Tensorflow jobs

My goal is to roll out an end-to-end AI solution that takes several repetitive business tasks off my team’s plate. I want to automate data entry, streamline inventory tracking, and tighten up customer-relationship workflows in one cohesive platform. The stack has to cover everything—from model design and training (think Python, TensorFlow / PyTorch, spaCy, or similar) through to a user-friendly front-end and robust back-end that can slot neatly into our current systems via APIs or webhooks. Here’s how I picture the engagement: • You architect and code the machine-learning and natural-language models that will drive the automations. • You build the surrounding web application (front-end + back-end) so staff can trigger, monitor, and override tasks when...

...and can fire an air-jet gate on command. What I need next is a production-ready program that • ingests each frame in real time, • detects spongy, internally damaged or otherwise bad fruit with high precision, and • sends the gate signal fast enough to remove the defect before the next fruit arrives. You are free to design the detection pipeline—classical CV with OpenCV or a small CNN in TensorFlow/PyTorch—as long as it runs on the on-board GPU (NVIDIA Jetson Xavier) and meets the timing budget of 60 ms per fruit. I will supply a labelled image set of good vs. spongy mangoes for training and a live video feed for validation. Deliverables 1. Well-commented Python source code ready to run on Ubuntu 20.04 (Jetson). 2. Model weights and training not...

...edge pointed squarely at high-frequency algorithmic trading. The goal is a production-ready strategy that delegates the intensive optimisation loop to a quantum co-processor while letting a classical AI layer handle real-time signal evaluation and risk controls. Here’s what I have in mind: the quantum side tackles portfolio state-space exploration—think QAOA, VQE or amplitude-estimation—while TensorFlow / PyTorch models learn micro-structure patterns from live tick data and route only the most promising parameter sets back to the gate model. Latencies must stay sub-millisecond from signal to order, so a coherent design for GPU–FPGA–QPU orchestration is essential. Deliverables • A documented architecture diagram showing data flow between clas...

...increase variability and improve the model’s ability to generalize. The core of the system will involve developing a Convolutional Neural Network (CNN) using either TensorFlow/Keras or PyTorch. The model will be trained and optimized through experiments with different parameters and configurations. Its performance will be evaluated using commonly used metrics including accuracy, precision, recall, and F1-score, along with a confusion matrix to better understand the model’s performance across individual disease classes. Once a satisfactory model is obtained, it will be saved in a deployable format such as H5, PyTorch (.pt), or TensorFlow SavedModel. This trained model will then be integrated into a Streamlit application, where users can upload an image of a pl...

I need a full-length research paper prepared and shepherded through publication in a Scopus-indexed Q2 journal. The topic is neural-network-based detection of visual defects in woven or knitted textiles, implemented in Python. I am flexible about the framework—TensorFlow, PyTorch, Keras or a comparable library is fine—so long as the final code is reproducible and well-commented. The paper must include a solid literature review, a clearly explained network architecture, an experimental section using a representative dataset of fabric images, and a results discussion that meets the methodological rigour typical of Q2 outlets. I will supply any proprietary images I have; if additional public datasets are needed, please curate them. Deliverables • Draft manuscript f...

I am preparing a full-length research article on automated fabric defect detection in industrial environments, driven by convolutional or hybrid neural networks coded in Python with TensorFlow or PyTorch. The end goal is a manuscript ready for submission to a Q2 Scopus-indexed journal, followed through peer-review until final acceptance. What I need from you • Curate or locate a high-quality, publicly shareable dataset (or assemble one from open sources) that covers common textile defects in varied lighting and weave patterns. • Design, train, and tune an appropriate neural-network architecture; document every experiment so the methodology section is fully reproducible. • Produce clear performance analyses—confusion matrices, precision-recall curves, abla...

...results against relevant baselines, and articulating the implications for real-world textile quality control. Once the research is solid, the manuscript needs structuring to meet the target journal’s author guidelines, followed by submission, peer-review revisions, and final proof corrections until the paper receives an online-first DOI. Key expectations • Strong, reproducible Python code (TensorFlow/PyTorch preferred) and a concise repository or supplemental ZIP. • Clear methodology, statistically sound evaluation, and visuals (confusion matrices, heatmaps, sample detections). • Proper referencing in the journal’s citation style and compliance with originality checks (≤10 % similarity). • Active liaison with the editorial office and pr...

...- Build and improve computer vision pipelines for identity verification - Work with large-scale datasets to improve accuracy and reliability - Optimize models for real-world deployment on edge devices and cloud systems Requirements - Strong experience in Machine Learning / Deep Learning - Hands-on experience with Computer Vision - Proficiency in Python and ML frameworks such as PyTorch or TensorFlow - Experience working with large datasets and model training Preferred - Experience with face recognition systems - Familiarity with models such as ArcFace, FaceNet, or similar - Experience withLLMs or multimodal AI systems Application Please send: - Your resume - A short summary of your past Computer Vision or LLM projects - Any GitHub, portfolio, or relevant work (if av...

I have three full years of trend data sitting in a single Excel workbook. Each row records a two-digit value, and I now need a machine-learning model that can reliably forecast both the “inside” and “outside” four-digit combinations drawn fro...and outputs predictions. • A brief write-up of feature engineering, model choice, and validation results demonstrating the required accuracy. • A simple way for me to paste new two-digit data and receive fresh four-digit predictions—command-line script, Jupyter notebook, or lightweight GUI is fine. Please outline the algorithms or libraries you plan to use (e.g., pandas, scikit-learn, TensorFlow, PyTorch) and how you will ensure the accuracy threshold is met. I am ready to start as soon as I conf...

...journals. The role involves supporting the research and manuscript preparation process. All work must follow standard academic integrity and publication ethics. ⸻ Scope of Work The assistant will help with: • Literature review on recent machine learning and deep learning methods • Supporting experimental design and benchmarking • Assisting with implementation and experiments (Python / PyTorch / TensorFlow preferred) • Preparing figures, tables, and experimental analysis • Structuring and editing manuscripts for clarity, scientific rigor, and journal readiness • Ensuring formatting suitable for Scopus-indexed journals ⸻ Target Papers • 2 experimental research papers • Approximately 12–13 pages each • Topics may include machi...

...already experienced, so each session must go straight into advanced techniques in Machine Learning and Data Visualization—no surface-level overviews. What I need you to handle • Shape the complete syllabus, ensuring a logical progression of advanced ML and visualization topics • Build concise slide decks, hands-on notebooks, and sample projects (Python, Jupyter, scikit-learn / PyTorch / TensorFlow, Plotly / Matplotlib) • Present and moderate the live webinars, fielding in-depth questions from a senior crowd • Record, edit, and package each session so the material remains valuable on-demand • Supply follow-up exercises and reading that keep participants engaged between events Acceptance criteria • First live session ready to broadc...

...pricing comparison, quality of goods/services, and overall reliability, then deliver concise, visual reports every single day. Your work should cover data pipeline design, model training or configuration, and a lightweight dashboard or API so my team can pull the insights straight into our ERP. I’m open to AWS, Azure, or GCP; if you prefer Python with libraries such as Pandas, scikit-learn, or TensorFlow, that fits our stack well. Acceptance criteria – the project is complete when: • Daily reports arrive automatically without manual triggers. • Each report scores vendors on price, quality, and reliability, flagging outliers and opportunities. • Dashboards/APIs export to CSV and JSON and are reachable from the cloud console with role-based ac...

...at multiple resolutions. On top of the stills I’d like a lightweight generator for short promo clips: the tool should string a few processed images into a 6–10 sec video, trim any silent gaps automatically, add royalty-free background music, simple captions, and tasteful transitions so I can post straight to social media. I’m open to the underlying tech. If you lean on Python with OpenCV, TensorFlow / PyTorch for segmentation, or use ready APIs like , that’s fine as long as the licence allows commercial use. A small React or Flutter front end that lets me test the workflow locally will be a bonus. Acceptance criteria 1. One uploaded photo returns a transparent-background PNG plus a white-background JPEG in under 10 seconds on mid-range hardware. 2...

I’m running a head-to-head study of several classic and deep-learning classifiers—KNN, Logistic Regression, linear SVM, Kernel SVM, and a simple feed-forward Neural Network—using both the original MNIST digits and the Fashion-MNIST images. I want the two datasets treated wit...Deliverables • Well-commented Python notebook(s) or script(s) showing data loading, preprocessing pipeline, model training, and evaluation • A short comparative report (PDF or markdown) highlighting results, insights, and any surprising findings • Plots or tables that clearly display metric scores and, where helpful, confusion matrices If you already have utilities for Scikit-learn or TensorFlow/PyTorch, feel free to leverage them—just keep the workflow reproduci...

...will design and execute the full experimental evaluation pipeline. This project focuses on rigorous experimentation and evaluation, not developing new ML models. Required Skills Strong candidates should have experience in: Machine Learning / Deep Learning Computer Vision for remote sensing Geospatial data processing Experimental design for research papers Technical stack: Python PyTorch or TensorFlow OpenCV NumPy / Pandas Scikit-learn Matplotlib / Seaborn AWS cloud workflows GPU computing Experience with the following is highly desirable: Satellite imagery processing GeoJSON / GDAL STAC catalogs LLM integration Retrieval-Augmented Generation Nice-to-Have Experience Experience with: Academic ML research Remote sensing journals Geospatial AI Multimodal AI pipelines Experiment r...

...against a held-out test set, with clear reporting on feature importance and model performance (precision, recall, F1). The image-recognition piece will classify and tag uploaded photos, surfacing confidence values for each label. A lightweight front-end demo or notebook that shows the model running on sample images will help us validate results quickly. Preferred toolchain includes Python, TensorFlow or PyTorch for model development, plus standard libraries for data handling (Pandas, scikit-learn, OpenCV as needed). If you have a different stack that still meets these requirements, mention it and explain the trade-offs. Deliverables • Trained predictive-analytics model with reproducible training script • Trained image-recognition model with inference endpoint or ...

...will design and execute the full experimental evaluation pipeline. This project focuses on rigorous experimentation and evaluation, not developing new ML models. Required Skills Strong candidates should have experience in: Machine Learning / Deep Learning Computer Vision for remote sensing Geospatial data processing Experimental design for research papers Technical stack: Python PyTorch or TensorFlow OpenCV NumPy / Pandas Scikit-learn Matplotlib / Seaborn AWS cloud workflows GPU computing Experience with the following is highly desirable: Satellite imagery processing GeoJSON / GDAL STAC catalogs LLM integration Retrieval-Augmented Generation Nice-to-Have Experience Experience with: Academic ML research Remote sensing journals Geospatial AI Multimodal AI pipelines Experiment r...

I’m expanding our team with an AI engineer who can take the lead on end-to-end Machine Learning work. The immediate focus is on time-series data: everything from cleaning raw feeds through to building and shipping a production-ready predictive model. You’ll be working in Python (think pandas, NumPy, scikit-learn, TensorFlow or PyTorch) and will have the freedom to introduce the tools you’re most comfortable with, as long as the final stack is reproducible and easy to maintain. Here’s what I need from you: • Prepare and engineer the time-series dataset so that it’s model-ready, documenting every transformation. • Design, train, and iterate on forecasting or anomaly-detection models that outperform a naive baseline. • Hand over clean, wel...

...web interface that presents predictions in an easy, fan-friendly format. Odds-style percentages, form graphs, and key player influences should surface prominently so visitors can grasp the rationale behind each forecast without reading a research paper. Front-end can be React, Vue, or another modern framework you’re comfortable with, as long as it’s lightweight and mobile responsive. Python (TensorFlow, PyTorch, or scikit-learn) is fine for the back-end model; Node or Django for the API that serves predictions—your choice so long as deployment to a standard cloud stack (AWS, GCP, or similar) is straightforward. Deliverables • End-to-end trained model with reproducible training script • Automated data-ingestion jobs connected to the two specif...

...through workout exercises and analyzes body movement during the exercise using the front camera. Pose detection must run locally on the device using: MoveNet Lightning – TensorFlow Lite No video or images should be uploaded to the server. The app should follow an offline-first approach, allowing workouts and results to be stored locally when internet is unavailable. Budget: FROM 400 TO 1000 $ Timeline: Flexible Tech Stack Framework Flutter (Dart) Expected packages: camera tflite_flutter video_player flutter_secure_storage Hive or SQLite Backend: Supabase Pose Detection Model: MoveNet Lightning (TensorFlow Lite) Important Project Scope The motion signatures for exercises will be provided by us. Each motion signature represents the reference movement ...

...behavioural cues—hand placement, posture and, ideally, gaze direction—to confirm active usage. Whenever the model judges that the phone is being used, it should trigger an audible or visible alarm on the host machine instantly; no other logging or alert channels are required for this first iteration. I am happy for you to choose your preferred computer-vision stack (e.g. OpenCV, MediaPipe, PyTorch, TensorFlow, ONNX) as long as the end result runs on a typical workstation without specialised hardware. Pre-trained networks are welcome, but please include any fine-tuning scripts so I can reproduce the results. If additional datasets are needed, point me to openly licensed sources or provide clear collection guidelines. Deliverables • Source code with clear setup ...

...cues—hand placement, posture and, ideally, gaze direction—to confirm active usage. Whenever the model judges that the phone is being used, it should trigger an audible or visible alarm on the host machine instantly; no other logging or alert channels are required for this first iteration. I am happy for you to choose your preferred computer-vision stack (e.g. OpenCV, MediaPipe, PyTorch, TensorFlow, ONNX) as long as the end result runs on a typical workstation without specialised hardware. Pre-trained networks are welcome, but please include any fine-tuning scripts so I can reproduce the results. If additional datasets are needed, point me to openly licensed sources or provide clear collection guidelines. Deliverables • Source code with clear setup inst...

...clients. The project is urgent and needs to be completed ASAP. Key Requirements: - Engaging and interactive presentation of AI capabilities - High-quality visuals and graphics - Clear and concise messaging tailored to potential clients - Experience in marketing materials and AI technologies is a plus Scope • Build the complete workflow in Python, using current mainstream libraries (scikit-learn, TensorFlow or PyTorch, plus supporting tools such as pandas, NumPy, and Streamlit/Plotly for visual insights). • Provide clean, reproducible code, modular enough to be adapted later. • Document the entire pipeline with architecture and data-flow diagrams, plus a concise narrative that explains each stage to a non-technical audience. • Incorporate rigorous evaluation...

...product pages, and in abandoned-cart emails. • Sales forecasting dashboards that help me plan inventory and promotions. • Customer-behavior analysis to segment audiences, predict churn, and surface upsell opportunities. Tech expectations Python is non-negotiable; a Django or FastAPI backend paired with a lightweight front end (React or plain HTML/CSS is fine) makes sense. For ML models, TensorFlow, PyTorch, or scikit-learn are acceptable, provided they can be trained on my transactional data and updated regularly. The marketing layer may tap APIs such as Twilio or WhatsApp Business. Acceptance criteria 1. A live, responsive e-commerce site running on my server or cloud account. 2. Admin console with inventory, order, and campaign modules fully tested. 3. M...

Project Title: Iraqi License Plate Detection and Recognition using Python (YOLO + OCR) Description: I am looking for a developer to build a complete Python project for automatic Iraqi vehicle license plate detection a...license plate number and characters. 4. The system should support Arabic letters, English letters, and Arabic-Indic numbers used in Iraqi license plates. 5. Use data augmentation techniques (rotation, blur, illumination changes) to improve model performance. 6. Provide training and testing scripts. 7. Provide the full Python source code. Tools preferred: - Python - YOLOv8 - OpenCV - PyTorch or TensorFlow - EasyOCR or Tesseract Output required: - Full working Python code - Trained model - Instructions to run the project I already have a dataset of Iraqi licen...

...testing, finetuning iterations is key. Key Requirements: • Pure Python RPA, with the core orchestrator, no third part tool. • Web navigation/ scraping with Selenium/Playwright: document download, classification, OCR/text extraction. • Build/train neural networks (e.g., CNNs for image doc classification). • NLP expertise with spaCy for entity extraction. • Computer vision using TensorFlow/OpenCV (offline Vision Libraries preferred). Preferred Skills: • MLOps (e.g., MLflow, Docker for deployment). • Strong problem-solving for complex, error-prone workflows. • 2+ years portfolio with RPA/CV projects (GitHub links required). Project Details: • Milestones: Week 4 (scraper prototype), Week 8 (CV model), We...

...algorithms—feel free to propose anything from Logistic Regression and Random Forests to XGBoost, LightGBM or even a small neural net if it clearly outperforms classical methods • Evaluating with cross-validation and reporting key metrics such as precision, recall, F1, ROC-AUC and a confusion matrix on an unseen hold-out set • Packaging a reproducible solution (Python 3.x, scikit-learn / PyTorch / TensorFlow, Jupyter notebook or .py scripts plus ) so I can rerun the pipeline on fresh data Acceptance criteria 1. End-to-end code executes without manual tweaks on my machine. 2. Final report concisely explains preprocessing choices, model selection rationale and metric results. 3. Trained model and preprocessing objects are saved so I can deploy them in a RE...

...to strip away elements that might provoke irrational responses while keeping the surrounding media unchanged. Here’s what I need you to deliver: • A working browser-based solution (extension, local proxy, or another approach you propose) that processes both static images and streaming video in real time. • Reliable detection of people and animals using modern computer-vision tools (e.g., TensorFlow, OpenCV, YOLO, or alternatives) and seamless substitution with a non-identifying silhouette or blurred overlay. • A simple toggle UI so users can turn the filter on or off without reloading the page. • Clear build/run instructions and concise technical documentation so I can install, test, and demo the concept easily on the latest versions of Chrome a...

...(Jupyter notebook or .py scripts) plus a brief README describing setup, retraining, and inference steps. • Optional but appreciated: a lightweight way to serve the model (e.g., FastAPI endpoint or batch script) so it can slot straight into production. I’ll provide the dataset and any domain context you need right after kickoff. If you have experience with pandas, NumPy, scikit-learn, statsmodels, TensorFlow/PyTorch, or Prophet, you’ll be right at home. Accuracy, clarity, and reproducibility are more important to me than flashy visuals, but a concise plot or dashboard that helps explain the results would be a bonus. Let me know what modeling approach you’d start with, how long you’ll need to deliver the first working prototype, and any assumptions ...

...cues—hand placement, posture and, ideally, gaze direction—to confirm active usage. Whenever the model judges that the phone is being used, it should trigger an audible or visible alarm on the host machine instantly; no other logging or alert channels are required for this first iteration. I am happy for you to choose your preferred computer-vision stack (e.g. OpenCV, MediaPipe, PyTorch, TensorFlow, ONNX) as long as the end result runs on a typical workstation without specialised hardware. Pre-trained networks are welcome, but please include any fine-tuning scripts so I can reproduce the results. If additional datasets are needed, point me to openly licensed sources or provide clear collection guidelines. Deliverables • Source code with clear setup inst...

...Detailed functional requirements that walk through the end-to-end pipeline: ingestion, preprocessing, labeling guidelines, and model-ready datasets. • Non-functional requirements covering performance targets (latency, accuracy, throughput), scalability, and security. • A modeling strategy outline suggesting suitable computer-vision approaches, necessary libraries or frameworks (e.g., PyTorch, TensorFlow, OpenCV), and how evaluation metrics like precision, recall, and F1 will be tracked. • Integration points with existing databases or APIs, plus a basic architecture diagram that ties components together. • A phased timeline with milestones, risk considerations, and a resource estimate so stakeholders can plan staffing and budget down the road. Deliver ...

...LSTMs, or classic scikit-learn algorithms), and any advanced techniques—transfer learning, data augmentation, hybrid architectures, etc.—that would let me demonstrate the novelty experimentally. Nothing is set in stone regarding domain, data type, or application area, so feel free to be creative—just keep the technical scope reasonable for one researcher with typical resources (Python, PyTorch/TensorFlow). Acceptance criteria 1. Each topic must reference at least one recent paper or benchmark it seeks to improve or re-direct. 2. The proposed methods should be reproducible with publicly available datasets or clearly point to open repositories. 3. Novelty statements must be specific enough that I can lift them directly into a “contribution” s...

...datasets to clean, preprocess, and engineer features. Collaborate with cross-functional teams to integrate AI models into production systems. Lead the evaluation, tuning, and optimization of machine learning models for performance and accuracy. Mentor junior engineers and assist with code reviews and best practices. Skills & Qualifications: Proven expertise in machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. Deep learning experience with neural networks (CNNs, RNNs, transformers, etc.) and advanced AI models. Strong background in Python programming, data manipulation (NumPy, pandas), and algorithms. Experience in deploying models at scale using tools like Docker, Kubernetes, AWS, or GCP. Solid understanding of statistics, linear algebra, and calculu...

**Project Title:** Source Detection using Human Behaviour Dynamics using Mach...a model also novelty is must **Scope of Work:** * Dataset preprocessing and exploration * Model development using ML/DL techniques * Training and testing the models * Performance evaluation (Accuracy, Precision, Recall, Confusion Matrix) * Comparison of different models * Clear documentation of the workflow **Preferred Tech Stack:** * Python * Machine Learning / Deep Learning models * TensorFlow / PyTorch / OpenCV * Data visualization libraries **Deliverables:** * Complete source code * Trained model * Results and performance comparison * Brief documentation of the methodology **Additional Notes:** If you have suggestions for improving the model or methodology, feel free to include them in your...

...tempo and key. On top of that, the whole site needs a polish pass: tighter UI visuals, faster page loading, and the elimination of a handful of known bugs that occasionally break the player or freeze the waveform display. You’ll receive the full codebase (front-end, back-end, and the existing transition logic) along with sample track data so you can test locally. I’m open to any AI stack—TensorFlow, PyTorch, or whatever framework you feel will get the best results—as long as the final experience feels flawless to the end user. Deliverables 1. Refactored autopilot module that uses AI/ML to analyse BPM, key, and energy to pick the next song, cue it perfectly, and apply beat-synced effects. 2. Updated UI with cleaner layout and responsive styling acr...

Hi , I came across your profile and loved your Flutter + AR/AI work! We are building a premium AI fashion & lifestyle app (virtual try-on, beauty, eyewear) in Pune, and looking for experienced developers (not newbies). Could you share your latest portfolio or past projects (especially ARCore, TensorFlow Lite, or fashion/AI apps)? Also, if you’re available for a 4-5 week MVP project, let’s chat. Thanks! Founder, LumiZen App

I need a ...exactly how lightweight the solution is. Acceptance criteria 1. Latency from spoken phrase to callback ≤ 250 ms on both targets. 2. ≥ 95 % wake-up rate in moderate background noise (office chatter, music at low volume). 3. ≤ 2 false activations per hour of continuous speech. 4. Complete build steps and source so I can reproduce the binary from scratch. You are free to use tools like TensorFlow Lite Micro, Porcupine, Picovoice DIY, or a custom DSP pipeline—as long as licensing permits commercial use. I am happy to provide extra voice recordings to help you fine-tune. If you’ve shipped similar models before, let me know; a quick video demo on actual hardware will fast-track selection. data collection and everything should be done solely by t...

...audit trails – Downloadable PDF sanction letters and system logs that satisfy bank compliance requirements. - All things as per referred website Tech stack guidance (flexible if you can justify alternatives): React or Vue front end, Node/Express or Django back end, PostgreSQL, Docker for containerisation, and AWS or GCP for deployment. AI components can leverage Python, scikit-learn, TensorFlow, or a third-party credit-risk API if it accelerates delivery. Chatbot may sit on Dialogflow or Microsoft Bot Framework; email/voice could integrate later through SendGrid and Twilio. Acceptance criteria 1. Demo environment accessible for all four user roles with dummy data. 2. AI risk score aligns within ±5 % of a provided sample model on the same dataset. 3. C...

I’m building a complete AI-driven platform that trades listed option...Acceptance criteria • Latency from data receipt to order placement ≤ 250 ms on my VPS. • Back-test must show at least 500 trades with Sharpe > 1 after fees/slippage on the last two years of SPX options data. • All trades adhere to pre-set max loss and margin rules; violations trigger an alert and auto-shutdown. I’m flexible on tech stack, though Python with libraries like pandas, scikit-learn, TensorFlow and a broker API (IBKR, Tradier, Zerodha, etc.) fits my current environment. Propose your preferred tools if they achieve the same outcome. If you have proven experience building AI or quant systems for options, let’s discuss how you would architect this and timelines ...

...tutoring or technical platform troubleshooting, I specifically need someone who can step in, finish the required tasks, and submit clean, well-commented solutions on my behalf. This will be an ongoing project and will span an year. Typical exercises range from data preprocessing and feature engineering to training and evaluating models with libraries such as Python, NumPy, pandas, scikit-learn, TensorFlow or PyTorch. Code must run flawlessly in the course’s Jupyter-based environment and meet the rubric laid out in each brief (accuracy thresholds, narrative explanations, and any visualisations the instructors request). What I’d like to see in your offer is a short note about your relevant experience—previous AI/ML coursework you’ve completed, projects y...

...task is to identify and download a suitable, well-labelled dataset from Kaggle. Feel free to compare a few candidates, but the final choice should give good class balance and enough samples per disease category. Once the data is in place, walk through exploratory data analysis, preprocessing, and augmentation inside a Jupyter notebook. From there, build and tune a convolutional neural network (TensorFlow / Keras or PyTorch are both fine) and report the usual metrics plus a confusion matrix so I can judge class-wise performance. When the model is satisfactory, save it and wrap inference in a clean Streamlit app where a user uploads a single image and instantly sees the predicted disease name along with a confidence score. Additionally, integrate AI-based recommendations (e.g., t...

...Voice-command execution to let them control key in-app actions hands-free. • Language identification that automatically detects whether the incoming audio or text is Amharic or English before processing. The finished app should run smoothly on Android phones and as a responsive web application; a shared code-base or robust API that feeds both fronts is ideal. I’m open to your preferred stack—TensorFlow, PyTorch, Whisper, or any other modern NLP/ASR tools—as long as model performance stays fast and the architecture can be retrained with additional corpora later. Deliverables 1. Source code with clear build instructions. 2. A runnable Android APK and a hosted web demo. 3. Documentation covering model training steps, data requirements, and how to mod...

I want to build a small, self-contained charging station that wakes up only when it “sees” a bottle and a can. The core will be an Arduino (any recent 32-bit board is fine) tied to a solar panel and battery pack. A lightweight AI vision module or camera running something like TensorFlow Lite or OpenCV should continuously—or on a duty-cycled basis—look for bottles. The moment a bottle is detected, the system must move straight into the charging routine without waiting for external confirmation; no alerts, no logging, just automatic activation. What I need from you • Complete Arduino firmware that integrates the vision trigger with the charge-controller logic. • A schematic / wiring diagram showing how the camera, solar panel, charge controller, ...

...timestamp; frame-level annotation may still be required for optimal accuracy. Scope • Design and train a deep neural network—CNN, transformer, or hybrid model—that detects all three defect categories directly from video streams. • Implement preprocessing (frame extraction, augmentation, ROI isolation) and post-processing (tracking, alert generation) in Python using libraries such as PyTorch/TensorFlow and OpenCV. • Optimise for inference on an on-premise GPU; latency under 200 ms per frame is the target. • Provide clear metrics: precision, recall, F1, and confusion matrices on a held-out validation set. • Package the final solution with a lightweight REST or gRPC endpoint so the in-house engineering team can call it from our SCADA s...

...2 pipeline that must reliably spot nuts and bolts in a live camera feed and publish their positions to the rest of my stack in real time. Your job is to create the complete vision-detection module—from model training or fine-tuning through to a clean ROS 2 node that subscribes to an image topic and spits out the detected objects with bounding boxes (or masks) and a confidence score. OpenCV, TensorFlow/PyTorch and any of the common ROS 2 image-transport plugins are all fine as long as the final node runs on Humble and stays GPU-agnostic (CUDA acceleration is a bonus, not a requirement). I already have a test rig with a standard USB camera; if you need specific calibration images I can capture them for you. Please deliver: • Source code for the detection model and ROS ...

...browser or local environment. Explanations will be detailed and actionable, so the platform can be maintained independently without guesswork. Functionality is non-negotiable, with every component—from AI modules to smart contract execution—fully operational and integrated. This project is ideal for a technical collaborator who is experienced in AI/ML integration using Python frameworks such as TensorFlow or PyTorch, proficient in blockchain development and smart contracts, and skilled in full-stack web development with JavaScript and Python. Familiarity with responsive design, conditional logic, and building scalable, secure applications is essential. The goal is not just to build a functioning product, but to create a robust, maintainable, and brand-aligned AI + bl...

More details: Which deep learning framework do you prefer for this project? TensorFlow Do you have a preferred dataset for brain MRI image segmentation? Please use a publicly available dataset Which style of output visualization do you prefer? 2D slices with segmentation overlay

...logos, motion graphics, illustrations Adobe Photoshop / Illustrator SEO articles, landing pages, marketing copy Digital Marketing & Social Media SEO, SEM, conversion optimization Paid ads, audience targeting, analytics Video Production & Editing Promotional and social videos Premiere Pro / After Effects AI & Machine Learning Integration Chatbots, NLP tasks, model fine-tuning Python / TensorFlow / PyTorch Cloud & DevOps Infrastructure AWS / Azure / GCP CI/CD pipelines, Docker, Kubernetes Cybersecurity & Security Audits What You Should Include in Your Bid Relevant experience with one or more of the above skills Portfolio or links to previous work Estimated timeline & deliverables Hourly rate or fixed price quote...

...illustrations Adobe Photoshop / Illustrator SEO articles, landing pages, marketing copy Technical documentation Digital Marketing & Social Media SEO, SEM, conversion optimization Paid ads, audience targeting, analytics Video Production & Editing Promotional and social videos Premiere Pro / After Effects AI & Machine Learning Integration Chatbots, NLP tasks, model fine-tuning Python / TensorFlow / PyTorch Cloud & DevOps Infrastructure AWS / Azure / GCP CI/CD pipelines, Docker, Kubernetes Cybersecurity & Security Audits What You Should Include in Your Bid Relevant experience with one or more of the above skills Portfolio or links to previous work Estimated timeline & deliverables Hourly rate or fixed price quote ...

...depth of knowledge across Python, Scala and SQL. Our stack centres on Azure and Databricks, so practical insight into large-scale Spark/PySpark jobs, data-model design, ETL orchestration and cloud performance tuning is essential. Candidates frequently discuss streaming, optimisation strategies and modern AI/ML add-ons, so any hands-on exposure to libraries such as PyTorch, NumPy, SciPy or TensorFlow will help you challenge them at the right level, though it is not mandatory. Availability is limited to two focused hours per weekday; I will share the interview schedule at least 24 hours in advance. After each session you will file a concise written assessment noting technical strengths, gaps and a simple hire/no-hire recommendation. Consistency and quick turnaround are key. ...