Tensorflow jobs

...training process and inference workflow * Recommendations for scaling the model to larger areas of Jharkhand Ideal Candidate Please apply if you have demonstrated experience in: * Remote sensing and satellite image processing * Computer vision / deep learning * Tree detection and crown segmentation * Tree species classification * GIS / GeoPandas / Rasterio / Google Earth Engine * Python, PyTorch/TensorFlow * Models such as DeepForest, YOLO, Mask R-CNN, U-Net, SAM or similar * Multispectral/hyperspectral imagery * Geospatial AI Experience with forest/tree species mapping is highly preferred....

...flexible enough to extend into stocks later, that’s a plus but not required right now. • Actionable outputs are essential. Whether through a lightweight dashboard, e-mail/SMS alerts, or direct API calls back into my broker, I need clear “risk heat” indicators and recommended de-risking steps (reduce size, tighten stops, hedge, etc.). I’m comfortable with Python, so a solution built around TensorFlow, PyTorch, or similar libraries will slot easily into my workflow, but I’m open to other stacks if you can justify the benefit. Just make sure any data feeds you rely on (price, order-book depth, news sentiment) are either free or come with clear cost estimates. Deliverables: • A working AI model that ingests live forex and crypto data an...

...that runs entirely offline. The workflow is straightforward: 1. I open the program, browse my local folders, and pick any .mp4 file. 2. Before the scan starts, I set the frame-sampling rate—this could be every frame, every nth frame, or even a custom decimal rate such as 2.5 fps. 3. The app then performs object detection on those chosen frames. I do not mind which framework you use (YOLO, TensorFlow, OpenCV, ONNX, etc.) as long as everything is bundled so the tool works without an internet connection. 4. When the run finishes, the program produces a plain .txt sheet: one line per analysed frame containing the timestamp and the symbols / class names it detected. No other file formats are required. Deliverables • Stand-alone Windows executable (installer or...

...idea of scope, the raw scenes are already orthorectified and radiometrically corrected. What I’m missing is the machine-learning layer that will take two (or more) aligned images, learn the patterns of normal variability, and then output clear, georeferenced change masks and summary statistics. Key expectations • Model architecture, training pipeline, and inference script packaged in Python (TensorFlow, PyTorch, or another proven deep-learning framework). • Clear instructions for reproducing results on my own machine, including environment file and command-line steps. • Evaluation report showing accuracy metrics on a held-out test set I will provide after initial proof of concept. If you have experience with satellite imagery, convolutional networks...

...performers among staff. • Adjust roles or permissions instantly without digging through code. Core deliverables 1. Web or hybrid mobile app for customers, staff, and couriers with a clean ordering workflow. 2. Admin dashboard built with a modern framework (React, Vue, or Angular is fine) plus backend APIs. 3. Integrated AI modules (recommendation system, chatbot) using your preferred stack—TensorFlow, PyTorch, Dialogflow, or similar—as long as setup instructions are provided. 4. Source code in a private Git repo, environment setup guide, and short video walk-through so I can test everything myself. I’m ready to move quickly once I see a concise plan and timeline. Let me know which stack you’d propose and any previous projects that show...

...feature set yet, so I’m open to your recommendations on whether to prioritise real-time alerts, historical data analytics, or seamless links to third-party platforms. What matters most is accuracy across various lighting and weather conditions and a design that lets me scale from a single roadside camera to a multi-site installation later on. If you have previous deployments on OpenCV, YOLO, TensorFlow, or similar computer-vision stacks, let me see them. Latency benchmarks or side-by-side comparisons with commercial services are a plus. Deliverables • End-to-end ANPR software (source code + install docs) • Configuration guide for cameras and optimal capture settings • REST or WebSocket interface for external systems • Brief report outlining m...

...performs on both real and fabricated pieces. The workflow I have in mind combines three parts: • an automated pipeline that scrapes or ingests fresh articles, cleans the text, and stores it in a structured format; • a robust NLP model—think transformer-based architecture fine-tuned on a well-curated fake-vs-real news dataset—trained and evaluated in Python with libraries such as PyTorch, TensorFlow or Scikit-learn; • a lightweight interface (REST API or simple web demo) that returns the probability of falseness plus the key features that influenced the decision for transparency. Deliverables • End-to-end codebase with clear instructions ( / , README) • Trained model weights and scripts to reproduce training and evaluation • ...

...of the app is to monitor stock levels in real time, predict restock points, and surface actionable insights that reduce overstock and outages—all powered by machine learning models that learn from each merchant’s sales history. Scope of this initial milestone • Deep-dive workshops (remote) to capture user journeys and data sources • Technical exploration of the AI stack you recommend (e.g., TensorFlow Lite, Core ML, on-device vs cloud inference) • Clickable wireframes for both iOS and Android that demonstrate key flows • A written product brief with estimates, architecture outline, and phased rollout plan Acceptance criteria – Every workshop outcome and design decision documented in a shareable report – Lo-fi wireframes signed...

... * Develop, deploy, and monitor machine learning models. * Clean and organise messy data from different sources. * Translate business needs into practical data or ML solutions. * Document systems, processes, and technical decisions. * Work independently and collaborate in English and Spanish. Requirements * Strong Python, pandas, NumPy, and scikit-learn skills. * Experience with PyTorch or TensorFlow. * Advanced SQL knowledge. * Experience with Airflow, Prefect, Dagster, or similar tools. * Knowledge of at least one cloud platform. * Fluent spoken and written English and Spanish. Experience with Spark, dbt, Docker, MLOps, LLMs, or an early-stage startup is helpful but not required. To apply, send your CV and a short description of something you built, including the problem, y...

...performs on both real and fabricated pieces. The workflow I have in mind combines three parts: • an automated pipeline that scrapes or ingests fresh articles, cleans the text, and stores it in a structured format; • a robust NLP model—think transformer-based architecture fine-tuned on a well-curated fake-vs-real news dataset—trained and evaluated in Python with libraries such as PyTorch, TensorFlow or Scikit-learn; • a lightweight interface (REST API or simple web demo) that returns the probability of falseness plus the key features that influenced the decision for transparency. Deliverables • End-to-end codebase with clear instructions ( / , README) • Trained model weights and scripts to reproduce training and evaluation • ...

...may follow later, phase one focuses exclusively on perfecting these recommendations. Technical expectations • End-to-end platform or plug-in capable of integrating with common stacks (Shopify, WooCommerce, custom React/Node, etc.). • Scalable data pipeline—batch and real-time—to capture events, train models, and serve predictions with low latency. • Model layer leveraging proven libraries (TensorFlow, PyTorch, or similar) and techniques such as collaborative filtering and deep learning for cold-start mitigation. • Admin dashboard for A/B testing, rule overrides, and performance analytics (CTR, AOV lift, revenue attribution). Deliverables 1. Deployed, production-ready storefront or extension with live product-suggestion widgets. 2. Source code...

...Your mission is to extract the signals that drive sell-through, forecast demand at SKU and store level, and surface actionable insights for merchandising and marketing. I expect you to handle everything from data ingestion and cleaning through to model deployment, with clear documentation of assumptions and feature engineering steps. You may use Python (pandas, scikit-learn, XGBoost, Prophet, TensorFlow, or similar), SQL for warehousing, and NLP libraries such as spaCy or transformers for the text components. If you prefer R or another stack, I’m open as long as the final model meets the accuracy and interpretability goals. Deliverables • Cleaned and well-structured datasets ready for modelling • Reproducible notebooks / scripts showing EDA, feature engineer...

...supply their own slide deck or lab guides and then deliver the material confidently—either live online or at a client site. When you apply, focus on your experience. Tell me which of the three domains you teach most often, the typical audience size you handle, and any notable tools or frameworks you specialise in (for example, Git & CI pipelines in software dev, OWASP testing in cybersecurity, or TensorFlow and Pandas for data science). A brief description of a past workshop or bootcamp you’ve led is enough; no lengthy proposals are required at this stage. Once we decide to work together, the first deliverable will be a session outline that lists learning objectives, timing and required software. After I approve it, we’ll lock in dates and move on to full ...

...structure the solution with easy extensibility in mind. The workflow I have in mind is straightforward: drop a folder (or send an API call) and receive a concise report that flags any file whose colours drift beyond an acceptable Delta-E or similar metric, along with a summary CSV/JSON and an optional visual overlay for quick human review. Popular libraries such as Python, OpenCV, Pillow or TensorFlow are welcome if they speed development, but I am open to alternative stacks provided setup remains frictionless on Windows and Linux. Deliverables • Source code or notebook implementing the evaluator • Clear installation and run instructions • Sample report generated from a small test set I will provide • Brief README explaining how thresholds can be twe...

...engine that understands natural language, replies with context-aware answers, and can be integrated into whichever channels we decide fit best once discovery is complete (website, mobile, or social). Here is how I picture the engagement: • Discovery & scoping session so we agree on the bot’s personality, knowledge boundaries, and technical stack. • Model selection or fine-tuning (OpenAI, Rasa, TensorFlow, etc.) with clear explanations of trade-offs. • Development of the dialogue flow, fallback logic, and analytics hooks. • Clean API or SDK to drop the bot into my chosen front-end. • A lightweight admin interface so I can update intents, responses, and view usage stats without touching code. • Deployment walk-through and hand-off...

...cross-disciplinary “general AI” scope rather than being limited to NLP, Computer Vision, or Reinforcement Learning alone. I need a collaborator who can help shape the research question, set up experiments, analyse results, and co-author the manuscript to publication standard. Key phases • Literature mapping to identify a novel research gap • Experimental design and implementation (using Python, PyTorch / TensorFlow, or similarly capable stacks) • Rigorous evaluation with reproducible code and well-documented datasets • Full paper write-up—including abstract, methodology, results, discussion, and formatted references—ready for submission Acceptance criteria • Manuscript of roughly 8–10 pages (IEEE two-column or com...

...and preserves an appropriate tone of voice. You’ll work with my existing dialogue data (plus any open-source corpora you recommend) to create a model that can: • Understand multi-turn context and user intent • Respond naturally in English without hallucinating facts • Respect soft constraints I’ll provide on length, formality, and persona Typical tools in this space—Python, PyTorch or TensorFlow, Hugging Face Transformers, and popular evaluation libraries—fit well here, but I’m flexible if you have a stronger stack. Deliverables 1. Pre-processed, reproducible dataset and accompanying scripts 2. Fine-tuned model checkpoints with clear versioning 3. Inference wrapper (REST API or lightweight microservice) that I can drop ...

...data or connect a live source. When I input specific criteria (e.g., a name or location), the app should retrieve and display the requested information. It should also allow me to view dashboards that translate findings into plain-language insights and exportable reports. Accuracy, explainability, and easy retraining on fresh data are non-negotiable. If you’re comfortable building with Python, TensorFlow or similar frameworks, integrating a visual layer in React or Flutter, and delivering clean documentation so future analysts can tweak the pipeline, let’s talk....

...The system must automatically cut and splice raw footage, apply colour-accurate corrections, and drop in context-aware special effects, then go a step further by generating entirely new video clips and still images from text or style prompts. Here’s what I want the tool to handle for me: • AI video editing • AI video generation • AI image generation Preferred tech includes PyTorch or TensorFlow for the modelling work, diffusion or transformer architectures for generation, and FFmpeg for final rendering, yet I’m open to any stack you can justify that still lets me run the solution locally or on my own cloud instance. Deliverables 1. A script or lightweight application (CLI or basic GUI) that performs the three tasks above. 2. Fully documented ...

...proof-of-concept that helps farmers monitor crop health and estimate likely yields. My immediate focus is on two functions: • Disease detection – flag visible leaf symptoms from the images I already have. • Yield prediction – provide a first-pass estimate based on those same images. Only images of crops are available right now, so the solution should rely on computer-vision techniques (Python with TensorFlow or PyTorch is fine). I need: 1. A well-commented notebook or script that trains and tests both models on my dataset. 2. Clear instructions for retraining with new images. 3. Basic performance metrics (accuracy / F1 or similar) on a held-out sample. 4. A short README outlining next-step recommendations for adding soil, weather, or sensor data a...

...similar package that I can sideload Acceptance criteria 1. Voice/text command executed within two seconds on a mid-range Android phone, offline. 2. At least 10 demo commands covering app launch, navigation, typing, and a simple code snippet insertion. 3. Source code, build instructions, and a brief video showing the assistant in action. If you have experience with on-device NLP (e.g., TensorFlow Lite, , Rasa, or similar) and Android automation APIs like Accessibility Service, I’d love to see your approach and previous work....

...of real penmanship. What I need from you is an end-to-end solution—from model design to final PDF export—that pairs visual authenticity with solid print fidelity. High-resolution (300 dpi, CMYK-friendly) output is non-negotiable; the pages have to survive a close look after coming off an office laser printer with no tell-tale artifacts. Deliverables • A handwriting synthesis engine (Python, TensorFlow/PyTorch or comparable stack) that ingests text and returns vector or high-resolution PDF files • Style library covering the three handwriting families, built for easy expansion • Configuration interface for all font customisation controls • Documentation plus a short demo video showing the workflow end to end Acceptance criteria Given a 2...

...goals. I do not need every biometric detail at launch; intermediate-level customization that factors in baseline fitness and objectives is perfect for version 1. Here’s what I need you to put in place: • A responsive front-end for iOS/Android and a matching web interface. The layout should feel native on phones yet remain fully functional on desktop screens. • A recommendation engine (Python, TensorFlow or similar is fine) that auto-generates daily or weekly plans for strength and yoga, adjusting intensity as users log progress. • Secure user accounts with cloud data storage so progress, preferences and goals sync seamlessly between devices. • Admin tools that let me upload new exercise videos, tweak difficulty parameters and view basic analytics...

...should test the entrepreneur’s concept against market demand, cost structures and funding criteria so the final proposal is both realistic and attractive to evaluators. My vision is a cloud-based solution with a simple interface: the user enters location and concept, presses “Generate”, and receives a ready-to-submit application plus an explanatory report. Python, machine-learning libraries (TensorFlow, PyTorch), NLP techniques for grant language, and a lightweight GIS component will likely be needed, but I am open to your preferred stack as long as accuracy and speed remain high. Payment will follow a subscription model of 300 RON per month for five years, aligning our interests over the long term while keeping the service affordable for small businesses. If...

I need an Android application that links to an external camera mounted inside a beehive, analyses the live feed with colour-based recognition and instantly warns me whenever the queen comes into or drops out of view. The workflow is straightforward: the app receives the video stream from the external camera, processes each frame locally (OpenCV or TensorFlow Lite are fine), isolates the queen by the distinctive colour mark on her thorax, then triggers real-time alerts through push notifications and an on-screen banner. A simple dashboard should show the live video with an overlay around the detected queen and log each event with a timestamp so I can review activity later. Deliverables • Full Android Studio project (Java or Kotlin) with clean, documented code • Trai...

...what matters most to me: • A well-trained object-detection model tailored to photographic input (no illustrations or charts in the mix). • Consistently higher precision and recall than my existing baseline; lowering false positives is more valuable than sheer speed. • A self-contained script (Python preferred) that can run headless on Linux, making use of familiar libraries such as PyTorch, TensorFlow, or OpenCV—whatever you feel will maximise accuracy. • A concise README that explains installation, inference commands, and how to tweak confidence thresholds. I will supply an initial, labelled photo set for training and a separate, hidden validation set for final evaluation. If your model meets or exceeds the benchmark metrics on that blind test, ...

I have an operational ERP that runs on a SQL back-end. I now want to ...with back-testing. 2. Natural-language queries (“Show me yesterday’s top five items”, “Predict next month’s purchase needs”) return results in under five seconds. 3. Scheduled reports (PDF or interactive dashboard) auto-generate and email daily without intervention. 4. Push notifications reach my Android phone instantly when predefined thresholds are met. Preferred stack is Python with TensorFlow/PyTorch and a lightweight API (FastAPI, Flask, or similar), but I’m open to alternatives if they get the job done quickly and reliably. All source code, model artefacts, and setup scripts should be delivered so we can host everything on our own server afterward. Logic ...

...awareness: fetch depth or stereo data (or infer depth with AI) so the user is warned about hazards at cane-length distance or overhead. • Extensible add-ons: hooks for voice commands, emergency SOS, text reading, object recognition, or any future computer-vision module. I already have access to sample hardware (camera-equipped glasses and a tactile band), so you can prototype quickly with OpenCV, TensorFlow Lite, PyTorch Mobile or a stack you prefer. What I really need is the architecture, clean code, and demonstrable logic that meld everything into a smooth UX. Deliverables 1. Source code with clear documentation and build/run instructions 2. A runnable demo (APK, executable, or Web build) that proves indoor & outdoor navigation on my test routes 3. API or mod...

...add-ons such as metadata scraping or playlist building can be left as optional notes rather than core components. Here is what I expect from the engagement: • A high-level and component-level architecture diagram showing how audio is ingested, fingerprinted, matched against a reference database, and the result delivered with sub-second latency. • Technology recommendations (e.g., Python, C++, TensorFlow/PyTorch models, audio fingerprint libraries like Chromaprint or ACRCloud SDKs, plus cloud services such as AWS Kinesis, Lambda, DynamoDB, or their GCP/Azure equivalents). • Scaling and fault-tolerance strategy for thousands of concurrent radio channels, including container orchestration (Kubernetes/EKS/GKE) and message queues (Kafka or Pub/Sub). • Laten...

...and optimize code for performance and reliability Implement new features to expand functionality or bypass current limitations Test the software thoroughly using provided test accounts Deploy the software to a live or staging environment Provide clear documentation of changes made What We're Looking For: Strong experience with Python (3+ years) Experience working with AI/ML libraries (TensorFlow, PyTorch, Hugging Face, etc.) Proven ability to debug and fix complex codebases Familiarity with GitHub workflows (branching, pull requests, merging) Experience deploying Python applications (Docker, AWS, GCP, or similar) Ability to test software and verify functionality before deployment Strong problem-solving and communication skills How It Works: We provide access to...

...and optimize code for performance and reliability Implement new features to expand functionality or bypass current limitations Test the software thoroughly using provided test accounts Deploy the software to a live or staging environment Provide clear documentation of changes made What We're Looking For: Strong experience with Python (3+ years) Experience working with AI/ML libraries (TensorFlow, PyTorch, Hugging Face, etc.) Proven ability to debug and fix complex codebases Familiarity with GitHub workflows (branching, pull requests, merging) Experience deploying Python applications (Docker, AWS, GCP, or similar) Ability to test software and verify functionality before deployment Strong problem-solving and communication skills How It Works: We provide access to...

...gallery. The interface must feel polished and business-grade—clean lines, subtle animations, dark/light theme toggle—so designers, influencers, and everyday users alike sense quality from the first screen. While I’m happy for you to choose the stack that best suits the task (Swift/Kotlin, Flutter, React Native, etc.), the core image-processing model should run on-device for speed and privacy. TensorFlow Lite, Core ML, ONNX, or a similarly lightweight framework is fine as long as the final APK/IPA stays lean and the results remain sharp at up to 4K resolution. Key expectations • Seamless import from camera roll, live camera view, or drag-and-drop share sheet • Automatic background removal with editable mask overlay • Library of preset backgro...

...deployment—while keeping future scalability in mind. The work involves natural-language processing, machine learning, and solid software-engineering practices. Expect to design a pipeline that cleans and enriches the text, applies state-of-the-art transformers or other suitable models, and exposes the results through a clean API my existing back-end can call in real time. Python, PyTorch or TensorFlow, Hugging Face, and containerisation (Docker/Kubernetes) should feel second nature; if you prefer equivalent tools, I’m open, provided maintainability stays high. Because the insights will feed directly into our live support dashboard, accuracy and low latency are critical. A well-structured test suite, thorough documentation, and CI/CD hooks will be part of the hand-of...

...American Sign Language in real time, turns each recognised sign into clear written text, and then voices that text through natural-sounding speech. The end goal is an easy-to-use educational tool that helps people who are deaf and non-verbal practise everyday communication with hearing users directly from their browser. Scope of work • Build or fine-tune a computer-vision model (e.g., MediaPipe, TensorFlow, PyTorch, or similar) to detect and classify ASL signs from a webcam stream. • Pipe the recognised signs to a text layer, then feed that text into a speech-synthesis engine so the conversation flows naturally. • Develop a responsive web interface where users can sign into the camera, read the live transcript, and hear the spoken output instantly. •...

...performance on real-world data. The work revolves around text data only. All preprocessing pipelines are in place; the immediate need is to refine the model architecture, tune hyper-parameters, apply efficient training strategies (mixed precision, gradient accumulation, distributed training if helpful), and benchmark the final checkpoints. Familiarity with Hugging Face Transformers, PyTorch or TensorFlow, Weights & Biases, and modern optimization techniques such as learning-rate schedulers, early stopping, and model pruning/quantization will be essential. Deliverables • Fully trained, optimized model files (with version tagging) • Reproducible training scripts/notebooks and environment files • Evaluation report covering metrics, confusion matrices, and ...

...Model development: an unsupervised architecture such as auto-encoder, variational auto-encoder, deep clustering, or another approach you can justify for anomaly detection. • Evaluation: quantitative metrics (reconstruction error distributions, AUC, or similar) plus a concise report explaining thresholds and decision logic. • Deliverables: clean, well-commented Python code (ideally PyTorch or TensorFlow/Keras), reproducible environment files, and a short README so I can retrain or fine-tune later. I will supply a representative sample to start; please keep the design modular so it scales once the full dataset arrives. Let me know any additional dependencies you anticipate, along with an outline timeline for data exploration, model iteration, and final validation....

I have a batch of jewellery photos that need an instant lift so they look irresistible online. The sole objective is to increase their visual appeal—think sharper sparkle, true-to-life colour, spotless backgrounds and an overall premium look. You are free to lean on any AI-driven workflow you trust—image enhancement tools such as Topaz Photo AI, Luminar, custom TensorFlow/PyTorch models, or even subtle style-transfer tricks—as long as the final images look clean, consistent and ready for web and catalogue use. Turnaround is critical; I need the finished, high-resolution JPG/PNG files as soon as possible. Please include a brief outline of your process, the number of images you can handle in one pass, and a short before/after sample so I can verify quality.

...with platform-specific aspect ratios • Auto-captions and animated subtitles in multiple fonts and styles • Voice and audio enhancement that removes silence and filler words • Template library with AI-suggested effects, transitions and color looks • In-app subscription system (monthly / yearly) with Google Play Billing • Cloud or on-device processing pipeline using FFmpeg, MediaCodec, TensorFlow Lite (or a stack you recommend) • Admin dashboard for user management, usage analytics and churn reporting I’m looking for someone who has already solved similar challenges—ideally you have shipped Android apps that mix FFmpeg with custom ML models, manage subscriptions securely, and handle video workloads at scale. When you reply, ...

...categorisation; expenses can be ignored for now. Accuracy matters more than speed, but the system must still process a typical daily batch (≈10 000 lines) in minutes, not hours. You will receive several months of historically tagged transactions to train and validate the model. I am comfortable with Python and would like well-commented scripts that rely on common libraries such as pandas, scikit-learn, TensorFlow or PyTorch, plus a concise README that lets me reproduce your results on my own machine. Deliverables: • Clean, runnable code (model training + inference) • Trained model weights or checkpoint • README with setup, execution steps, and metrics achieved on the validation set Acceptance criteria: F1-score ≥ 0.90 on the supplied hold-ou...

...new set of market-trend predictions. • Output format: a concise JSON or CSV report with price direction, confidence score and any key indicators you derive. I am comfortable with Python and would prefer to host the solution on a lightweight cloud instance (AWS or similar), but suggest alternatives if they shorten turnaround time. Please include a short note on the framework you plan to use—TensorFlow, PyTorch, or a lighter ML library are all fine as long as they support scheduled retraining. Acceptance criteria 1. An executable script or container that fetches current price data, processes it, and stores the fresh prediction daily. 2. A README that explains setup, scheduling and any environment variables. 3. A quick demo run showing one full cycle from da...

...precision: minimise artifacts and better capture subtle tone shifts so the generated speech feels indistinguishable from the source voice. • Multilingual capability, emotion-aware output, and a seamless path for users to upload short samples and train their own custom voices. • Efficient inference that scales—any enhancements must keep latency low and integrate cleanly with the existing Python/TensorFlow back-end and React front-end. Deliverables 1. Refined cloning model (code + trained checkpoints) meeting measurable quality gains on sample tests. 2. Integrated support for multiple languages, emotion detection, and custom voice training within the current UI/API. 3. Clear setup notes and a short report explaining architecture changes so I can maintain an...

...entirely in Japanese through live online sessions for our platform intellipaat. The audience already has basic programming knowledge, so we will dive quickly into model design, best-practice workflows, and real-world project implementation rather than introductory theory. You should be comfortable switching between conceptual explanations and hands-on coding demonstrations (Python, Jupyter, TensorFlow/PyTorch, scikit-learn). Clear, native-quality Japanese communication is essential; all slides, code comments, and Q&A will be in Japanese. To keep the engagement high I expect: • A concise syllabus that shows how you will sequence ML, DL, and NLP topics over the proposed calendar • Total duration of the course will be 40 hours • Practical assignments after ...

...grows and as future modules—such as chatbots or recommendation engines—come online. Here’s what I’m expecting from you: • A high-level architecture blueprint showing how each component fits together (APIs, data pipelines, orchestration, security, monitoring). • Clear technology stack recommendations with reasoning—think language choices, cloud services, AI frameworks (e.g., Python, Node.js, TensorFlow, AWS, GCP, Docker, Kubernetes). • Data-flow and integration diagrams capturing how customer queries travel through NLP models, knowledge bases, and analytics layers. • A phased implementation roadmap, broken into practical milestones, so engineering teams can pick it up and start building. • Guidelines for horizontal s...

...model that can take a raw photo—forest, desert, coastline, mountain range, or any other natural scene we decide on—and return the correct label with strong accuracy. Here’s what I need from you: • A well-structured dataset or clear guidance on sourcing and curating one (public sets are fine as long as licensing is respected). • A training workflow in Python using a mainstream framework such as TensorFlow or PyTorch, complete with data-augmentation, fine-tuning, and validation steps. • Trained model weights plus inference code that runs on CPU or GPU with a single command. • A concise README explaining environment setup, training parameters, and how to add new classes later. • Evaluation metrics (precision, recall, confusion matr...

...Automation flows: WhatsApp messaging, transactional and drip email sequences, plus a visual sales-pipeline engine that can be tweaked from an admin dashboard. Tech stack is flexible, but I usually lean toward React (or Flutter) + Node/Express or Django for APIs, PostgreSQL or MongoDB for data, and Twilio/WhatsApp Business APIs for messaging. If you have a better way to make the AI component sing—TensorFlow, OpenAI, LangChain—I’m open. Just explain why. Deliverables 1. Production-ready web app deployed to a cloud host of your choice. 2. iOS & Android builds published to TestFlight / internal track. 3. Integrated CRM with basic data migrated from a CSV I’ll provide. 4. End-to-end automation workflows tested and documented. 5. Admin guide and an...

I am undertaking a full-scale build of an AI-driven music creation platform—think Suno, but entirely my own. T... 5. A short demo playlist showcases each major capability. Timeline & collaboration There is no fixed deadline; quality and completeness outweigh speed. Show me examples of previous AI music or audio-generation work—ideally a live link or working demo—so I can gauge how quickly we can move into production. Tech flexibility is fine—whether you prefer LangChain, Triton, Python, Node, Go, TensorFlow, PyTorch, or proprietary DSP tools—just outline the reasoning behind your stack and how it supports future scale. If you have shipped anything similar, I’d love to hear the details and dive straight into discussion on model choices, ...

...recorded in typical everyday settings, so the model must stay robust whether the user is in a bustling office, walking along a busy street, or standing in a crowded venue. Here’s what I need from you: • An end-to-end speaker-recognition pipeline—data preprocessing, feature extraction, model training, and inference—implemented in Python with a mainstream deep-learning stack such as PyTorch or TensorFlow. • Noise-handling techniques (e.g., spectral subtraction, data augmentation with synthetic noise) integrated so the final model meets the 95 % identification benchmark on a held-out, noisy test set that we will agree on. • A concise report explaining architecture choices, training parameters, and evaluation results, plus clear instructions f...

...or busy streets. The sole objective is to identify who is speaking; transcription and emotion analysis are outside the scope. I’m open to any modern approach—deep-learning architectures such as ECAPA-TDNN, x-vector, or a custom CNN-RNN hybrid—so long as the final model remains reliable when the signal-to-noise ratio drops. Python is preferred for the pipeline, and frameworks like PyTorch or TensorFlow are perfectly acceptable. Please work with publicly licensable datasets or clearly state any proprietary material you intend to use, and describe your noise-augmentation strategy up front so I can vet it. Deliverables • A trained speaker-recognition model capable of handling noisy audio • A lightweight API or CLI demo that accepts a wav/mp3 file and...

...working feature. Written guides or recorded videos can be added later if you think they’ll reinforce the lessons, but the core delivery method must remain workshop-style. Key areas we must cover • Practical design and scaling of the MLM binary tree structure, including spill-over handling, commission calculations and real-time genealogy visualisation. • Integration of current AI tools (e.g., TensorFlow, PyTorch, OpenAI APIs) to add predictive analytics, chatbot onboarding and fraud detection layers to the platform. The audience is solidly at an intermediate level—they know their way around Git, REST APIs and basic data structures—so you can skip beginner explanations and focus on architecture decisions, optimisation tricks and AI model fine-tunin...

SmartFit is an AI-powered web application designed to help users determine the appropriate clothing size using their camera and body-pose analysis, reducing the uncertainty involved in online clothing purchases. The application uses computer vision and pose estimation to analyze a user's body structure through a live camera feed. It uses TensorFlow MoveNet, which detects 17 body keypoints in real time, such as the shoulders, elbows, hips, knees, and ankles. MoveNet is specifically designed for fast real-time pose estimation, making it suitable for browser-based interactive applications. How SmartFit works User opens the SmartFit application The user accesses the application through a web browser. The camera is activated for body analysis. Body detection The camera captures th...