details). The AI component should work behind the scenes—think auto-tagging amenities from photos, suggesting competitive pricing ranges, or surfacing the most relevant homes to a tenant based on their previous in-app behaviour. I’m open to the exact technique you use (TensorFlow Lite, ML Kit, embedded models, or a lightweight cloud call), so long as it stays responsive on typical mid-range Android devices. No third-party property-management or CRM integrations are required; the app should run as a self-contained product with its own lightweight backend or local data layer. A clean Material-style UI, Kotlin codebase, and modern Android archi...

Please Sign Up or Login to see details.

...adjusts intensity and volume to suit beginner through intermediate levels, and outputs a structured weekly routine (exercises, sets, reps, rest, and optional equipment notes). The system should justify its choices in plain language so the end user understands the reasoning behind each exercise block. I’d like the core to be written in Python, preferably leveraging familiar ML libraries such as TensorFlow, PyTorch, or scikit-learn—happy to hear your recommendation. Data sources for exercise selection can come from public, reputable fitness datasets or a curated ruleset you supply. The end result should be easy for me to integrate into a simple web or mobile front end. Deliverables • Clean, well-commented source code for the workout-plan generation engine &...

...with mobile app Mobile App Requirements Android & iOS compatibility (Flutter / React Native preferred) Login & user profiles Real-time notifications AI-based smart features Secure backend connectivity Preferred Tech Stack (Developers can suggest better alternatives) Frontend: React / / Vue Backend: Node.js / Django / Laravel Mobile App: Flutter / React Native AI/ML: Python, TensorFlow, OpenAI API, or similar Database: MongoDB / MySQL / PostgreSQL Cloud: AWS / Firebase / Azure Security Data encryption Secure authentication Role-based access (Admin/User) Deliverables Fully working website Mobile app (APK + iOS build) Admin dashboard Source code Deployment support Documentation Freelancer Requirements Proven experience in AI projects Portfolio of...

...for lack of blinking, lip-sync errors, or artifacts). * Uniform/Badge Recognition: Detect if the person is wearing a police uniform or showing a badge (using object detection like YOLO). * Real-Time Risk Dashboard: * A simple UI that displays a "Trust Score." If the score drops below a threshold, it shows a "SCAM ALERT" warning. Preferred Tech Stack: * Language: Python * ML Frameworks: TensorFlow / PyTorch / Keras * Computer Vision: OpenCV, MediaPipe * NLP: Hugging Face Transformers (BERT/RoBERTa for intent classification) * Interface: Streamlit or Flask (for the demo dashboard) Deliverables: * Source Code (well-commented). * A file for easy installation. * A short demo video showing the system detecting a scam attempt from a sample video file....

...just for them. My priority is customer engagement, so the core of the job is a recommendation engine that serves personalised promotional offers in real time, based on search intent, page behaviour and purchase history. Your job: • Examine my current site structure, content and analytics to see what data we can safely feed the model. • Build or configure an AI recommendation layer (Python, TensorFlow, GPT-based, or a proven SaaS solution—whichever you can justify) that plugs into the site and pushes the most relevant promo offer to each user. • Optimise on-page SEO signals so the personalised content also strengthens overall ranking without keyword stuffing. • Set up event tracking so we can measure uplift in click-through and conversion. •...

...printable files. You’ll choose or design the model, train or fine-tune it, then wrap everything in a lightweight API that my mobile team can call in real time (on-device when feasible, cloud fallback when not). You should be completely comfortable with OpenCV plus deep-learning frameworks such as PyTorch or TensorFlow, and you know the trade-offs between traditional filters, GAN-based approaches, and modern super-resolution networks. Experience packaging models for CoreML, TensorFlow Lite or similar mobile runtimes will set you apart. I’m most interested in seeing what you’ve already shipped, so please include past work that proves you can take an image-processing idea from notebook to app store. Deliverables • Clean, well-commented Python codeb...

...for both iOS and Android. While the mobile build is underway, I also want to formalise the visual language of the product—colours, type, iconography, tone—into a concise brand style guide that my team can reuse across every touchpoint. Certain features in the roadmap rely on AI (for example, smart content recommendations and intent-based search). If you have preferred libraries or services—TensorFlow Lite, OpenAI, LangChain, or on-device ML kits—bring them into the discussion; speed of delivery is key. I’m comfortable with AI-assisted tooling (GitHub Copilot, automated testing, etc.) if it keeps the timeline tight. Once the mobile MVP is solid, I want a pared-down web companion built from the same React codebase wherever possible. A responsive ...

...free to abstract this behind a clean API layer so either provider can be swapped in later. • Send confirmation and reminder messages automatically, with hooks for SMS and email. Tech preferences I am most comfortable reviewing code written in Python, and I already run Docker in production, so please containerise the service. You are welcome to use libraries such as spaCy, Rasa, Dialogflow, TensorFlow or PyTorch—choose what fits the problem, document your reasoning, and make installation reproducible with a single script. What I will accept as “done” 1. A Docker-ised project that I can spin up locally, connect to my calendar, and watch it schedule a demo meeting end-to-end. 2. Clean, commented source code plus a concise README detailing setup, envi...

...Messaging is used for internal notifications and alerts. The system follows a serverless architecture where security rules are managed through Firestore rules. The architecture supports multi-tenant functionality with hospital-level data isolation. Artificial Intelligence Generative AI using the Gemini API is integrated for medical summaries and clinical analysis. On-device AI is implemented using TensorFlow Lite for offline disease classification and suggestion logic. Local JSON-based datasets are used for storing information about medications, precautions, and self-care guidelines. Core Features and Functionality Global and Common Features The system supports multi-role authentication including System Admin, Hospital Admin, Doctor, Receptionist, and Patient. Real-time notifi...

...train a powerful intrusion-detection model without ever sharing raw traffic logs. Each embassy keeps its packets local, trains an IDS in Python, then ships only the updated weights to a permissioned blockchain that averages them and sends back the enhanced parameters. Key points I need turned into code: • Dual-framework training loops: the local agent must be able to switch between PyTorch and TensorFlow so each site runs whichever stack its engineers prefer. • Attack coverage baked into the dataset pipeline: the IDS must correctly classify Malware, Phishing, and DDoS patterns. Synthetic generation for edge cases is fine as long as the final validation shows clear detection rates for all three. • Smart-contract aggregator: the chain’s sole responsibility ...

...throwing errors whenever it calls certain library functions. I need a sharp eye to dive into the code, pinpoint the exact cause, and leave me with a clean, reproducible fix. Here’s the situation as clearly as I can put it: • The faulty piece lives in a Python script that glues together key stages of the workflow. • The issue surfaces inside library-level calls—think NumPy, pandas, scikit-learn, TensorFlow, or similar. • Once corrected, the rest of the training and inference steps should run without manual work-arounds. What I’m expecting from you • A patched script that runs end-to-end on my side. • A concise changelog or inline comments explaining what broke and why your fix works. • Any environment tweaks (package versio...

I'm looking for an experienced Python teacher specializing in advanced programming and machine learning. Essential requirements: - Expertise in Python, especially in machine learning - Ability to explain complex concepts clearly - Experience with popular ML frameworks (e.g., TensorFlow, PyTorch) - Flexible scheduling to accommodate my learning pace If you have a strong background in these areas, please apply!

I need a wearable device to detect sleep-time bruxism. Requirements: - Monitors muscle activity. - Alerts with sound when clenching. - Collects clenching duration and frequency data. - Must reside in india ( bangalore) Ideal Skills: - Arduino/ESP32 development - Python/TensorFlow Lite (microcontrollers) - Embedded systems & electronics (mic setup, signal processing) Hardware can be procured by me or reimbursed. Urgent requirement

I’m ready to take my current WordPress-based platform and weave AI into its core so the site works harder—and smarter—without constant manual input. The overarching goal is “website AI integrated,” meaning the chosen solution should sit natively inside WordPress, draw on best-fit frameworks such as OpenAI, TensorFlow, or similar, and deliver tangible daily efficiencies. The three areas I want the AI to handle are: • Customer support chatbots – a conversational layer that resolves common questions, hands tougher issues to humans, and logs every exchange back into WordPress or our CRM. • Content personalization – dynamic page, product, or article recommendations driven by real-time visitor behavior. • Data analysis and rep...

I am rolling out a trio of inter-linked prototypes that tackle pressing urban and environmental challenges while showcasing cutting-edge AI, blockchain, and IoT engineering. First, the AI-driven Smart Traffic System must ingest multi-sensor feeds, apply real-time reinforcem...report comparing baseline vs. prototype performance Acceptance criteria – Source compiles and runs without modification on the stated platform – ML models reproduce stated metrics using provided data – Voting demo passes independent audit script – Traffic simulation shows ≥ 15 % average wait-time reduction If you need data samples, CAD files, or clarifications on preferred libraries (TensorFlow, PyTorch, ROS2, Hardhat, ), let me know early so I can share the assets and keep...

...tricks • Record results, visualise them clearly, and explain the “why” behind the numbers • Iterate on your findings until we have a result worth integrating into production-grade code What you should bring Your application only needs to highlight relevant experience, but that experience must show strong analytical and problem-solving skills. If you are already comfortable in Python, R, TensorFlow, PyTorch or similar stacks, say so—those tools are the basis of most of our work, though deep mastery is less important than the ability to dissect a problem and reason through solutions. Deliverables 1. Reproducible notebooks or scripts for each experiment 2. A concise report explaining methodology, results, and next steps 3. A short hand-off ...

A small TensorFlow script in my project has started throwing errors, and I need it back in working order within 48 hours. The bug sits somewhere between the data-loading step and model training; once you jump in you’ll have full access to the Python code, sample data, and the original (working) training logs so you can compare behaviours. I work entirely in Python and TensorFlow, with a handful of standard utilities such as NumPy, pandas, and Matplotlib. No other frameworks are involved, so deep familiarity with TensorFlow’s debugging tools, graph/symbolic APIs, and eager execution will let you move quickly. Here is what I expect at hand-off: • A corrected script that runs start-to-finish on my machine (TensorFlow 2.x, Python 3.9). • A concise...

I'm seeking an AI/ML expert to develop a smart health ID system with predictive analysis capabilities for brain cancer risk assessment. Key Requirements: - Predictive Analysis: Focus on risk assessment. - Data Source: Analyze medical imaging scans. Ideal Sk...predictive analysis capabilities for brain cancer risk assessment. Key Requirements: - Predictive Analysis: Focus on risk assessment. - Data Source: Analyze medical imaging scans. Ideal Skills & Experience: - Expertise in AI/ML, particularly in predictive analytics. - Experience with medical imaging data. - Background in healthcare technology is a plus. - Strong programming skills (Python, TensorFlow, etc.). - Ability to deliver secure and compliant health data solutions. Please provide relevant work samples and a...

...source files and outputs clean, artifact-free H.264/H.265 versions at multiple resolutions. It should be efficient enough for batch processing on a single workstation but scale to a GPU server when required. • Recommend (and set up) an AI model suited to my animation goals, then wire it into the pipeline so I can move seamlessly from encoded footage to AI-augmented renders. Whether you lean on TensorFlow, PyTorch, or OpenCV is up to you—just justify the choice and document how to reproduce it on my side. • Provide concise documentation: command-line flags, filter graphs, model checkpoints, and any tuning parameters. I need to understand why each setting was chosen and how to tweak it for future projects. Acceptance criteria 1. A working FFmpeg script or s...

...what I need from you: Architecture & Data – Connect to major GDS and OTA APIs (Amadeus, Skyscanner, , etc.) and stream prices continuously. – Design a pipeline that normalises the data and feeds an ML model for deal scoring. – Implement efficient caching so agents always see fresh yet lightning-fast results. Deal Intelligence – Train or fine-tune a model (Python, scikit-learn/TensorFlow acceptable) that flags outlier bargains in real time and ranks them by savings, convenience and agent-defined preferences. – Expose this logic through a clean REST/GraphQL endpoint the front-end can hit on demand. Itinerary Engine – Given destination, dates and traveller profile, generate a structured day-by-day plan filled with top-rated attraction...

I need a developer who can take this idea from concept to a working, browser-based product. The core objective is to enrol users with a unique “vo...prompts prior to recording. Acceptance criteria • Enrolment and verification must run end-to-end in under five seconds on a typical broadband connection. • Equal Error Rate (EER) ≤ 5 % on a public speaker dataset or a comparable internal test set. • Clear documentation (setup, model training pipeline, API endpoints) plus a Dockerised deployment script. Tech stack is open, but Python (TensorFlow/PyTorch), Node.js, or Rust are all fine as long as you can justify the choice and meet the performance targets. Please outline your proposed approach, libraries you favour (Kaldi, SpeechBrain, etc.), and any simi...

...developer to help build AI-powered mobile applications. The work involves integrating machine learning models for real-time detection and analysis, both running locally on-device (offline) and via cloud APIs. Note: Your task will be integration of AI models in app architecture but its nice to have knowledge about AI models. What You'll Be Working On Integrating custom detection models (YOLO, TensorFlow Lite, ONNX) into Android apps Implementing on-device inference for offline functionality Connecting apps to AI APIs for cloud-based processing Optimizing model performance for android mobils(Snapdragon 6 cpus etc.) Building clean UI to display detection results in real-time Required Skills Strong Android development experience (Kotlin/Java/Flutter) Hands-on experience ...

...The core objective is simple: turn time-consuming manual work into an intelligent process that runs on its own. Because I don’t yet have data or legacy tools in place, we’ll define the workflow together, identify what information needs to be gathered, and then create the logic, models, or rule-based components that best fit. You’ll have full freedom to choose the right libraries—whether that’s TensorFlow, PyTorch, scikit-learn, spaCy, or a leaner approach using pure Python—so long as the end result is reliable, maintainable, and easy for me to extend later. Deliverables 1. Brief discovery call and written workflow outline 2. Prototype demonstrating successful end-to-end automation on sample data you create 3. Clean, well-commented Pytho...

I need a piece of software that plugs straight into the video stream coming from existing, off-the-shelf CCTV cameras and immediately adds deep-learning smarts. The core ...Deliverables • Installable software (source + compiled package) that connects to standard RTSP/ONVIF camera feeds • Model training or transfer-learning pipeline that achieves high accuracy on my sample footage • Real-time alert module covering email, SMS, in-app and monitor popups • Setup guide and brief user manual I’m comfortable if you leverage frameworks such as Python, OpenCV, TensorFlow or YOLO, as long as performance remains near real-time on 1080p streams. Let me know your approach, estimated turnaround time and any prerequisites you’ll need from my side (e.g., l...