Strojové učení (ML) Jobs

I need a highly accurate deep-learning model that translates Indian Sign Language (ISL) sentence-level gestures into English sentences in real time. The key outcome is maximum translation accuracy with the lowest possible latency, and a design that remains practical and scalable after hand-off. Key Points: Input: Live video from a camera feed or landmark data from MediaPipe/OpenPose. Output: English word or phrase predictions rendered directly on a simple web page in real time. Platform: Web/Mobile platform deployment. Scope: Deliver a working proof-of-concept with clear, commented code, minimal UI, and easy-to-follow setup instructions so the system can be tested end to end. Model: Transformer-based architecture for sentence-level translation, optimized for real-time inference. Dat...

I’ll hand you a raw CSV (or Excel) containing transactional records and would like it transformed into clear, actionable insights about customer purchase patterns. Here’s what I need: • Clean the dataset—handle missing values, fix data types, remove duplicates, and document any assumptions. • Explore and quantify key purchase-related metrics such as frequency, average basket size, and category preferences. • Highlight notable trends and segments in customer behavior, summarising them in plain language. • Present the findings visually, favouring bar charts for the main comparisons, though you can supplement with Matplotlib or Seaborn line or pie visuals if they help the story. • Compile everything into a concise PDF report or an annotate...

I have a stack of microscopic images of composite materials and need them segmented in ImageJ/Fiji so that the fibre distribution is isolated cleanly from the matrix and any interfacial noise. The end goal is to quantify that distribution for material-science analysis, so pixel-accurate masks and a reproducible workflow are essential. You’ll start from raw TIFFs (bright-field and a few cross-polarised shots). I’d like you to design or adapt a segmentation pipeline in Fiji—thresholding, filtering, maybe some machine-learning plugins if needed—and package it as a macro or script I can run on other datasets. Please annotate each processing step in the code and include a short read-me explaining parameter choices. Deliverables: • Fiji/ImageJ macro or script with ...

I have a complete set of anonymised MRI scans from real patients and I’m ready to turn the findings into a publishable journal article. The paper must focus on diagnosing tumors and rely on solid quantitative analysis—no qualitative discussion sections beyond what is needed for context. Here is what I need: • Literature integration: a concise review positioning our dataset within current tumor-diagnosis research. • Methodology: clear description of preprocessing, segmentation, and statistical approaches applied to the images (e.g., radiomics, machine-learning classifiers, ROC analysis). • Results section: detailed quantitative metrics, tables, and figures that highlight diagnostic accuracy. • Discussion & conclusion: interpretation tied back to t...

I’m building an ASR-driven application that listens to users through the microphone and instantly evaluates how closely their spoken Arabic matches a native reference. At the core, I need Dynamic Time Warping for temporal alignment and a Goodness of Pronunciation (GOP) module to score each phoneme. The interface itself should work in both Arabic and English so learners can switch languages for menus, feedback, and error messages. I already have built most of the logic and mostly just need help making sense of some things. I don't need making an app, just help me with the actual functionality so that it works how I intend it to. Essentially, the users of this project would be children, usually with an Arabic base but lacking in speech or conversation skills. I will have mainl...

Necesito una versión inicial sencilla de una aplicación Android que use la cámara frontal del teléfono colocado en el parabrisas para detectar en tiempo real las patentes de los vehículos que pasan. Cada matrícula reconocida debe consultarse al instante contra mi base de datos propia (puedo facilitar un endpoint REST o un archivo local). Cuando la patente coincida con un registro, la app debe generar una notificación inmediata—visual y/o sonora—para alertar al conductor. No requiero una interfaz compleja: basta una pantalla con la vista previa de la cámara, la última patente leída y un indicador del estado de conexión con la base. Tecnología: soy flexible; puedes emplear ML Kit, OpenALPR u...

I want a basic proof-of-concept model that takes an empty-room photo and returns a furnished version. The same model must handle living-room, bedroom, and office layouts, switching styles on demand. Scope (keep it lean for now): • Prepare or source a small, royalty-free dataset of empty rooms plus matching furnished references. • Train a lightweight model—GAN, diffusion, or another vision transformer is fine—so long as it runs on a single GPU or CPU. • Provide an inference script that accepts a JPEG/PNG and a style flag (living, bedroom, office) and saves the composited result. • Include two or three sample outputs per style to prove the concept. • Package code in a clean repo with a short README covering setup, training parameters, and how to ...

I have a Python-only codebase that needs an intelligent way to pinpoint code bugs automatically. I want a detailed, working prototype that leverages CodeBERT together with TreeBERT (or a comparable pair of transformer models if you can justify the switch) to identify likely faulty lines or functions. Scope of work • Prepare or adapt a suitable dataset of buggy / fixed Python snippets. • Fine-tune or otherwise tailor CodeBERT + TreeBERT for line-level bug localization. • Build an inference pipeline I can run from the command line: given a .py file, it outputs ranked suspicious lines with confidence scores. • Include clear evaluation: at minimum precision, recall, and an F1 score on a held-out test set so I can judge effectiveness. • Document setup, training...

I need a highly accurate deep-learning model that translates Indian Sign Language (ISL) sentence-level gestures into English sentences in realtime. The key outcome is maximum translation accuracy with the lowest possible latency and a design that remains practical and scalable after hand-off. Key Points Input: Live video from a camera feed or landmark data from MediaPipe/OpenPose. Output: English word or phrase predictions rendered directly on a simple web page in realtime. Platform: Web/Mobile platform deployment. Scope: Deliver a working proof-of-concept with clear, commented code, minimal UI, and easy-to-follow setup instructions so the system can be tested end to end. Model: Transformer-based architecture for sentence-level translation, optimized for real-time inference. Data: You ma...

My long-term goal is to roll out a fully fledged recruitment SaaS, but the cornerstone is an AI Talent Matching System. I need a developer who can stay dedicated to the project without strict timing pressure and gradually layer on the additional modules I have mapped out. Phase 1 – AI Talent Matching System The matching engine must handle three core functions: • Match candidates to open roles • Suggest relevant jobs to each candidate • Rate the overall candidate-job fit It will work primarily with résumé data and the candidate profiles we store internally. I expect a robust ML/NLP pipeline that can evolve as we ingest more data, so experience with transformers, embeddings, vector databases, and model fine-tuning will be valuable. Accuracy, e...

I need a highly accurate deep-learning model that translates Indian Sign Language (ISL) sentence-level gestures into English sentences in realtime. The key outcome is maximum translation accuracy with the lowest possible latency and a design that remains practical and scalable after hand-off. Key Points Input: Live video from a camera feed or landmark data from MediaPipe/OpenPose. Output: English word or phrase predictions rendered directly on a simple web page in realtime. Platform: Web/Mobile platform deployment. Scope: Deliver a working proof-of-concept with clear, commented code, minimal UI, and easy-to-follow setup instructions so the system can be tested end to end. Model: Transformer-based architecture for sentence-level translation, optimized for real-time inference. Data: You ma...

I need a mid-scope computer vision program built from scratch. The core goal is to ingest image or video data and produce meaningful, automated insights. I’m open to whether the solution focuses on image classification, object detection, or full image segmentation—whichever best fits the problem we identify together once you review my data and target use case. Here’s what I expect: • A working prototype that runs locally or in the cloud, complete with model training scripts, inference pipeline, and clear instructions (README). • Well-structured, commented code in Python, leveraging common libraries such as PyTorch or TensorFlow, plus OpenCV for preprocessing. • A concise report outlining data preparation steps, model architecture, training metrics, an...

I need a highly accurate deep-learning model that translates Indian Sign Language (ISL) sentence-level gestures into English sentences in realtime. The key outcome is maximum translation accuracy with the lowest possible latency and a design that remains practical and scalable after hand-off. Key Points Input: Live video from a camera feed or landmark data from MediaPipe/OpenPose. Output: English word or phrase predictions rendered directly on a simple web page in realtime. Platform: Web/Mobile platform deployment. Scope: Deliver a working proof-of-concept with clear, commented code, minimal UI, and easy-to-follow setup instructions so the system can be tested end to end. Model: Transformer-based architecture for sentence-level translation, optimized for real-time inference. Data: You ma...

I’m ready to move my modern-style house concept from sketch to a fully documented design package and need your expertise to do it right. Here’s what I’m after: a detailed, furniture-ready floor plan in 2D, plus complete 3D models of both the interior and exterior. The 3D assets should be presentation-quality, suitable for still renders as well as a short walkthrough. Alongside the visuals, I also want an aggregated cost comparison that shows how construction and finish prices shift from one location to another (materials, labour, local codes—whatever drives the difference). Preferred tools are flexible—AutoCAD or Revit for the technical drawings, SketchUp, 3ds Max, Lumion or comparable software for modeling and rendering—so use what lets you work f...

I need a clean-style overall architecture diagram showing my AI system pipeline ( data → preprocessing → ML & DL branches → fusion → evaluation). It should look professional , simple, well-labeled, and ready in 3 hours. Deliverable: 1 diagram (PNG ) Budget: $40

I’ll hand you a raw CSV (or Excel) containing transactional records and would like it transformed into clear, actionable insights about customer purchase patterns. Here’s what I need: • Clean the dataset—handle missing values, fix data types, remove duplicates, and document any assumptions. • Explore and quantify key purchase-related metrics such as frequency, average basket size, and category preferences. • Highlight notable trends and segments in customer behavior, summarising them in plain language. • Present the findings visually, favouring bar charts for the main comparisons, though you can supplement with Matplotlib or Seaborn line or pie visuals if they help the story. • Compile everything into a concise PDF report or an annotate...

I’m building a “learn-by-doing” lab for my Retrieval-Augmented Generation (RAG) course and need a full-stack engineer who can deliver the complete platform—from architecture to deployment. Core layout • Left pane: lesson instructions and guided prompts that I can edit in Markdown. • Right pane: a live code editor with the feel of Jupyter, Colab or VS Code; it must run Python end-to-end (backend kernels, package management, plotting, etc.). • Top-right corner: an integrated LLM assistant that offers contextual help, code generation and debugging support, always aware of the active notebook/cell. Key requirements • Python-only for now, but the stack can be designed so additional languages slot in later. • Smooth inline execution—...

need six model architecture diagrams three machine learning (ML) and three deep learning (DL) models. I will provide a full description of each model, including how it works, the hyperparameters used, and other technical details. Only the diagrams are required (no explanations or reports). This is urgent I need them within the next 4 hours if possible. I’m looking for someone who has hands-on experience in both ML and DL and can accurately draw or generate these model structures based on my descriptions. Budget: 60 used

I want a compact language model that can spit out fluent, casual chat responses on everyday topics. The end goal is smooth text generation, not question-answering or classification, and it needs to stay small enough to serve on modest hardware. What I need from you: • Pick or design a lightweight architecture—something in the “tiny” range that still sounds natural. Distilled GPT, a trimmed-down Llama, or a custom-built transformer are all fine as long as the total parameters remain comfortably low. I want the model to have fast interference on cpu, well it should run on cpu. • Source or build a conversational dataset with permissive licensing, then fine-tune and evaluate until the model’s casual tone is consistent. • Track metrics (perplexity or a...

Project Name: GaiaLink — The Living Planet Network Tagline: A global, AI-powered digital nervous system for Earth — enabling the planet to sense, heal, and evolve itself. 1. The Core Vision Humanity monitors the Earth through satellites, research, and reports — but there is no unified, real-time intelligence that allows the planet itself to “speak” to us. GaiaLink is a planetary-scale network that fuses AI, bioengineering, and nanotechnology to make Earth self-aware and self-regulating — capable of detecting damage (deforestation, pollution, climate change) and triggering automated responses to heal itself. It’s not just environmental tech — it’s the foundation for a living digital ecosystem. 2. Core Concept (Never Existed Before) G...

I need a real-time vision/video routine that taps into our Unifi camera stream, inspects the texture of product (dewatered potato pulp) moving on a conveyor belt (or in a screw converyor), and decides whether that material is wet or dry. See images. It is also possible to give more close up images of the product on the conveyor belt or during the overflow. Once a decision is made the software must immediately do two things: • push a flag we can read inside the PLC/SCADA layer so the process can react (speed change, diverter, etc.), and • raise an operator alarm whenever the state flips or a confidence threshold is not met. Key points you should know • Source feed: live RTSP stream served by our Unifi NVR. No file uploads—the analysis has to run continuously. ...

Freelancer should be of Pakistan or India. I need new freelancer at low budget. I need a complete, end-to-end Python pipeline that accurately segments brain-tumor regions on the BraTS 2023 MRI dataset. The job covers everything from data loading and preprocessing through model training, validation, and inference. You’re free to choose the deep-learning framework you’re most productive with—PyTorch, TensorFlow, or Keras—as long as the final code is clean, reproducible, and clearly commented. a deep learning-based segmentation model using TransUNet, a hybrid CNN + Transformer-based U-Net model, to automatically segment brain tumors from MRI scans in the BraTS 2023 dataset.

Artificial Intelligence (AI) is the field of computer science that focuses on building systems capable of performing tasks that normally require human intelligence — such as learning, reasoning, problem-solving, understanding language, and recognizing patterns. With AI technologies like Machine Learning, Deep Learning, and Natural Language Processing (NLP), computers can analyze data, make predictions, and automate complex processes. I work with AI tools and frameworks such as Python, TensorFlow, PyTorch, and scikit-learn to build intelligent models that can: classify text or images, make data-driven predictions, and optimize workflows. AI is shaping the future of automation, business, and innovation — and I’m passionate about creating smart solutions that bring rea...

I’m looking to build a functional prototype of an AI-driven examination portal that focuses on lecture-based learning data. The goal is to prove the core concept end-to-end, so I can later scale it into a full SaaS product. What I need you to develop: • Lecture-to-Question Generator Ingest a recorded lecture (audio or video), segment it by topic, and automatically create a mixed set of questions. Multiple-choice is welcome, but the must-have is auto-generated fill-in-the-blank items. • Smart Evaluation On submission, the system instantly checks those fill-in-the-blank answers with NLP similarity scoring or keyword matching, then stores the graded attempt. • Adaptive Testing Logic Serve the next question set based on the student’s current performan...

I’ll hand you a raw CSV (or Excel) containing transactional records and would like it transformed into clear, actionable insights about customer purchase patterns. Here’s what I need: • Clean the dataset—handle missing values, fix data types, remove duplicates, and document any assumptions. • Explore and quantify key purchase-related metrics such as frequency, average basket size, and category preferences. • Highlight notable trends and segments in customer behavior, summarising them in plain language. • Present the findings visually, favouring bar charts for the main comparisons, though you can supplement with Matplotlib or Seaborn line or pie visuals if they help the story. • Compile everything into a concise PDF report or an annotate...

Hi, We're an emerging news media startup, looking for a freelance technical writer with thorough understanding of technological, Artificial Intelligence (AI) and Machine Learning (ML) concepts, and an innate knack for storytelling with clean and crisp writing skills. You are expected to break down complex topics into simplified, engaging and well-researched stories. If you are passionate about cutting-edge and innovative technologies and have the ability to explain them in a lucid manner, then this job is for you. Prior writing samples appreciated. Please note that candidates will only be shortlisted after appearing for a test. No ghostwriting please. Responsibilities: Write explainer articles on AI/ML concepts Cover trending AI developments and tools. Research technical papers,...

Title: AI + DSP Audio Engine for Music Platform – Python / PyTorch / Signal Processing Experts Wanted Project Description: We are developing an advanced AI-powered music collaboration platform — a system that intelligently recognizes, aligns, and mixes thousands of human vocals recorded globally. This is not a standard audio app. It is a deep-technology project combining Digital Signal Processing (DSP), AI/ML, and scalable backend engineering. We are seeking skilled engineers to support the completion and optimization of the DSP core and backend infrastructure. Your Role Develop and optimize modules for: Noise reduction and dereverberation Pitch tracking and formant correction Multi-user vocal alignment (CQT, DTW, NCC) AI-driven mixing and mastering (LUFS normalizati...

I need a concise, academically-sound overview of an AI-driven cybersecurity system that SecureBank International could deploy. The assignment consists of two deliverables: • A 2 500-word Harvard-referenced report that: – Explains weak vs. strong AI and positions the proposed solution within ANI, AGI or ASI terminology. – Describes how AI supports threat detection, phishing detection with NLP, anomaly detection, malware & ransom detection, automated incident response, and UEBA. – Discusses ethical AI in cybersecurity, covering privacy, bias, explainability and relevant GDPR considerations. – Presents clear technical, legal and organisational implications for the bank. • A supporting slide deck (10–15 slides) that distils the key po...

I have a fully-labeled collection of WAV recordings and need a compact solution that can 1) tell whether an input clip is a human voice and 2) identify which speaker from the dataset is talking. My preference is to work with MFCC features fed into a Convolutional Neural Network; if you believe another architecture will reliably hit the 90 % accuracy mark, feel free to explain why. Scope of work • Write a clean training script that reads the WAV files, extracts MFCCs, and trains the model. • Validate on a held-out set and document the accuracy; target ≥ 90 %. • Provide the final weights, an inference script that accepts a single audio file and prints the predicted speaker name (or “unknown” if outside the set), and a short README with setup and run com...

I’m looking for a pre-trained model set that drops straight into DeepFaceLab and performs flawlessly for face-swapping work in video production. Here’s what I need: • 256×256 male model (primary priority) • 512×512 male model • 512×512 female model Each model should be “rich”—well-trained on diverse, clean data so texture, lighting, and expression coverage are excellent and artifacts minimal. My end goal is smooth, believable swaps on 1080p and 4K footage with as little post-cleanup as possible. Key points – Target platform: DeepFaceLab (“Model Deepfacelab” was my Q&A selection). – Main use case: Face swapping for videos, so consistency across frames matters more than single-image sharpn...

I want to level-up my data-analysis skills by diving into machine learning that works specifically with text data. I’m looking for a mentor who can break concepts down clearly, walk me through hands-on examples, and leave me with resources I can revisit afterward. What I need • A short series of live, screen-share sessions (Zoom, Google Meet, or similar) that cover the core workflow of building an ML model for text: cleaning, vectorizing, training, evaluating, and iterating. • A well-commented notebook (Python preferred—think scikit-learn, pandas, maybe a peek at TensorFlow if time allows) that mirrors what we covered in the calls. • A concise checklist or roadmap highlighting next steps so I can continue practicing on my own. Focus areas – Machine le...

I already have an Android app written in Kotlin that upscales images with TensorFlow Lite. Right now the model runs on CPU and GPU; I’d like a concise upgrade that lets it execute on the Neural Processing Unit found in recent Qualcomm Snapdragon chips. Key details • Tech stack in place: Kotlin + TensorFlow Lite. • Target hardware: recent Snapdragon devices (e.g., 855, 865, 888—exact list can be refined together). • Priority: unlock NPU performance while preserving the current accuracy of results. What I need from you 1. Modify the existing TensorFlow Lite setup so inference routes through the Snapdragon NPU (likely via the Qualcomm Neural Processing SDK / QNN delegate or any newer, officially supported path). 2. Keep model output numerically in line...

hi , we have a platform that stock data of our clients websites : ip visitors - session duration of each click - sponsored link ou organic visitor. we want to implement a strategy to detect patterns that identify fraudulent clicks. we stock our datas on supabase . we can have months of ips data with all infos .

My production platform has grown rapidly and the cracks are starting to show. It was built over time in Python, Node .js, JavaScript and a legacy PHP layer that still serves parts of the front end (HTML/CSS). We are in the maintenance phase, yet demand keeps climbing, so scalability is now the priority. What I need is a seasoned software architect who can dive into the existing codebase, profile real-world traffic, and refactor or redesign the pieces that limit horizontal growth. The database layer is holding up for now; the bottlenecks are mostly in application code—tight loops, blocking calls, duplicated logic and a few monolith-style services that should be broken out or made asynchronous. Experience with high-throughput data processing, machine-learning pipelines and load-aware ...

I need new freelancer at low budget. I need a complete, end-to-end Python pipeline that accurately segments brain-tumor regions on the BraTS 2023 MRI dataset. The job covers everything from data loading and preprocessing through model training, validation, and inference. You’re free to choose the deep-learning framework you’re most productive with—PyTorch, TensorFlow, or Keras—as long as the final code is clean, reproducible, and clearly commented. a deep learning-based segmentation model using TransUNet, a hybrid CNN + Transformer-based U-Net model, to automatically segment brain tumors from MRI scans in the BraTS 2023 dataset.

Is there any way we can pull such data automatically using AI we have list of organizations i have attached a sample file you can test on the file attached contains a list of organizations you need to find a way using AI to automatically get those fields

Is there any way we can pull such data automatically using AI we have list of organizations i have attached a sample file you can test on

I need a web-based system that forecasts three key outcomes—moneyline (H2H), line/spread, and total points (over/under)—for the following sports: NRL, AFL, NBL, NBA, NHL, MLB, and NFL. Core requirements • Model training must rely on historical game data only; I already have access to public datasets and can provide sample CSVs if that helps. • Weather, venue, date, and start-time should be treated as additional features to improve accuracy. • The interface should let me: – browse upcoming fixtures with the model’s probabilities and suggested picks – record the bets I actually place (stake, odds, outcome) – view running profit/loss and basic analytics such as win rate and ROI. Technical notes • Deploy as a res...

Sns platform Data,SEO,AD Analytics → Auto Content(wrting image video)→ Multi-Platforms upload→ Email autosend classify→ Chat & Call shopping aniisis uplaod like Once start I will provide the detailed workflow structure (links, nodes, prompts, etc.) so you can work smoothly

I want to build a multi-tier application that replicates the core idea of DocsGPT while remaining fully self-hosted. The stack is already chosen: • Front end: ReactJS or AngularJS (your choice, but keep component structure clean and reusable) • Back end: Python with Django REST framework for the API layer • Database: MongoDB for persistent storage Vector handling The system must index and retrieve information through three separate numerical vector spaces. Each layer should be pluggable so I can experiment with different embedding models later without rewriting the pipeline. Core AI features 1. Text generation 2. Summarization 3. Question answering These should all draw on the vector stores and run on an on-prem LLM—no external API calls once the mo...

AI Monitoring & Analytics Agent Developer Project Overview We are developing a smart AI-powered monitoring and reporting agent to automate media and data analysis across Saudi Arabia, the Gulf region, and global markets — in all languages including Arabic dialects. The system will analyze large-scale data streams, validate content accuracy, and generate professional reports for executive and media decision-making. AI Agent Role The AI Monitoring Agent will: Collect data automatically from Talkwalker (via API integration) and related media sources. Clean and merge datasets, removing duplicates, spam, and bot-generated content. Perform validation & fact-checking by comparing multiple sources and confirming credibility against official and verified entitie...

I’m ready to run a powerful open-source LLM on my Windows machine and then use it as the engine for future agents. I need someone who will walk me through the process live, rather than just handing over a script. Scope of work • Help me choose and download a suitable Windows-friendly build of the models I’ve shortlisted (Meta, Gork, DeepSeek or a comparable alternative if you can justify the swap). • Set up all required dependencies—CUDA or CPU builds, Python environment, GPU drivers, libraries such as llama-cpp-python or Hugging Face Transformers—so the model loads locally without errors. • Validate the installation by running a quick inference test from the command line and a simple Python script. • Guide me, step by step, in creatin...

I’m refining an existing image-generation model and need it to produce realistic photos rather than stylised art. The target output is medium-resolution with moderate detail—crisp enough for web display without ballooning file size. You’ll receive my curated training set, current checkpoint and prompt examples. From there, I’d like you to set up the fine-tuning workflow (LoRA, DreamBooth or another efficient approach), run training, iterate on hyper-parameters, and return: • the updated weights • reproducible training code or notebook • a short read-me covering environment, key settings and how to infer new images Acceptance criteria • Sample batch from agreed prompts looks convincingly photographic • Quantitative metric (e.g., FI...

I have a large time-series dataset (anonymized financial data) and want to build a predictive model that can identify patterns and forecast short-term movements. You’ll be working on real-world data — but the asset name will stay confidential. Your job is to build, test, and train a model that can generate predictions or trading-style signals with measurable accuracy.

I’m building a suite of custom language models for the finance sector and need an experienced partner to steer both the technical and business aspects of the rollout. The immediate goal is to integrate commercially available LLMs—think OpenAI, Anthropic, Cohere or similar—then fine-tune or extend them so they speak the language of finance fluently. Core use-cases we’re targeting include risk assessment, predictive analytics, credit underwriting, data capture automation and score-card creation. The models will ingest and reason over three main data streams: financial transaction data, customer data and live market data. Beyond accuracy, we must meet strict compliance and explainability requirements typical of regulated environments. Here’s what I need from yo...

I have an existing application that already uses machine-learning code. I need a developer who can dive into the current repo, clear out the lingering bugs, and roll out several new enhancements: • User-interface upgrades – specifically a smoother, more intuitive UX and refreshed styling that matches our latest brand guidelines. • Seamless integrations – connect the app to leading payment gateways and cloud-storage providers so users can purchase add-ons and save video assets in the cloud without friction. • Backend AI hooks – wire the codebase to external AI platform calls and tidy up data management so our models run efficiently at scale. You’ll be working directly with me on feature branches, submitting clean, well-commented commits and short...

Im looking for a highly skilled electrical engineer (preferably with a PhD) to support our project focused on EEG signal processing and role involves: • Algorithm Development: Designing and implementing algorithms to process EEG data. • Data Analysis: Performing in-depth analysis of EEG signals. • Hardware Setup: Assisting in setting up EEG signal acquisition systems. • High-Quality Writing: Supporting documentation and research writing with clear, professional, and accurate language. Involvement We are seeking an electrical engineer with a PhD in the field to provide assistance with deepening EEG signals. The project involves the following tasks: • Algorithm development: The main focus of the project is to develop algorithms for processing EEG signals. • Da...

I need a compact solution that plugs into my existing real-time market feed and continuously scans candlestick data for three specific formations: Head and Shoulders, Double Top/Bottom, and Cup and Handle. When any of these patterns complete (or are in a well-defined final stage), the system should raise an instant alert that I can route to a webhook, email, or simple on-screen notification. The job centres on the recognition logic itself rather than feed acquisition; the streaming API is already available and delivers OHLCV ticks in JSON. A clean Python module using pandas, NumPy, or TA-Lib is preferred, but I am open to another language if it offers clear advantages and the code remains readable and easy to maintain. Acceptance criteria: • Processes live ticks with a maximum e...

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Project Proposal: Real-Time Fraud Detection in Financial/Banking Transactions Demo 1. Project Overview The goal of this project is to design and develop a real-time fraud detection system for financial and banking transactions using machine learning (ML) and artificial intelligence (AI) techniques. The system should identify potentially fraudulent transactions across multiple payment channels, including credit/debit cards, net banking, mobile banking, and UPI. Since real data cannot be shared, the freelancer must generate realistic dummy data that simulates actual banking transactions and covers a wide variety of fraudulent scenarios commonly observed in financial systems. 2. Objectives 1. Build a data-driven model to classify transactions as “legitimate” or “fraudulent...