Machine Learning (ML) Jobs

I’m launching a pet-grooming site that does more than list services—I want it to think. The heart of the build is an AI engine that studies a visitor’s pet breed and instantly returns tailored grooming recommendations (coat-care routines, trim frequency, product tips, seasonal advice, and so on). I have the content ready; your job is to wrap it in logic and deliver it through a clean, mobile-first interface. Beyond the recommendations module, I also need a secure user area where owners can log in and view a timeline of every grooming visit or home session they record. Each entry should store date, notes, and any products used, so the AI’s future advice can grow smarter over time. Key deliverables • Responsive website (React, Vue, or similar) connected to ...

I need to build an AI-powered video creator that leans heavily on computer-vision techniques. The goal is a tool that takes raw clips or even still images and, through smart scene understanding, automatically assembles polished videos—essentially an AI video maker that handles the tedious parts of editing and enhancement for me. Core objectives • Train or adapt a computer-vision model that can detect key moments, faces, objects, and scene changes, then use that information to sequence footage intelligently. • Implement automated video generation logic—transitions, basic trimming, and soundtrack alignment—so the user can go from assets to finished output with minimal clicks. • Include real-time or near-real-time preview plus the option for manual twea...

I have a Raspberry Pi 5 paired with a HealthyPi 5 HAT on my bench and I want to turn it into a completely offline, voice-driven health companion in the next two weeks. All the hardware is already wired up; I just need solid software engineering to pull the pieces together. Core workflow I’m after • Speech-to-text: run Whisper locally to listen for conversational prompts and, at minimum, “Give me a status update.” • Vitals ingestion: poll HealthyPi’s heart-rate, SpO₂, respiration, temperature and any other available metrics in real time. • Decision layer: generate simple health advice from those vitals (e.g. flagging abnormal ranges) and package it into a friendly sentence. • Text-to-speech: feed that sentence to Piper so the Pi replies a...

I want to build a sophisticated cryptocurrency arbitrage program that scans several major exchanges—Binance, Coinbase, Kraken, or any others you judge more profitable—in real time, pinpoints price discrepancies, and executes trades automatically. My target is an 80 %+ win rate, so the core logic should combine fast order-book scraping with an AI-driven decision engine that filters for the highest-probability spreads before committing capital. The application must stream data with minimal latency, place and manage orders end-to-end, and keep me fully informed through a clean analytics dashboard showing live PnL, historical performance, and risk metrics. Flexibility to plug in additional exchanges later is important, so please structure the code modularly (I’m fine with Py...

I’m putting together a fully local pipeline that can turn text or microphone input into real-time synthetic video with out latensy and matching speech without ever calling a paid API. What I need from you is a clear, reproducible worksheet that walks me from a blank machine to a working demo. My main pain-point is model selection and setup, so the document has to name the exact models, versions, weights and repos you recommend (Stable Diffusion / Stable Video Diffusion or similar on the visual side, plus an open-source TTS or voice-cloning stack). Everything must run on a local Linux server with an NVIDIA GPU, CUDA and Python—no external SaaS calls. Please include any build flags, environment variables, VRAM tips and latency-saving tricks that actually matter in practice...

I am building a fully autonomous system that can think and act like a veteran construction engineer—only faster. The core features I need you to deliver are: • Project planning and scheduling: ingest drawings, specs, or even a rough scope and instantly output an optimised, resource-levelled schedule (Gantt, CPM, critical-path alerts, what-if analyses). • Cost estimation and budgeting: generate detailed BoQs, pull live material-price feeds, model labour curves, and keep contingency and escalation logic intact throughout the life-cycle. Everything must run seamlessly on mobile (iOS / Android), in the browser, and as a desktop install. A single code base with a shared AI engine is strongly preferred so end users can pick up work on-site, in the office, or in the field with...

I need a well-structured research proposal that investigates how artificial intelligence can cut the environmental footprint of transportation within e-commerce logistics. The document must clearly identify the current challenges of last-mile and line-haul delivery, map the latest AI-driven solutions that address them, and articulate a research methodology capable of testing their impact on carbon emissions, fuel consumption, or related sustainability metrics. Please ground the study in recent, peer-reviewed literature and authoritative industry reports, focusing on transportation methods such as electric or automated vehicles, dynamic route-optimisation algorithms, and predictive demand planning. While my priority is reducing environmental impact including Carbon emission, links to opera...

I need a well-structured research proposal that investigates how artificial intelligence can cut the environmental footprint of transportation within e-commerce logistics. The document must clearly identify the current challenges of last-mile and line-haul delivery, map the latest AI-driven solutions that address them, and articulate a research methodology capable of testing their impact on carbon emissions, fuel consumption, or related sustainability metrics. Please ground the study in recent, peer-reviewed literature and authoritative industry reports, focusing on transportation methods such as electric or automated vehicles, dynamic route-optimisation algorithms, and predictive demand planning. While my priority is reducing environmental impact including Carbon emission, links to opera...

Autonomous AI agent I want help creating a self-directed AI agent that can tackle biological/medical research research by reviewing the literature and creating mathematical models of disease pathology using the R programming language. • Perform comprehensive literature reviews by ingesting and summarising peer-reviewed papers from major scientific journals and pre-print servers. • Analyse data pulled from public repositories • Reproducing models in the literature and coming up with new hypotheses for mathematical models of disease. I expect an end-to-end workflow: automated retrieval of journal articles and database records, semantic search across that corpus, data cleaning, exploratory and confirmatory analysis in R/mrgsolve, and an LLM-driven (Claude) reasoni...

Hello, I want to make LLM model complete from scratch. Please contact if any experience developer available

I’m building a unsupervised classifier that learns jointly from audio recordings and accompanying physiological signals. My end-goal is a robust prediction model that can generalise to new subjects, so every modelling choice—from feature pipeline through network architecture and hyper-parameter search—has to be evidence-driven and reproducible. Here is what I already have: raw multichannel wave files, synchronised physiological traces (ECG, EDA and respiration) and a draft protocol for train-test splits. What I still need is the deep-learning firepower to turn this into a working model, coded cleanly in Python with TensorFlow or PyTorch, complete with training scripts, inference wrapper and clear documentation. I’ll share the data dictionary, baseline metrics and ...

I want to turn a standard RC chassis into a smart, self-aware toy that can do far more than just follow joystick commands. The end goal is a prototype car that: • Detects obstacles in real time • Plans an optimal path around them • Switches between full autonomous driving and classic “manual” mode on demand Everything should be directed from a single mobile app that works seamlessly on both iOS and Android. From that app I need to: 1. Watch a live video feed (low-latency) 2. Toggle between autonomous and manual modes 3. See a simple map of the car’s planned path and any detected hazards 4. Push OTA firmware updates when new AI models are trained Hardware is already on hand (Raspberry Pi 4, camera module, ultrasonic sensors, ESC, and an ESP...

I will provide a corpus of raw call recordings, each in MP3 format, and I need a machine-learning model that can automatically flag fraudulent activity. The model must correctly recognise the three problem categories—Phishing, Robocalls and Telemarketing scams—without human intervention. What I expect you to handle: • Pre-processing: clean the audio and extract features (e.g., MFCCs or spectrograms) that capture speaker and content cues. • Modelling: design, train and fine-tune a classifier; CNN, RNN, Transformer or a hybrid approach is acceptable if it improves accuracy. • Evaluation: deliver precision, recall, F1 and a full confusion matrix for each fraud type so I can judge real-world performance. • Deployment assets: an inference script or small R...

ob Title: Data Scientist Role Overview: We are seeking a Data Scientist to help us transform our CRM, Gradlynk, into a more intelligent, AI-driven platform. The role will focus on leveraging data to enhance student engagement, improve learning outcomes, and optimize operational efficiency across our edtech ecosystem. Key Responsibilities: -Collect, clean, and analyze data from Gradlynk and other sources to generate actionable insights. -Develop predictive models and machine learning algorithms to personalize student experiences and forecast performance trends. -Collaborate with IT, Product, and Operations teams to integrate AI-driven features into Gradlynk. -Translate complex data findings into clear recommendations for educators, administrators, and business stakeholders. -Monitor an...

Senior AI / ML Architect – GenAI, MLOps & Enterprise AI Work Support (10+ Years) Job Description We are seeking a highly experienced AI/ML professional (10+ years) to provide ongoing technical work support across advanced AI, GenAI, and data-driven systems. This role involves hands-on guidance, design reviews, problem-solving, and production support for complex AI/ML implementations in enterprise environments. The ideal candidate has deep real-world experience and can quickly understand requirements, identify gaps, and provide clear technical direction. Candidates may specialize in any subset of the skills listed below. Core Expertise (Any of the Below) Generative AI & LLM Systems LLM-based applications and enterprise GenAI platforms Prompt design, alignment, evaluat...

I am building a web-based SaaS that lets estheticians quickly scan a client’s photo, receive an instant professional skin analysis, book the appropriate facial treatment, and sell the products the scan recommends—all in one place. Core analysis: The algorithm must reliably detect acne or blemishes, dryness or oiliness, wrinkles or fine lines, combination skin, redness, and visible pores or texture issues. Accuracy and consistency are critical because treatment plans and sales will hinge on the results. Workflow vision 1. Client uploads or snaps a photo during an online consultation or in-spa visit. 2. The system runs the analysis, displays condition scores, and explains each finding in easy language. 3. Based on those scores it lists the facial services I pre-configur...

I have a large collection of raw text documents and images that I need turned into clear, actionable insights. The job centres on exploratory data analysis rather than predictive modelling: I want to understand patterns, themes and relationships hidden inside both formats. Here is what I expect at the end of the engagement: • A well-commented Python (or R) notebook that walks through preprocessing, cleaning and exploratory techniques applied to the text and image sets. • Concise visual summaries—charts for the text, heat-maps or feature plots for the images—exported in high-resolution formats I can drop straight into presentations. • A short written report (PDF or Markdown) highlighting key findings, unusual correlations and any recommendations that emerge...

I want to launch a web platform whose core function is data analysis, specifically focused on how visitors interact with the site itself. Every click, scroll, hover, and dwell time should be captured, stored, and fed into an AI layer that surfaces patterns, segment-level insights, and actionable recommendations. The emphasis is on website interaction data; while purchase history or social media feeds could be interesting later, they are out of scope for this first release. The build needs three tightly integrated pieces: a tracking script that records session events in real time, a scalable backend (Python, Node, or similar) that cleans and aggregates those events, and a lightweight ML pipeline—think TensorFlow, PyTorch, or a comparable framework—to run clustering and predicti...

AI Engineer / AI Agent Architect – ERP Platform (Monolithic Java, MySQL, SaaS) We are developing a multi-tenant ERP platform currently built as a Java Spring Boot monolithic application with MySQL as the database and Angular as the frontend. While our long-term roadmap includes migration to microservices, the immediate objective is to safely introduce an AI-powered intelligence layer without disrupting the monolithic ERP core. Objective of the Role Design and implement an external AI intelligence layer that integrates with our existing monolithic ERP to provide: Business analytics and dashboards Predictive insights and forecasts Alerts, reminders, and anomaly detection Conversational ERP intelligence (AI Copilot) The AI must be ERP-aware, secure, tenant-isolated, and product...

I want to build a conversational personal assistant whose single mission is fast, accurate information retrieval for general-knowledge queries. No calendars, no task lists—just a lightweight, reliable engine that listens to a natural-language question, finds the best answer, and returns it with a clear citation. Here is the picture I have in mind. A compact LLM (e.g., Llama 3, Mistral, or whatever stack you recommend) sits behind an RAG pipeline that searches trusted public sources, ranks passages, and feeds only the most relevant snippets back to the model. The response should arrive in under five seconds and include at least one hyperlink or reference so the user can verify the claim. Deliverables • Source-controlled code for the model, retrieval layer, and a simple web or...

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ob Title: Data Scientist Role Overview: We are seeking a Data Scientist to help us transform our CRM, Gradlynk, into a more intelligent, AI-driven platform. The role will focus on leveraging data to enhance student engagement, improve learning outcomes, and optimize operational efficiency across our edtech ecosystem. Key Responsibilities: -Collect, clean, and analyze data from Gradlynk and other sources to generate actionable insights. -Develop predictive models and machine learning algorithms to personalize student experiences and forecast performance trends. -Collaborate with IT, Product, and Operations teams to integrate AI-driven features into Gradlynk. -Translate complex data findings into clear recommendations for educators, administrators, and business stakeholders. -Monitor an...

We are looking for a developer to build a visa application system with the following features: Scope of Work: Client portal for users to fill visa application forms (dynamic & conditional fields) Secure document upload system AI-based document validation (format / quality checks with instant alerts) Admin panel for reviewing applications and documents AI-based document compliance checking using predefined rules System must clearly highlight specific issues Chrome Extension to auto-fill the official government visa website Pull data from our portal Populate fields only (no auto submission) Requirements: Experience with Python (Django / FastAPI preferred) Strong JavaScript skills Experience building Chrome Extensions (Manifest V3) Experience with OCR / document processing ...

I need structured, beginner-friendly coaching that will take me from “hello world” to employable in Natural Language Processing. My goal is to understand core NLP concepts, build a small portfolio of projects, and feel confident discussing them in interviews. I already code a little in Python but have no formal NLP background. I’d like to cover the foundations—tokenisation, embeddings, transformers—then progress to hands-on mini-projects using libraries such as spaCy, Hugging Face, TensorFlow or PyTorch. Guidance on best practices for data preprocessing, model selection, evaluation and error analysis is essential, along with tips on how to present this work in a résumé or GitHub repo. Deliverables I have in mind: • A personalised learning ...

I have a pre-processed collection of aligned audio-video clips and I want to push them through the AVHubert CoDA pipeline to obtain a clear Character Error Rate (CER) metric. The raw training and validation splits are ready; what’s missing is the glue code and know-how to hook my data into the official AVHubert / fairseq framework, run inference, and surface the CER report. Here’s what I expect at the end: • A working script or set of commands that load my dataset and execute AVHubert CoDA end-to-end (feature extraction, decoding, and CER calculation). • A brief README summarising environment setup (Python, PyTorch, fairseq, ffmpeg, KenLM, etc.) and any extra dependencies. • The final CER value plus the log files or JSON outputs that back it up, so I can re...

I need a comprehensive book aimed at intermediate users that provides deep insights into the AI industry. The book should cover the following areas in detail: - Machine Learning - Natural Language Processing - Computer Vision The content should be engaging, informative, and reflective of current industry trends and future predictions. Ideal skills and experience: - Strong background in AI - Excellent research and writing skills - Experience writing for an intermediate audience - Ability to analyze and present industry insights

Project Description: I am looking for an experienced full-stack developer (preferably with blockchain/DeFi knowledge) to create a high-quality, modern cryptocurrency price oracle scanner and monitoring platform, closely inspired by — specifically the "BTC Oracle Scanner" tool. This site is not a full publishing oracle like Chainlink or Pyth (i.e., it does not need to push data on-chain initially), but rather a powerful real-time monitoring, deviation detection, latency tracking, and anomaly alerting dashboard that compares BTC/USD (and potentially other assets) prices across multiple sources: CEXs, oracles, DEXs, and wrapped/bridge tokens. Core Goal & Inspiration Replicate and improve upon the functionality of : Real-time BTC/USD price pulling and comparison every few...

Remember this should work offline environment I have a batch of English-language PDFs that were scanned as images. Each file contains a mix of cleanly typed passages and more challenging handwritten notes in the margins. I need every legible word pulled out with the highest accuracy you can achieve and stored directly in a MySQL database, not as flat files. Accuracy matters more than speed; feel free to combine engines such as Tesseract, Google Vision, or AWS Textract—whatever blend gives you the best recognition rate on both printed and cursive text. Pre-processing for skew, noise, and contrast is expected so the handwriting is captured as reliably as the typed sections. The database is already provisioned; I will share connection details and a simple schema suggestion (doc_id, p...

I’m building a cross-platform mobile app that acts as a personal styling and beauty assistant for both men and women. The core of the product is an AI engine that delivers highly-personalized outfit recommendations. Key functionality • The assistant studies three user-supplied inputs—body measurements, skin tone and face shape—and combines them with each person’s stated style preferences, their body type and real-time fashion trend data. • For every request it returns a clear set of outfit suggestions, indicating why each piece flatters the user’s proportions, complexion and current tastes. • A lightweight dashboard lets me update trend data, brand catalogs and style rules without redeploying the app. Technology expectations The re...

I’m completing my MTech at GTU and my approved thesis topic is sentiment analysis of hotel reviews collected from major online review websites such as TripAdvisor and Booking.com. I need a data-savvy NLP partner who can work with me across the full research pipeline—from harvesting the raw reviews to writing up publish-ready results. Here’s what I have in mind: • Build and share a reproducible scraper or API workflow that gathers a sizeable, legally usable corpus of hotel reviews (ideally 50 000+). • Clean, label, and explore the text so we can isolate meaningful sentiment signals; I’m open to focusing on customer satisfaction, service quality, room amenities, or any mix that produces the most insightful output. • Develop both baseline keyword ap...

I’m ready to turn a fresh idea into a working MVP and need an AI specialist who can own the end-to-end predictive analytics layer. The single most important outcome is a model that takes my existing data, produces reliable forecasts, and is simple enough to slot straight into a lightweight product demo. Here’s the scope in plain words: • Select and train an algorithm that balances accuracy with speed—feel free to use Python, TensorFlow, PyTorch, or another framework you prefer, so long as the environment is reproducible. • Wrap the model in a small REST or GraphQL API so I can call predictions from a basic front-end. • Hand over deployment instructions for a cloud environment (AWS, GCP, or Azure—your choice) so the MVP runs in a real setting, n...

I'm looking for a skilled machine learning expert to help with my final year university project. The goal is to identify different sleep stages using multimodal data, specifically ECG patterns and blood pressure signals. Key Requirements: - Analyze ECG and blood pressure data - Develop a machine learning model to estimate sleep stages - Utilize existing dataset Ideal Skills and Experience: - Strong background in machine learning - Experience with ECG and blood pressure signal analysis - Proficiency in data processing and model development - Familiarity with sleep stage identification techniques

I’m building a retrieval-augmented generation (RAG) pipeline and need a specialist to stand up the vector database layer for my large-language-model workflow. All content going into the store will be purely textual—think markdown files, knowledge-base articles, and long-form documents—so the schema, chunking strategy, and embedding approach should be optimised for fast, accurate text search. Here’s what I’d like from you: • Recommend and deploy a production-ready vector database (Pinecone, Weaviate, Chroma, Milvus or a comparable option). • Design a text-specific embedding and metadata schema, including parameters such as chunk size, overlap, and namespace strategy. • Build ingestion scripts that batch-process my existing documents, generate em...

- Implement voice-to-task automation in Roman Urdu/Hindi, English, or Arabic. - Develop drawing and toolpath generation based on input dimensions or customer requirement - Create an AI agent for client management and quotation generation. - Set up an end-to-end workflow to handle technical preparation. Experience with AI tools and automation in industrial settings - Proficiency in developing multilingual voice recognition systems - Knowledge of CNC operations and toolpath generation - Ability to integrate client management systems with AI

Project Overview We are looking for an expert AI/Computer Vision developer (or small team) to build a scalable, production-ready AI pipeline for a fashion eCommerce catalog. The goal is to automate product tagging and generate photorealistic on-model images from flat-lay photos. We prioritize cost-effective solutions leveraging state-of-the-art (SOTA) open-source models (e.g., IDM-VTON, OOTDiff, Stable Diffusion XL). 1. Automated AI Product Tagging • Volume: 20,000–40,000 SKUs/year (Batch processing required). • Scope: Fashion only (Apparel, Accessories, Footwear). • Task: Build a CV-based engine to extract attributes (Category, Color, Material, Fit, Pattern, Style, etc.). • Taxonomy: Consultant should help define a scalable tagging structure. • Requirement:...

I want to build an in-house AI system that lets my team drag-and-drop both KYC and Income documents and, in one click, receive a neatly formatted PDF report. The PDF must always include: • Eligibility check (based on the rules I will supply) • Salary details in a clear monthly breakdown table • Current obligations in a similar table • Pending documents list • Pending form details • Probable queries for the credit team All eligibility logic, standard document lists and a library of past queries will be provided so the model can be fine-tuned to our exact policies. Accuracy and consistency matter more than fancy UI; I simply need a reliable back-end that ingests scans or PDFs, extracts the data, applies the rules and returns a single consolidated...

I'm looking for an AI-driven building automation energy analyzer tailored for commercial buildings. The system should have the capability to upload comprehensive building databases and trend files in CSV, Excel, JSON, or Zip formats. Key Requirements: - Analyze overall energy consumption and efficiency ratings - Provide insights on kW consumption versus energy savings - Identify faulty equipment and potential energy savings Ideal Skills and Experience: - Expertise in AI and machine learning - Strong background in energy analysis and building automation systems - Proficiency in handling and analyzing data in CSV, Excel, and JSON formats - Experience with commercial building energy metrics BAS System examples - WebCtrl -Honeywell Niagara -Tridium -Seimens -Alerton Once the database...

I’m evaluating security vulnerabilities in three Arabic-capable language models—Allam, Falcon, and Fanar—by running the Garak prompt-injection suite. My top priority is the technical implementation, with a particular emphasis on translating each of Garak’s 256 English attack prompts into clear, natural Arabic before the tests run. Here’s how the workflow looks: • Build a Python notebook that loads the three models from Hugging Face (PyTorch backend), pipes the Arabic prompts through Garak, captures logits and full responses, and writes everything to tidy CSV files. • Include bilingual testing so the notebook can toggle between the original English prompts and their Arabic counterparts, allowing side-by-side success-rate comparison. • P...

I want a single, turnkey application that watches my CCTV feeds, spots shop-lifters in real time, recognises grocery products on the shelves, and keeps a live head-count of customers. The core model must be YOLO, and I need the exact same code-base to compile and run on both Windows (desktop with NVIDIA GPU) and a Raspberry Pi 4. Video sources vary—some cameras stream RTSP over IP while a few older analog units reach the NVR through a capture card—so the program has to accept either type without manual re-configuration. For product recognition I care only about groceries; no clothing or electronics labelling is necessary. The model should be trained (or fine-tuned) on the most common supermarket items so false positives stay low even when shelves are crowded. Key expecta...

I’d like to turn my stock-market ideas into an AIML pattern–driven trading bot that can watch live prices, analyse them on the fly, and place orders automatically while staying within clear risk limits. The core logic must be written around AIML so that trading rules can be updated simply by editing or adding patterns rather than rewriting code. Scope • Data feed & brokerage connection: connect to reliable real-time stock quotes and an API that allows live order execution. • AIML engine: ingest my pattern files, match market conditions, and trigger buy/sell signals. • Strategy design: please propose robust, back-testable strategies suitable for liquid equities; optimisation and walk-forward testing are expected. • Risk layer: position sizing, st...

I need a seasoned statistician who can move comfortably between classical regression techniques and modern Convolutional Neural Networks. The project centres on predictive analytics: you will build, compare and explain regression-based models, explore where a CNN adds value, and present the insights through clear, publication-ready visualisations created in Python (think pandas, scikit-learn, TensorFlow/Keras, matplotlib, seaborn or Plotly—use what fits best). We will begin with a brief video call so I can walk you through the dataset, the business question and the success metrics. After that, you will take full ownership of data preparation, model selection, training, validation and visual storytelling. Expect to hand back clean, well-commented notebooks and graphics that a non-tec...

I need an expert in Python to help with data analysis and processing tasks, specifically focused on unstructured data such as text or images. The ideal candidate should be proficient in Python libraries and tools designed for handling unstructured datasets. Your role will involve creating scripts or solutions to extract insights, patterns, or other relevant analyses from the data provided. If you have a strong command over libraries like Pandas, NumPy, or specialized tools for text and image processing, I’d love to hear from you.

I need a working proof-of-concept that hardens my wireless network by analysing live traffic and flagging hostile activity the moment it appears. The model must reliably catch the attacks that worry me most: Denial of Service (DoS), Man-in-the-Middle (MitM) intrusions, classic packet sniffing, and ARP spoofing. Everything has to run in real time on a modest on-prem machine, so efficient feature extraction and lightweight inference are a priority. The task breaks down naturally into three parts. First, capture and label representative WLAN traffic—public datasets are fine as a starting point, but I also want a small tool that lets me pipe raw pcap streams into the training set so the system can learn my network's quirks. Second, build and train the detection engine: a well-comme...

I am assembling a full-stack solution that ingests live financial databases, open-source macroeconomic feeds, and user-submitted figures, then turns all of it into forward-looking insights. The core of the product is an AI layer that delivers predictive analytics and runs configurable scenario simulations; the results need to surface instantly inside an intuitive web dashboard where users create and save their own reports and visual layouts. What I need from you is an end-to-end build: • Data layer – connectors that automatically pull structured and unstructured data from the three source categories above, plus a storage design that can scale as historical records grow. • ML & simulation engine – time-series forecasting models, Monte Carlo or agent-based simula...

Proposal using CRISP-DM (not coding): •Describe problem, data, prep, modeling, evaluation •When doing Data analysis, add before and after measurement per company •Use this survey to extract the data structures and the data lookup: •Generate random dataset with 1000 records for the form shown at open-dma link above. Strictly from what the form offers!!! Generate Before and then a After dataset (a separate one with improved results). Save it to excel as and •Process the data in python •Create a function in python that will generate individual reports (word or PDF format) – sample 5 reports (for delivery), not 1000 and produce them as files. •Create visuals for the web report or individual reports as needed. •Elaborate any correlation between ...

Hiring: AI Bot Development Company – Truck Valuation System (AU-Based Company) We are an Australian-based company seeking an experienced AI development company to build an intelligent AI bot capable of performing truck valuations. Project Overview: We require an AI-powered solution that can accurately assess and estimate the market value of trucks based on various data inputs such as make, model, year, condition, mileage, location, and current market trends. Key Requirements: Development of an AI bot capable of automated truck valuations Integration with market data sources and historical sales data Ability to continuously learn and improve valuation accuracy User-friendly interface (web-based or API integration) Secure data handling and compliance with Australian data standards E...

This project will create an end-to-end, AI-powered email delivery system for a U.S. client. All work must be carried out on-site or remotely from New York State; residency is a strict requirement because of data-handling policies. Scope of work The core task is to design, train, and deploy a regression-based machine-learning model that predicts optimal email-send parameters from rich transactional data. I will supply secure access to the historical transaction logs; you will architect the data pipeline, engineer the relevant features, and iterate on model performance until it is production-ready. Once validated, the model should be wrapped in an API and integrated into our existing email infrastructure so it can trigger personalized sends automatically. Key responsibilities • Da...

I need an end-to-end deep-learning model that can pick out identical human faces across images and video in real time. The core requirements are straightforward: • Detect every human face in an image or live stream, draw accurate bounding boxes, then compare each face against a gallery to decide whether it is an identical match. • Serve three environments without extra rewrites: security-grade CCTV feeds, social-media style mobile uploads, and large photo-management archives. • Deliver low latency on a single modern GPU while still running acceptably on CPU-only hardware for lightweight deployments. I’m comfortable with either PyTorch or TensorFlow/Keras; use the framework you know best. A pre-trained backbone such as ResNet, MobileNet, or Vision Transformer is...

I need a working, proof-of-concept framework that ingests live and historic network traffic logs, learns from them in near-real time, and flags malicious patterns before they escalate. The core must combine traditional threat-intel techniques with machine-learning pipelines so the system continuously adapts as new data arrives. Here’s what success looks like to me: • A modular data-collection layer that can stream pcap, NetFlow, or similar log formats into a preprocessing engine. • Feature-engineering and model-training code written in Python (feel free to leverage Pandas, scikit-learn, TensorFlow, PyTorch—whatever best suits the task). • A detection component that scores incoming traffic and raises alerts via a simple REST API or CLI output. • Cl...

I'm looking for someone to develop an App similar to Cal Ai, SnapCalorie and Qalzy. I work in the fitness industry and would like to sell the app to online customers. If you think you can develop something similar, please reach out and we can discuss the details.