Tensorflow predict jobs
...ERP with React, Node, and MySQL that works, but the three main parts—Management of Projects, Billing for Clients, and Material Management—still feel like they are on their own. I need a full-stack developer to put them all together, finish the last few screens, and most importantly add the new tracking and intelligence features below. What needs to change? • AI-powered insights must be able to predict project finish dates and times, as well as flag cost overruns or budget deviations through easy-to-understand screens and reports that can be exported. • Tracking material theft and waste should be real-time. I don't want data to be updated once a day, once a week, or once a month; data needs to be updated all the time so a site manager can move as soon...
...has a working ERP built with React, Node and MySQL, but the three core areas—Projects Management, Client Billing and Material Management—still feel like separate islands. I need a full-stack developer who can weave them together, finish the remaining screens and, most importantly, layer in the new intelligence and tracking features listed below. What has to change • AI-powered insights must predict project timelines and completion probability while flagging cost overruns or budget deviations, all surfaced through clear dashboards and exportable reports. • Material theft and wastage tracking should be live; I don’t want daily, weekly or monthly batches—data needs to update continuously so a site manager can act the moment a discrepancy appear...
...compatible with Windows operating system. Key Requirements: - Over 6 years of experience in software development - Proven expertise in data science, Python and SQL - Experience in API integration - Based in Mumbai - Experienced in building data-driven solutions and implementing algorithms - Skilled in Windows desktop application development - Familiarity with machine learning frameworks such as TensorFlow or scikit-learn - Experience with project management and version control tools like Git - Ability to create data visualizations and dashboards - Experience in writing unit tests to ensure code quality - Skilled in optimizing applications for better performance - Proficient in designing user-friendly UI/UX for desktop applications - Knowledge in developing cross-platform applica...
I’m building a responsive web app that runs smoothly on any iPhone browser and on Windows de...demonstrating sub-5-second odds refresh and sub-60-second player/weather updates 3. Documented data sources, model methodology, and environment setup instructions 4. Admin panel for adding new bookmakers or tweaking model parameters 5. Automated tests covering data ingestion, model outputs, and UI critical paths I’m flexible on the final tech stack—React or Vue on the front end, Python (TensorFlow, PyTorch, or XGBoost) or a Node alternative for the AI layer are all fine as long as they deliver speed and transparency. Let me know how you’d structure the data feeds, what modelling approach you would use, and any previous work that proves you can bring real-ti...
...& Production Engineering Experience with: * Docker * Kubernetes * CI/CD pipelines * MLflow * Model versioning * Model deployment * Model monitoring * Experiment tracking * Feature stores * GPU inference optimization * REST APIs (FastAPI preferred) Cloud experience with at least one platform: * AWS * Google Cloud Platform * Microsoft Azure --- ## Nice to Have * Deep Learning (PyTorch or TensorFlow) * Fine-tuning LLMs (LoRA/QLoRA/PEFT) * Distributed training * Knowledge Graphs / GraphRAG * Computer Vision or NLP experience * Reinforcement Learning * Streaming data pipelines (Kafka, Pub/Sub) * Airflow or similar orchestration tools * Experience building AI agents for enterprise applications --- ## What We're Looking For The ideal candidate is: * Strong in both cl...
...drawings must hit an advanced level of detail: framing member sizing, schedules, dimension strings, call-outs, legends, title blocks, and a basic material take-off table. Typical flow I envision 1. User uploads the 2D floor plan and enters site ZIP/postcode. 2. AI parses geometry with computer-vision (OpenCV or similar) and converts it to a clean parametric model. 3. Generative rules (Python, TensorFlow/Keras, or your preferred stack) combine the parsed model with rule-based logic that encodes IRC 2018. 4. Finished sheets are pushed to a CAD/BIM file (DWG, DXF, or RVT) and a collated PDF set. Acceptance criteria • All five plan types render without manual post-processing. • Each sheet carries correct IRC 2018 citations and site-specific loads. • Out...
...to read the rule in , choose the right metric direction automatically and optimise accordingly. I picture the workflow like this: 1. The user drops the four task files into a fresh directory. 2. They run python solution.py. 3. The script detects the data type, the metric orientation and the task family, trains the best available model (scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, Hugging Face transformers—use whatever fits), and writes ready for upload. Acceptance criteria • runs with `python3 ` on a clean machine (specify any pip installs). • The script finishes inside a sensible time window on a single GPU or CPU-only fallback. • It produces a numeric score close to the current public leaderboard baseline for each test
...from. Once the data layer is solid, the core requirement is a fault-detection model that can recognise patterns linked to hardware problems—temperature spikes, power irregularities, component degradation, and similar signatures. Accuracy, low latency, and clear interpretability matter more to me than cutting-edge algorithms for their own sake, so please choose whatever combination of Python, TensorFlow/PyTorch, or any proven libraries you prefer as long as it makes the results easy to explain and monitor. I also want the results surfaced through a lightweight, responsive website. Think dashboard rather than marketing page: live fault alerts, a historical view, and a simple way to download or stream the underlying data. Hosting can be on AWS or another mainstream cloud...
...integrate AI capabilities into user-facing products - Improve system architecture, scalability, reliability, and performance - Collaborate on technical decisions and future AI product development Required Technical Skills - Strong experience with Python and AI/ML development - Experience with AI model training, fine-tuning, and evaluation - Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or similar - Experience building AI pipelines, data processing workflows, and model integrations - Full-stack web development experience - Backend: Python frameworks (FastAPI, Django, Flask, etc.) - Frontend: React, , or modern JavaScript frameworks - Experience designing and integrating REST APIs - Understanding of databases, cloud infrastructure, and deployment workflows ...
I’m refining an AI module that powers a heads-up, visually oriented interface. The core engine is Natural Language Processing, yet right now its intent detection and response generation drift off-target too often. I need your help to push raw and benchmarked accuracy noticeably higher without sacrificing latency. You’ll dive into the existing Python codebase (TensorFlow and a light PyTorch utility are already in play), audit the current model pipeline, then propose and implement improvements—be that better tokenisation, a more suitable transformer architecture, advanced data augmentation, or smarter post-processing. The interface overlays results on a visual HUD, so clean, deterministic outputs matter; hallucinations or fluffed confidence scores show up instantly ...
...Expected Output Example: { "plateNumber": "123456", "country": "Qatar", "plateType": "Private", "confidence": 0.94, "timestamp": "2026-07-07T10:30:00", "cameraId": "CAM-01", "plateImage": "path/to/", "vehicleImage": "path/to/" } Important Requirements: * Developer must have previous experience in ANPR, OCR, object detection, OpenCV, YOLO, PaddleOCR, EasyOCR, TensorFlow, PyTorch, or similar technologies. * The system should be trainable/improvable using our own Qatar/GCC plate dataset. * Accuracy should be tested in day, night, low-light, angled, and moving vehicle conditions. * The final solution should not depend...
...calling the original repo’s model. Deployment setting: mixed environments—classrooms, corridors, and sometimes outdoors—so the pipeline must handle variable light and background noise. My goal is clear: a rock-solid solution that delivers at least 99 % identification accuracy. I’m open to revising or replacing the existing pipeline, whether that means retraining with FaceNet, switching to TensorFlow Lite, integrating OpenCV + Python via a native bridge, or any other approach that reliably meets the target. Key problems to tackle • Incorrect face identification • Slow processing speed • App crashes or errors What I need from you 1. Diagnose the current code and model to pinpoint why accuracy and stability are low. 2. Propose and...
I’m building a proof-of-concept that lets an ultra-low-power board—specifically an ESP3...ESP32’s limits. If you’re interested, send a detailed project proposal outlining: • The model architecture you would adapt or design (e.g., TinyML CNN, MobileNet variants, quantization/pruning strategy) • How you will tackle data collection, augmentation, and on-chip preprocessing • Your plan for optimizing inference time and RAM/flash usage on the ESP32 toolchain (ESP-IDF / Arduino, TensorFlow Lite Micro, or similar) • A validation strategy showing accuracy, sensitivity, and false-positive rates on a held-out image set Final deliverables include compiled firmware, source code, trained weights, and concise build/run documentation so I ca...
...IS A LONG TERM ASSOCIATION, AND WE WILL NOT DEAL WITH YOUR EXCUSES. ONLY GENUINE DEVELOPERS LOOKING FOR A LONG TERM ASSOCIATION. Here is what I need from you: • Architect and code a responsive portfolio website where AI runs the primary logic that shapes pages, layouts, and interactions. • Select and integrate the most suitable AI frameworks or APIs (for example OpenAI, LangChain, TensorFlow, or your own models) so the site can evolve over time without a manual CMS. • Build clean, maintainable code in a modern stack such as React/, Vue/Nuxt, or a lightweight Python/Flask setup—whichever best supports the AI layer. • Ensure deployment on a scalable host (AWS, Vercel, Netlify, etc.) with version control on GitHub or GitLab. Acceptance cri...
...items all the way from booking to delivery. Data flow • Primary data source: customer input collected through web forms. • Optional hooks for historical move data or live market rates should be left open but not hard-wired, so the architecture must remain modular. Tech expectations A lightweight front end (React or similar) can sit on top of a Python/Node microservice that hosts the model—TensorFlow, PyTorch, scikit-learn or whichever framework you feel is best for fast iteration. Clean REST or GraphQL endpoints are essential, and everything should be containerised for easy deployment. Deliverables • Customer-facing responsive form that feeds data to the model • Trained price-estimation model with documented feature set • Inventory-ma...
...practical walk-throughs of code where appropriate. Scope • Introduction to AI concepts – history, terminology, ethics, basic math refresh. • Advanced machine learning techniques – supervised/unsupervised methods, deep learning, model evaluation, hyper-parameter tuning. • Practical AI applications – small end-to-end projects that show theory in production, ideally with Python, Jupyter, TensorFlow/PyTorch and relevant datasets. What I will supply – High-level syllabus with learning objectives. – Branding guidelines and lower-third templates. – Access to any datasets or notebooks you may require. What you will deliver 1. Professionally shot HD recordings (1080p or higher) in .mp4. 2. Clean audio, good lighting and...
...Real-world examples of how you’ve shipped AI-driven products so I can model best practices. Scope highlights – Full-stack focus: front end, back end, and the glue that connects them. – Hands-on AI integration: prompt engineering with Claude, code generation and refactoring in Cursor, and React-based interfaces that surface the AI’s output cleanly. – Openness to additional frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) if they help illustrate a concept, but they’re not mandatory. Acceptance criteria 1. A clear syllabus delivered at the outset, broken into logical modules. 2. At least one functioning demo app completed by the end of our engagement, showing an AI feature in production. 3. Written recap after each session captur...
...is to understand today’s leading architectures—think GPT-style transformers—and then reproduce, extend, and evaluate recent research in natural language processing. Here’s what I need from you: • A clear learning roadmap that walks me through the essential papers, repos, and concepts behind modern text-generation systems. • Hands-on guidance while I set up a Python environment (PyTorch or TensorFlow, Hugging Face Transformers, perhaps LangChain) and fine-tune or train a model on a small dataset. • Practical notebooks that generate text, document the hyper-parameters used, and demonstrate evaluation techniques such as perplexity, BLEU, and human-readability checks. • Regular feedback sessions—screen-sharing, code reviews, tr...
I need an AI-driven solution that plugs into my Oracle instance and pinpoints query-level problems in real time while still giving me the option to run scheduled, deeper analyses. The focus is squarely on query performance: I want to see why certain SQL statements are slow, which...scenarios with minimal false positives. • Real-time visual dashboard plus a scheduler for periodic reports. • Setup guide and usage documentation clear enough for a DBA to maintain going forward. The stack is flexible—Python, Java, or even a low-code AI platform is fine as long as it interacts cleanly with Oracle and can be deployed on-prem. Let me know which libraries (e.g., Scikit-learn, TensorFlow, or Oracle Machine Learning) you plan to use and how you will keep overhead on the da...
...dominate and EXIT the full network, sites, audiences within an 8 week timeframe. You must be an experianced expert, capable of steering, knowing the edgiest reach tool sets and rapid implementation. Perception of rapid growth is extremely important to monitisation and industry view points. Must hyper target - dominate industry influencers with relevent push media. Drive cash flow. We can predict the demise of big media players and use that in exit talks. You must be able to connect with data at pace, clearly explain plans, do work your self, motivate the team, drive monitisation, content ingestion, audiences growth agents. Agree to weekly success fees, kpis - and a "big exit success payment" that reflects your capability and success. You will report to me and my ...
...comparison of four popular Convolutional Neural Network architectures—VGG16, ResNet50, DenseNet121, and EfficientNetB0—on my own custom image dataset (which I will supply as soon as the project starts). The prime metric I care about is accuracy, so every step of the pipeline should be optimised and documented with that goal in mind. Scope of work • Set up a clean training environment in Python using TensorFlow/Keras or PyTorch (whichever you prefer). • Implement, train, and fine-tune each of the four models on the provided dataset, applying standard data-augmentation and early-stopping techniques as needed. • Log and visualise training/validation accuracy and loss curves. • Produce confusion matrices and a concise performance table summarisi...
I need an AI solution that takes product photos and sorts each image into fewer than five preset categories. The sole goal here is image classification—no detection or enhancement features are required. You will start from an existing dataset of labelled product images (I’ll supply a download link once we begin). A lightweight, production-ready model built in Python with either TensorFlow or PyTorch is preferred; transfer-learning from a well-known backbone (e.g., ResNet, EfficientNet, MobileNet) is perfectly acceptable so long as the final classifier is accurate and quick to infer on standard CPU hardware. Key deliverables: • Clean, commented source code for training and inference • The trained model weights (or exported SavedModel / .pt file) • A...
...that mines Satellite imagery and GIS layers with AI so I can validate a larger platform idea. The goal at this stage is pure data analysis: ingest the two data sources, run machine-learning workflows that surface patterns or anomalies, then surface the results through a minimal interface or notebook I can demo to stakeholders. A typical stack for me would be Python with GeoPandas, rasterio, TensorFlow or PyTorch, plus PostGIS or a lightweight spatial database—but I’m open if you have a smarter path. What matters is that the pipeline reliably pulls in the imagery and vector layers, cleans and aligns them, applies the models, and outputs clear, reproducible insights. Please attach past work that proves you’ve built something similar—ideally an AI applicati...
...(script, voice, music and footage) tuned for entertainment niches • Automatic video assembly and aspect-ratio formatting for Shorts • One-click or scheduled publishing with title, description, and hashtag handling • A lightweight dashboard so I can review, approve, or edit clips before they go live I have no fixed opinion on the exact tech stack as long as it scales and stays maintainable; TensorFlow/PyTorch, ffmpeg, Node/React, Python-based backends, or comparable tools are all acceptable if you justify the choice. Clean, well-commented code and deployment documentation are must-haves so I can keep the project running without hand-holding. To help me gauge fit, please link to past work that shows you have built AI or automation pipelines for video, social ...
...seamlessly into our current back-end and scales with user demand. • Three automation tracks—predictive analytics, chatbots/virtual assistants, and automated data processing—each exposed through clean API endpoints. • Solid integration glue so these AI services talk to the rest of the SaaS features (auth, billing, dashboards, etc.). I’m flexible on the underlying framework; if you prefer TensorFlow, PyTorch, Hugging Face Transformers, or another proven stack, that’s fine as long as the final service is efficient, secure, and easy to maintain. Acceptance criteria 1. Endpoints return accurate, low-latency responses under load tests we’ll define together. 2. All code is version-controlled with clear readme and environment setup scripts....
...code entirely on their own—no AI code-generation tools in the workflow. The work is part-time and ongoing. The core of the job is to help me streamline and optimise several business processes. On any given week you might: • explore raw data in pandas, craft insightful visualisations in Matplotlib or Plotly, and present concise dashboards; • build and tune scikit-learn (or similar) models that predict key operational metrics; • wrap those models or analyses in lightweight automation scripts, then integrate them with our existing systems through REST APIs, scheduled jobs, or direct database hooks (PostgreSQL/MySQL). Your deliverables should run smoothly inside our current codebase, pass internal unit tests, and include brief README-style instructions fo...
I’m looking for a fully working AI chatbot written in modern C++. The system must ingest structured data that I’ll provide (typically CSV or a small SQL dump) and turn...parses the structured data and stores it for fast look-ups. • Core dialogue logic: intent detection, record retrieval, and natural-language reply generation. • A simple CLI demo (or minimal GUI) that lets me type a question and receive an answer on the spot. • README with build steps, library dependencies, and a short “getting started” guide including an example dataset. Libraries such as TensorFlow C++, PyTorch C++ API, or even a rules-based engine are fine—use whatever achieves accurate replies with low latency. Deliverables are the complete compilable source, e...
We are looking for experienced Freelance AI/ML Engineers to jo...Engineers to join multiple exciting remote projects. If you have 6+ years of hands-on experience in Artificial Intelligence and Machine Learning, we'd love to hear from you. Requirements: 6+ years of experience in AI/ML development Strong expertise in Python, Machine Learning, and Deep Learning Experience with LLMs, Generative AI, RAG, AI Agents, and Prompt Engineering Hands-on experience with TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain, or similar technologies Experience developing, deploying, and optimizing production-grade AI/ML solutions Excellent analytical, problem-solving, and communication skills Job Details: Role: Freelance AI/ML Engineer Experience: 6+ Years Work Mode: 100% Remote Ope...
... • Works offline after initial installation and enrolment • Fast verification (under two seconds on mid-range Android) • Local biometric templates encrypted at rest • False-accept and false-reject rates comparable to commercial SDKs (we can fine-tune together) • Clean, well-commented source code so our internal team can maintain it Preferred stack is Kotlin or Flutter paired with TensorFlow-Lite or any edge-optimized library you are comfortable with; I’m open to other suggestions if performance is better. If you already have an engine that can be re-skinned, let me know. When you reply, please confirm: 1. Which on-device model or library you propose 2. Hardware you will use for performance benchmarks 3. Typical FAR/FRR you can a...
...recommendations • Natural language processing so users can navigate and issue commands conversationally • Image recognition for instant interpretation of photos the user captures or uploads A single codebase—Flutter, React Native or a similarly efficient framework—should keep maintenance lean, but I’m open to alternatives that achieve equal performance. For the AI layer, feel free to propose TensorFlow Lite, Core ML, or a managed cloud service; low latency and a clear training/inference pipeline matter most. Deliverables • Universal iOS/Android app source code with build scripts • Audited Binance Smart Chain contracts and deployment scripts • Integrated AI models (predictive, NLP, image) with documented pipelines • U...
Wind Detection / Prediction System Built a machine learning model to predict wind patterns/speed based on meteorological parameters, deployed as a web application for real-time predictions. The system takes environmental inputs (such as temperature, pressure, humidity, and location-based data) and outputs wind speed/direction predictions, useful for applications like weather forecasting, renewable energy planning (wind turbine placement), and agricultural planning. Skills demonstrated: Data preprocessing, regression/classification modeling, feature engineering, Flask web integration, model deployment. Student Admission Classifier Developed a machine learning classification model to predict student admission outcomes based on academic and personal parameters (such as GPA, t...
The goal is to build a Claude-powered agent that can ingest our day-to-day operational data, turn it into clear periodic reports, and surface forward-loo...accuracy. Deliverables • Clean, well-commented code repository • Deployment scripts (Docker or serverless) • A short read-me explaining how to add new data sources and adjust reporting schedules • One live demo session to walk through setup, outputs, and maintenance steps Acceptance criteria The agent must produce weekly summary reports without manual intervention and correctly predict at least 80 % of historically observed capacity crunches in a back-test over the last six months. If everything above sounds clear, tell me how you would architect the pipeline and how long you’d need fo...
...gathering business requirements, but the essentials are clear: • You’ll clean, explore, and engineer features from whatever data sources we finalise (they may include structured tables, free-text logs, images, or time-series feeds). • When the data story warrants it, you’ll build and validate predictive or prescriptive models in Python or R, leveraging libraries such as pandas, scikit-learn, TensorFlow, Prophet, or similar. • Clear, decision-ready output matters, so expect to create concise visualisations or dashboards—Tableau, Power BI, or matplotlib/Plotly—alongside well-annotated notebooks and a short slide deck summarising key findings. • Every step should be reproducible. Please version your code in Git and containerise any ...
...institutional-grade IP Intelligence Platform. We provide data-driven predictive insights that replace expensive, manual intellectual property work, such as outside counsel watch services, M&A due diligence, and traditional competitive intelligence. Our platform empowers Chief Revenue Officers, General Counsels, and corporate development teams to quantify the value of their patent portfolios, predict litigation risks, and identify lucrative white-space opportunities. We sell high-ticket subscriptions and project-based reports to organizations that are already spending heavily on IP defense and strategy. The Role We are building a remote, high-performing, commission-only sales team to drive our Go-To-Market strategy. You will be responsible for conducting outreach, running d...
...compliance internally; what I need is a specialist who can design and embed reliable, role-specific assessments that separate top talent from the merely qualified. Here’s where I am: • Positions range from entry-level logistics coordinators to mid-level HR generalists. • We use an ATS (Workday) and video interviewing tools, yet our current skills checks are basic multiple-choice quizzes that don’t predict on-the-job performance. • Turnaround time between screening and job offer has to remain under three weeks. What I’m expecting from you: 1. Audit our existing tests and identify validity gaps. 2. Propose or build new assessments—coding challenges, situational judgment tests, Excel mini-tasks, etc.—mapped to the competencies...
I need a seasoned AI developer to design and deliver a new platform whose core mission is to automate routine tasks inside my business workflow....loop works on at least one representative task. • Source code (Python preferred), environment files, and brief documentation so I can reproduce and scale the system. • Your guidance on the most effective approach—whether the solution relies on machine learning, natural language processing, computer vision, or a hybrid—so long as it meets the automation goal. I’m open to frameworks such as TensorFlow, PyTorch, or spaCy and will welcome your recommendations on cloud services if they speed up delivery. Please outline your proposed approach, similar projects you’ve completed, and an estimated timeline ...
...timestamped breakdown. 3. Clear configuration file showing how event labels, pitch geometry, and stat thresholds can be swapped for another sport without touching the core code. 4. Documentation that explains model choices, data flow, and how a developer can add new metrics or visual templates. If this challenge excites you and you have proven experience with computer vision (OpenCV, PyTorch/TensorFlow), sports analytics, and efficient video processing, let’s talk through your approach and timeline for an MVP....
...documentation so I can roll it out on-prem or to a private cloud. Acceptance criteria 1. Demonstrate each module on recorded sample feeds, then on two simultaneous live cameras. 2. Trigger at least one incident per module and show it flowing through the response console. 3. Provide full source, build instructions, and admin manual in English. If any off-the-shelf libraries (e.g., OpenCV, TensorFlow, PyTorch, or YolovX) speed things up, feel free to leverage them—just keep licensing clean....
...anti-spoofing. • All training and evaluation will rely on publicly available datasets; I already have a concrete shortlist I can share as soon as we begin. • You will implement or adapt a state-of-the-art SSR network, generate the synthetic hyperspectral data, then train comparable RGB and SSR-based pipelines for each task. Deliverables 1. Clean, well-commented code (Python, PyTorch or TensorFlow) covering data preprocessing, SSR reconstruction, task-specific model training, and evaluation. 2. Reproducible experiment scripts and environment files. 3. A technical report suitable for the methods section of a journal paper: datasets, architectures, hyper-parameters, quantitative results (accuracy/AP, ROC, EER, etc.), statistical significance tests, and ablatio...
I run an existing real-estate website and now want to layer AI-driven automation on top of it. My main focus is keeping the inventory data display realtime, answering routine user inquiries, and suggesting the most relevant prop...(Python or Node.js) trained for property availability and scheduling visits, with an easy way for me to add new intents later. • Recommendation service that ranks and serves up properties based on user history, deployable via REST or GraphQL. • Clear setup instructions and commented source so my team can maintain it. If you have prior experience combining real-estate data with tools such as TensorFlow, OpenAI, LangChain or similar, that will help us move faster, but I’m open to any robust stack as long as the final result is reliable a...
...automated-bidding module so buyers can set ceilings and let the system compete for them. • A fraud-detection layer that flags suspicious listings or bidding patterns before a transaction closes. Everything must sit behind a clean, minimal interface—no clutter—because both food and pharmaceutical professionals will be using it every day under time pressure. I’m open on stack, but Python with TensorFlow/PyTorch for the models and a lightweight React or Vue front end makes sense; CUDA optimisation is a plus for the Inception pitch. Acceptance criteria for the MVP: 1. End-to-end workflow: seller upload → AI price suggestion → live auction → automated & manual bids → secure checkout. 2. Latency for price predictions under two seco...
I’m building a web-based application that hinges on a robust Cursor-powered AI component, and I need a sharp mind to craft the model from the ground up. Your main responsibility is to translate the problem statement into a clear-cut architecture: define the data requirements, select o...for help with: • Choosing an appropriate model family and justifying trade-offs • Sketching data preprocessing steps and feature engineering ideas • Defining evaluation metrics and an iterative improvement plan • Delivering a concise technical specification (diagrams, pseudo-code, and any relevant research links) If you’re fluent in Python and familiar with frameworks like PyTorch or TensorFlow—and you have a track record of designing production-grade mod...
Successfully developed a Machine Learning model to predict passenger survival outcomes based on historical maritime data from the Titanic dataset. Key Responsibilities & Tech Stack: Data Preprocessing & Cleaning: Handled missing data thoroughly, including advanced imputation for missing ages using passenger titles. Feature Engineering: Extracted meaningful features like passenger 'Titles' and engineered a 'Family_Size' metric to improve model accuracy. Model Training & Evaluation: Implemented and compared classification algorithms (like Random Forest / XGBoost) to optimize performance, achieving a solid accuracy of 76.54%. Tools used: Python, Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn. This project demonstrates strong capabilities in data ...
...detected action trigger. * Build the Edge-to-Cloud pipeline to upload compressed video fragments efficiently to a secure cloud platform (AWS S3, Google Cloud, or Azure). * Build a clean, lightweight frontend interface (using tools like Retool, Streamlit, or a basic React app) for cloud video playback. ## Required Skills * Deep expertise in Computer Vision and Deep Learning (Python, OpenCV, PyTorch/TensorFlow). * Extensive experience with real-time object detection models (YOLO workflow is highly preferred). * Proven track record building multi-camera RTSP video pipelines and handling edge processing hardware (NVIDIA Jetson or GPU workstations). * Cloud architecture experience (AWS S3 / Lambda or Google Cloud equivalents). * Experience with video encoding and compression (FFmpeg...
...Identify the top five most important variables in your model and provide your own interpretation: Why are they important, and how do they impact your prediction? (“Is it intuitive or counterintuitive? Is the predicted value higher or lower when this variable’s value increases?”) 5. If possible, add some external data to solve this problem: what other factors not included in this dataset can help to predict our target? Submission The assignment must be delivered in a Python notebook. 1) Please follow the attached files 2) No AI 3) Follow the comments from pervious assignment A2.1 Comment: Hello Mohammed, Thank you for submitting Assignment A2.1. Here is your feedback: Your submission demonstrates exceptional technical sophistication, particularly in your i...
...your daily workstation. The heaviest lift right now is integrating and refining our AI components, so a solid grasp of TensorFlow workflows is essential. Someone in Chile preferred to understand Chilean market and its specific customer needs. You’ll work end-to-end across the JavaScript stack—Node.js services, browser interactions, and the shared utilities that glue them together—while also writing the Python glue code that moves data to and from our models. Experience with cursor-based data handling and at least two years of professional development in these languages will help you hit the ground running. Day-to-day you will: • Extend and optimise existing TensorFlow models, then expose them through clean APIs. • Build and maintain f...
...scalability, and security of cloud environments - Monitor and optimize cloud costs and performance - Experience with Kubernetes, Docker, and CI/CD pipelines 3. AI/ML Engineer - Develop, train, and deploy machine learning and deep learning models - Work with large datasets to build predictive and analytical solutions - Integrate AI/ML models into production systems - Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn - Strong background in NLP, computer vision, or generative AI is a plus 4. Data Engineer - Build and maintain robust data pipelines and ETL processes - Design and manage data warehouses and data lakes - Work with large-scale distributed systems such as Apache Spark, Kafka, or Airflow - Collaborate with data scientists and analysts to support dat...
...and send the push notification photos to the main pc Should be able to load 40 camera per hub depending on the specs of the hub pc • Video input will arrive over standard RTSP / ONVIF streams from existing IP cameras. • Accuracy and speed matter more than fancy UI elements; a lean desktop or web dashboard that shows the current feed, bounding boxes, and an alert log is enough. • OpenCV, TensorFlow or a comparable framework is fine; I am open to the model you recommend as long as false positives remain low in typical indoor-outdoor lighting. • Platform can be Windows, Linux, or a cross-platform container—choose what lets you ship fastest without licensing headaches. Selected detection modes (mandatory) • Human detection • Vehicle de...
...posts through the relevant platform APIs, pushing traffic back to the knock knock website. • Feedback loop: pull engagement metrics into n8n so the AI can refine tone, length and formats to iterate constant improvement. 2 goals. Mass eyeballs, engagement. Convert eyeballs to buyers of homes or leads for realestate agents that pay us $10 pw for predictions and leads. Collect sentiment data to predict people selling a home and share that with our agent dash board. We pay significant success fee on top of base rate or per project fee. What I need from you 1. Set up the complete n8n pipeline, fully documented so I can tweak triggers or copy variations later. 2. Configure AI prompts and variables that keep messaging on-brand for real estate while still feeling disrupti...
