Tensorflow estimator predictproiecte
Am nevoie de o aplicatie in tensorflow pentru comanda vocala, aplicatia trebuie sa fie in romana.
...to 17000, at 17000 and before goes to 16500 big action happen you need to consider carefully : it is moving fastly through all the 55 pages to show them and you need to store those 55 pages(at this instance you need to captured those page photos and store them and the time taken associated), no csv files only photos please, at counter value 17000 the mouse shape changed, keep your eye on it to predict the future move of this excel file. This counter CA31 value is same in all pages, so if it got value of 17000 then its same in all other pages. This counter in page hkdsgd is at BR128. Give me the input in your code the 9 digits of screenleap page to enter to follow up because this 9 digits number changed frequently not fixed. Do your code again and take your time in testing please ...
...remote teams Required Skills Frontend Development React, , React Native TypeScript, JavaScript (ES6+) Redux Toolkit, React Query Tailwind CSS, HTML5, CSS3 Responsive UI design Progressive Web Apps (PWA) Backend and API Development Node.js, Java, Python, Go, C#, or .NET Core Flask, FastAPI, or Django REST APIs, GraphQL, or gRPC Microservices architecture Machine Learning and AI TensorFlow, PyTorch, Scikit-Learn, or similar frameworks Experience working with LLMs and modern AI frameworks Prompt engineering, RAG, or vector databases is a plus Cloud and DevOps AWS, Azure, or Google Cloud Platform Docker and Kubernetes CI/CD pipelines and deployment practices Data and Systems SQL or NoSQL databases (PostgreSQL, MySQL, MongoDB, Redis) Data processing and scalable...
I need a seasoned statistician who can move comfortably between classical regression techniques and modern Convolutional Neural Networks. The project centres on predictive analytics: you will build, compare and explain regression-based models, explore where a CNN adds value, and present the insights through clear, publication-ready visualisations created in Python (think pandas, scikit-learn, TensorFlow/Keras, matplotlib, seaborn or Plotly—use what fits best). We will begin with a brief video call so I can walk you through the dataset, the business question and the success metrics. After that, you will take full ownership of data preparation, model selection, training, validation and visual storytelling. Expect to hand back clean, well-commented notebooks and graphics that a ...
Business Name: Score Predictor Concept: Mobile app where users predict football match scores, earn points, and win small cash prizes. Goal: Build MVP prototype with Premier League matches for testing, then expand to Championship, European competitions, and special jackpot games. Business Model: Users pay a small entry fee per round, £1 per round. Users can predict as many rounds as they wish; winners receive cash prizes. Revenue comes from entry fees and potential in-app advertising or sponsorship later. Backend: Connect to a football data API for live scores & league tables; scalable for future expansion.
...excel as and •Process the data in python •Create a function in python that will generate individual reports (word or PDF format) – sample 5 reports (for delivery), not 1000 and produce them as files. •Create visuals for the web report or individual reports as needed. •Elaborate any correlation between variables (if and when applicable) •Apply linear regression to predict the Digital maturity level for an input variable. •Show top 10 best vs 10 worst cases in dashboard. •Final result should look like this (we want this or similar, maybe streamlit) Deliverables: Both Excel Files; Python analysis code; Sample reports (5 pdf or word); web dashboard with items as per reference. Below you have sample data from previous reports delivered
...excel as and •Process the data in python •Create a function in python that will generate individual reports (word or PDF format) – sample 5 reports (for delivery), not 1000 and produce them as files. •Create visuals for the web report or individual reports as needed. •Elaborate any correlation between variables (if and when applicable) •Apply linear regression to predict the Digital maturity level for an input variable. •Show top 10 best vs 10 worst cases in dashboard. •Final result should look like this (we want this or similar, maybe streamlit) Deliverables: Both Excel Files; Python analysis code; Sample reports (5 pdf or word); web dashboard with items as per reference. Below you have sample data from previous reports delivered
...monitoring dashboards and retraining scripts Acceptance criteria A working API must return real-time predictions within agreed latency limits, integrate seamlessly with the current SMTP/ESP workflow, and include logging for compliance review. Final delivery is considered complete when the system runs in production and all documentation passes peer review. Tools & stack Python, scikit-learn or TensorFlow, SQL/NoSQL for data storage, and standard MLOps utilities (Docker, CI/CD) are anticipated, yet alternative libraries are welcome if they meet the same reliability and security standards. Timeline and milestones will be outlined together at project start, with code reviews scheduled at each major checkpoint....
...compare each face against a gallery to decide whether it is an identical match. • Serve three environments without extra rewrites: security-grade CCTV feeds, social-media style mobile uploads, and large photo-management archives. • Deliver low latency on a single modern GPU while still running acceptably on CPU-only hardware for lightweight deployments. I’m comfortable with either PyTorch or TensorFlow/Keras; use the framework you know best. A pre-trained backbone such as ResNet, MobileNet, or Vision Transformer is fine as long as you include the full training pipeline so I can continue to improve the model with fresh data. Deliverables 1. Source code with clear, commented modules for detection, embedding generation, and similarity matching. 2. Pre-tra...
...combine traditional threat-intel techniques with machine-learning pipelines so the system continuously adapts as new data arrives. Here’s what success looks like to me: • A modular data-collection layer that can stream pcap, NetFlow, or similar log formats into a preprocessing engine. • Feature-engineering and model-training code written in Python (feel free to leverage Pandas, scikit-learn, TensorFlow, PyTorch—whatever best suits the task). • A detection component that scores incoming traffic and raises alerts via a simple REST API or CLI output. • Clear documentation covering setup, retraining, and how new data sources—such as endpoint events or social-media threat chatter—could be plugged in later. Because this is time-...
...stability, thermal management, and seamless connectivity transitions. Technical Specifications: 1. Camera Pipeline & Intelligent Routing: Implement CameraX to ensure maximum compatibility across various Android OEMs (Samsung, Pixel, Xiaomi, etc.). Develop a Routing Engine to ingest the camera stream and dispatch frames to two parallel modules: Offline Module: Local processing using ML Kit or TensorFlow Lite for immediate tasks (e.g., fast OCR, object proximity). Cloud Module: Optimized frame streaming (compressed JPEG/WebP) to the Google Gemini Flash API (target: 1-2 frames per second). 2. Smart Connectivity Fallback: Implement a robust network listener using ConnectivityManager / NetworkCapabilities. Automatic Failover: The system must detect low-latency or lost sign...
...a MySQL database. Each stored image must be linked to the corresponding frame number and any detection metadata so I can later query, filter, and analyse the results. Once the data is stored, I want a lightweight viewer that steps through the saved frames in order, overlaying the detection boxes so I can visually confirm accuracy. OpenCV for frame extraction and display is acceptable; YOLO, TensorFlow, or another modern model is fine so long as the code is clean, well-commented, and easy for me to retrain with additional classes. To keep the hand-off smooth, please include: • A self-contained Python 3 script (or module set) that performs detection, inserts frames into MySQL, and plays them back. • The SQL schema and sample data script. • A brief README explai...
...rewrite. On the modelling side, I want a workflow that lets me start a new model from scratch, feed in data, train, save, and then reuse that model inside the video generator. Ideally this is handled behind a clean dashboard rather than command-line steps. Core expectations • Intuitive UI/UX for both the video creator and the model-training console • Scalable backend (Python, PyTorch/TensorFlow, or comparable) with GPU support • Real-time preview for voice and style selections • Secure user accounts and storage for datasets, models, and rendered videos • Source code, build instructions, and a short hand-off call on completion If you have a reusable codebase or experience with generative media tools such as Stable Diffusion, FFmpeg, or J...
Szukam doświadczonego developera, który stworzy dla mnie bot...środki rzeczywiste. Po stronie technicznej liczę na: • Model uczenia maszynowego lub kombinację algorytmów statystycznych reagujących w sekundowym interwale. • Integrację z order book, jeśli pozwala na to przepustowość API. • Dashboard lub prosty panel www/CLI do podglądu metryk, stanu konta i ręcznej interwencji. W zgłoszeniu napisz, proszę: 1. Jakiej dokładnie architektury i bibliotek (TensorFlow, PyTorch, CCXT, itp.) zamierzasz użyć. 2. Szacowany czas realizacji poszczególnych etapów. 3. Koszt wykonania oraz model późniejszego utrzymania i aktualizacji. Zależy mi na długofalowej współpracy i stabilnej rentowności, przy pełnej świadomości ryzyka ...
...a researcher who can build a production-ready model that listens to a baby’s cry, watches the paired video, and decides—reliably—whether the cause is hunger, discomfort, or simple attention seeking. Audio and video must be fused inside one architecture; running them in parallel but independently will not satisfy our accuracy goals. You may use the deep-learning stack you trust most (PyTorch, TensorFlow, Keras, OpenCV, torchaudio, etc.) provided the final network can run in real time on an edge device and be exported to ONNX or TFLite. I will share product constraints and a small proprietary data set; you will expand it through public sources or augmentation, perform rigorous cross-validation, and refine the model until we consistently exceed 90 % precision and ...
...The specifications on the calculators and keywords will be provided. However, you may need to scrape or research needed data for the pages, such as available resources in a specific area. On every page, visitors should see a lightweight, embedded calculator that runs in-browser and never forces a page reload. For launch, that means 22 calculators (budget planner, debt payoff, emergency-fund estimator, etc.). The calculators can rely on vanilla JavaScript injected by the generator, but the build logic itself should remain in Python for consistency. Finally, I need an insertion script that scans each freshly generated file, matches relevant keywords, and drops partner affiliate links into pre-defined blocks without breaking the layout or SEO structure. Deliverables • Pyth...
...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...
...dataset available. But definately need a NEW DNN training Dataset. simple UI . Total Project is 250 USD STAGE 1 - 100 USD STAGE 2 100 USD Deplyment, Testing and Document 50 USD STAGE 1 handles intelligence + cloud STAGE 2 handles device + communication + app STAGE- I Backend Engineer (Cloud + Data + API) Deep Neural Networks for classification (imbalanced datasets, SMOTE preferred) Python (TensorFlow/PyTorch) and model deployment via REST API Handling weather/time-series datasets Cloud hosting (Azure/AWS) and database management SMS gateway integration and push notification backend Secure API development and logging system Deliverable: Deployed ML model with working API endpoint and backend system. STAGE 2 — Embedded & Mobile Systems Engineer (LoRa + App + Hardware...
I have an ongoing structural-optimization study that will be powered by a large language model...Deliverables • Python scripts and MATLAB functions that load data, train the LLM, and call the structural optimization routine. • Clear documentation (inline comments and a short README) so I can rerun the experiments on my workstation. • A brief report summarizing training results and the improvement achieved in the optimized designs. All work must execute on standard Python 3.x with PyTorch (or TensorFlow, if preferred) and MATLAB R2021a+. Provide any additional open-source libraries in a requirements list. Once the code reproduces the baseline accuracy and demonstrates a measurable structural-performance gain, the project is considered complete and ready for the n...
I have a steady flow of commercial jobs and detailed architectural plans ready to go; what I need now is a sharp estimator who can turn those drawings into clear, competitive numbers. Your primary focus will be pricing material and labor—subcontractor quotes are already handled elsewhere—so tight take-offs and realistic crew‐hour projections are critical. Typical workflow • I send PDFs or DWG files and my bid form. • You perform a full material and labor quantity survey in Bluebeam, PlanSwift, or similar, then apply current market pricing (RSMeans, supplier quotes, or your own database). • You return an itemized spreadsheet with unit costs, a concise executive summary highlighting risk items, and any clarifying notes that will help me defend the num...
...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...
I need a complete transient (surge) study for a 13-km buried pipeline that carries treated wastewater from our STP. The goal is to predict all critical pressure extremes, then turn those numbers into practical hardware locations so the line can be protected before we commission it. Scope of the study • Model the existing line geometry, elevations and flow data (I will forward the General Arrangement Drawing as soon as it is finalised). • Simulate the three key operating upsets that worry us: pump start/stop sequences, planned valve manoeuvres, and a full power-failure trip. • Identify positive and negative pressure envelopes, vapour pocket risks and column separation zones. • Translate the results into a clear markup on the GAD, showing where air-release...
...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...
I already have a working estimating spreadsheet program with extensive data base. I now need to add further columns to improve the estimating spreadsheet. Here is what I’m looking for: • Add to the current spreadsheet with additional information i have. • Display the information from a data base. • Make sure the new calculations pick up the same input data fields • Provide clear, concise documentation of every new function and a short change-log so I can track what was modified. • Include a small sample project or test file showing the results of the new time calculations against known benchmarks; this will be the acceptance criterion. The existing program is stable and I have full source control access; you will receive a Git branch to work in. ...
...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...
I need a web app that allows users to predict match winners in cricket. Key Features: - Match Winner Prediction: Users can predict who will win a match. - Player Performance Prediction: Users can forecast batting, bowling, and fielding performances. - Display Predictions: Predictions should be shown as numeric probabilities. Ideal Skills and Experience: - Experience in developing web applications - Familiarity with cricket and its statistics - Ability to create prediction algorithms - Skills in UI/UX design for clear numeric display
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...
Job Description: The Exterior Cladding Estimator will be responsible for preparing accurate material takeoffs andestimates for exterior cladding systems. This role requires strong attention to detail, the ability tointerpret architectural drawings, and a practical understanding of exterior building components. Responsibilities: ~ Estimating & Takeoffs Review architectural drawings for all project locations ~Identify all required exterior elements, including hidden areas, returns, soffits, andtransitions ~Prepare clear and accurate takeoffs showing total square footage (SF) of all requiredmaterials ~Ensure all scope items are fully captured and documented ~ Material Quantities & Optimization Create detailed material counts for cladding sheets and extrusion systems ~...
Job Description: The Exterior Cladding Estimator will be responsible for preparing accurate material takeoffs andestimates for exterior cladding systems. This role requires strong attention to detail, the ability tointerpret architectural drawings, and a practical understanding of exterior building components. Responsibilities: ~ Estimating & Takeoffs Review architectural drawings for all project locations ~Identify all required exterior elements, including hidden areas, returns, soffits, andtransitions ~Prepare clear and accurate takeoffs showing total square footage (SF) of all requiredmaterials ~Ensure all scope items are fully captured and documented ~ Material Quantities & Optimization Create detailed material counts for cladding sheets and extrusion systems ~...
...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...
...the solution must actually do once deployed: • Predict individual risk levels instantly after a prospect submits an application, using supervised models trained on our claims history. • Recommend the most suitable policy and limits automatically, showing the visitor a clear quote while passing the selected product and premium back to our 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, PyT...
I’m preparing a research paper that demonstrates how explainable AI can predict and interpret student academic grades using a mix of exams and quizzes, assignments and projects, plus class participation records. I already have raw datasets in CSV form; what I need is the complete experimental pipeline and a well-structured manuscript ready for journal submission. Here’s what I’m expecting: • Clean and engineer the three data sources so they align on student IDs and time frames. • Build at least one solid predictive model—feel free to compare alternatives—but tie every result back to a clearly articulated explainability layer (e.g., decision trees, SHAP, LIME or any other method you justify). • Evaluate accuracy and, just as importa...
...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...
We are seeking an experienced estimator to prepare a full interior demolition takeoff and HARD-BID estimate from provided blueprint PDFs. This estimate will be used for a fixed-price contractor bid. Conceptual estimates, rough budgets, or high-level approximations are not acceptable. Quantities, pricing logic, and assumptions must be clearly defined and defensible. Scope of Work Estimator will review drawings and produce the following: 1) Detailed Quantity Takeoff Interior partitions – LF by wall type with stated height assumptions Ceilings – SF by type Flooring – SF by type Base – LF Doors & frames – EA Casework / millwork – LF or EA Specialties – EA where applicable MEP demolition as allowances unless explicitly show...
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...
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...
I have a steady flow of commercial electrical projects that need accurate, defensible cost estimates before they move into bidding and construction. You will receive full drawing sets, specifications, and any addenda; from there I need a detailed take-off, labor and material pricing, and a concise executive summary that I can hand straight to the project manager. Please be comfortable interpreting commercial-grade plans, applying current NEC requirements, and using mainstream tools such as Accubid, ConEst, Trimble or a comparable platform—whatever lets you turn around numbers quickly without sacrificing precision. Deliverables for each assignment: • Digital take-off file (native format + PDF) • Line-item labor & material spreadsheet with clear assumptions &bull...
...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 a detailed fatigue analysis for FRP composites under cantilever loading conditions. The main goal is to predict fatigue life and generate S-N curves. Key Requirements: - Analyze fatigue behavior under cantilever loading - Predict fatigue life - Develop S-N curves Ideal Skills: - Expertise in fatigue analysis - Experience with FRP composites - Proficient in mechanical loading simulations Please include relevant experience in your bids.
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...
