머신 러닝 (ML) Jobs

I want my Windows-based PC ready to build and release Flutter apps to Google Play. Nothing is installed yet, so I’ll need the full environment put in place—from downloading the Flutter SDK to configuring every path variable and Android tool. Once everything is up and running, I’d like to run a clean test project, generate a signed AAB, and verify that it passes Play Store checks. Because the app I’m planning will rely on some AI features, please also make sure any common AI/ML plug-ins (e.g., TensorFlow Lite or other Dart packages you recommend) compile cleanly in the new setup. Deliverables • Flutter SDK, Android Studio, and required Android SDKs installed and linked in PATH • Working device/emulator configuration for debugging • Keystore...

I am competing in a HackerEarth data-science contest and I want to push my score into the top tier of the leaderboard before the challenge closes next month. I have already set up the competition workspace and can grant you immediate access to the dataset, rules, and current public-leaderboard baseline. Here is what I need from you: build, tune, and iterate a high-performing regression model, supply well-commented code (Python is preferred, but you are free to choose the stack you are fastest with), and hand over a prediction file ready for final submission. Along the way, please keep a concise notebook or script that allows me to reproduce your workflow end-to-end on my own machine. In your bid, include links or brief summaries of past work that demonstrate strong results in similar com...

Quiero sacar el máximo partido al kit Grove Vision AI v2 unido a un microcontrolador XIAO para ejecutar reconocimiento facial directamente en el borde. El sistema debe funcionar al aire libre, en plena naturaleza, de modo que la latencia sea mínima y no dependa de la nube. Ademas el dispositivo al reconocer en el entorno natural debe ser capaz de enviar la información en tiempo real ya sea a una pagina web o dispositivo movil, tambien debe ser capaz de generar imformes con los datos recopilados. Cuento con un conjunto de imágenes de fauna silvestre que servirá como dataset de entrenamiento; necesito tu ayuda para limpiar ese material, entrenar el modelo y convertirlo al formato óptimo para el Grove Vision AI v2, asegurando que corra con la memoria...

Brain disorder detection using Deep Learning Uses MRI brain scan images Detects multiple brain diseases automatically Early disease detection and diagnosis Multi-class classification system Diseases detected: Glioma tumor Pituitary tumor Meningioma tumor Alzheimer’s disease Healthy brain Uses Convolutional Neural Networks (CNN) Uses Transfer Learning techniques Models used: CNN VGG16 ResNet50 Dataset collected from Kaggle MRI datasets Combined brain tumor and Alzheimer datasets 1000 images used for training 250 images used for testing Image preprocessing and normalization Pixel values converted from 0–255 to 0–1 Feature extraction using convolution layers Pooling layers reduce computation Fully connected layers perform classification Softmax activation used for multi-clas...

Enhance scripting agent to support playwright and Filter out any code or PII data from sending to LLM I have an in-house AI agent that Identifying code updates and new feature additions and update the k6 and selenium scripts or create new scripts accordingly . however, The project is partially developed, it creates selenium, k6 and loadrunner scripts and deployed in aws bedrock agent core runtime . we need to add playwright and make the overall solution more robust to support complex flows like journey flows in the script . Your task is to create a new agent so it watches a codebase , create k6 , loadrunner, selenium and playwright scripts for new functionality or update any existing scripts to add new functionality mentioned above . Filter out any code or PII data : GitHub R...

I'm seeking a tutor for computational image processing and data-driven methods (machine/deep learning), specifically for my biomedical engineering coursework. I'm looking for assistance in: - Image segmentation - Feature extraction - Image registration - Binary images - Image transforms The exam is mathematical and theoretical. Ideal skills and experience: - Expertise in computational image processing - Proficiency in data analysis, visualization, and statistical methods - Excellent teaching and communication skills Looking forward to your expertise!

Hiring: ML Engineer – Test & Learn Platform Experience: 3+ Years Location: Remote (1–2 visits to Bangalore required) Salary: ₹40,000 – ₹50,000/month --- Role Overview: We are looking for an ML Engineer to build and scale experimentation and causal inference systems. You will work on statistical engines, APIs, and cloud-based pipelines to enable data-driven decision-making. --- Key Responsibilities: - Develop ML/statistical models (DID, Synthetic Control, A/B Testing) in Python - Build and integrate FastAPI-based services - Design large-scale data pipelines using PySpark, Delta Lake, and Azure Data Lake - Optimize Spark jobs (memory, partitioning, performance tuning) - Work with Databricks for job orchestration and data workflows - Containerize and deploy applica...

1. Smart CT Scan Analyzer An AI system that analyzes lung CT scan images and detects possible lung cancer signs early. Main Features Upload CT scan or X-ray images AI detects lung nodules Cancer risk prediction Heatmap highlighting suspicious areas Doctor dashboard Patient history tracking PDF medical report generation Technologies Frontend: Vue.js / React Backend: Node.js or Python Flask AI Model: TensorFlow / PyTorch Database: MySQL / PostgreSQL Image Processing: OpenCV AI Models CNN (Convolutional Neural Network) ResNet50 YOLO for object detection Users Doctors Radiologists Hospitals Patients 2. AI + IoT Lung Monitoring System A smart healthcare platform connected to wearable devices. Features Real-time breathing monitoring Oxygen level tracking AI predicts lung disease risk Emergen...

I’m putting together a series of concise, hands-on learning guides that walk readers through Artificial Intelligence, Blockchain, and Cloud Computing. Each guide should be written (or recorded, if you prefer video) by someone who already works at an advanced level in that field and can translate complex concepts into clear, actionable steps. Scope • Three stand-alone guides—one per topic—covering fundamentals, real-world applications, and a mini project or demo that readers can complete on their own. • Practical focus: code snippets, architecture diagrams, or workflow screenshots where relevant. • Tone: friendly but authoritative, suitable for professionals looking to upskill quickly. Acceptance criteria 1. Depth matches senior-level understandi...

Cancer Detection Using Machine Learning ## Project Overview I have developed a Machine Learning based Lung Cancer Detection system that predicts the likelihood of lung cancer using patient medical parameters and data analysis techniques. This project is suitable for: * Final year engineering students * Academic submissions * Research work * Machine Learning learning purposes * Healthcare AI projects ## Features * Data preprocessing and cleaning * Exploratory Data Analysis (EDA) * Machine Learning model training and testing * Accuracy evaluation and prediction system * Visualization graphs and reports * Easy-to-understand code structure * User-friendly implementation ## Technologies Used * Python * Scikit-learn * Pandas * NumPy * Matplotlib * Jupyter Notebook ## Deliverables * Com...

We are looking for a hands-on Senior Computer Vision Architect to scale our live multi-camera video analytics platform from 100 to 1,000+ cameras across NVIDIA DeepStream and distributed edge device architectures. The ideal candidate must have strong production experience with NVIDIA DeepStream SDK, TensorRT optimization, edge AI deployments, and large-scale camera infrastructure. Responsibilities: • Design and manage a scalable 1,000-camera architecture with high availability and low latency • Optimize DeepStream pipelines (NvInfer, NvTracker, NVDEC, GStreamer) for stable FPS under heavy load • Deploy an manage CV models on Jetson or equivalent edge devices • Fine-tune YOLO models and export optimized TensorRT engines • Build and improve infrastructure using Doc...

# Lung Cancer Detection Using Machine Learning ## Project Overview I have developed a Machine Learning based Lung Cancer Detection system that predicts the likelihood of lung cancer using patient medical parameters and data analysis techniques. This project is suitable for: * Final year engineering students * Academic submissions * Research work * Machine Learning learning purposes * Healthcare AI projects ## Features * Data preprocessing and cleaning * Exploratory Data Analysis (EDA) * Machine Learning model training and testing * Accuracy evaluation and prediction system * Visualization graphs and reports * Easy-to-understand code structure * User-friendly implementation ## Technologies Used * Python * Scikit-learn * Pandas * NumPy * Matplotlib * Jupyter Notebook ## Deliverables...

I’m building a mobile experience that lets a user pick a picture from their gallery and instantly discover who’s in it and how they feel. Think of Sherlock-style intelligence focused on faces and emotions, but built natively for Android first, with a clean, modern interface that will later scale to iOS. Here is the flow I need implemented end-to-end. A user opens the app, chooses a photo stored on the device, the image is uploaded securely to the cloud, an AI model analyses faces, detects their emotions, and returns the findings in seconds. Results should appear in an elegant card-based UI that feels at home on recent Material guidelines. All design work, backend APIs, AI model integration, security (encryption in transit and at rest), and Play-Store-ready build are part of t...

Core required Senior full-stack web — TypeScript, Node, React, Vite, Express, Drizzle, SQLite/Postgres Multi-tenant SaaS architecture — auth (OAuth/JWT), user namespacing, row-level access control, SQLite → Postgres migration Payments and metering — Stripe (or adult-friendly equivalents like CCBill, Segpay, Epoch), subscription webhooks, credit systems, per-feature usage metering GPU infrastructure / ML ops — RunPod, Modal, Replicate, or Kubernetes + bare-metal GPU; queueing, autoscaling, cold-start handling, retry/backoff ComfyUI — workflow JSON editing by node ID, custom node management, model file management, VACE for face swap Media storage and delivery — S3 / R2, CDN (CloudFront / ), signed URLs, retention policies FFmpeg / video pipeline &mda...

I want a working prototype of a truly pocket-sized gadget that can run completely offline. The flow is straightforward: a standard-resolution camera captures a printed or handwritten question, an on-board OCR module extracts the text, a lightweight language model generates a full textual answer, and the reply appears on a small built-in screen. No cloud calls, no external power brick—everything must live inside the device itself. I am open on the exact OCR library; Tesseract OCR is the obvious first choice, but if you have a lighter or faster alternative that will compile on something like a Raspberry Pi Zero 2 W, an ESP32-S3, or any comparable single-board solution, I’m happy to discuss it. For the AI model, please keep it compact (e.g., TensorFlow Lite, ONNX, or similar) s...

I need a self-contained Python pipeline that runs on a Raspberry Pi, grabs an image from the Pi Camera, extracts any text it finds in the picture, sends that text to a lightweight AI function, then shows the AI’s short answer on a small SPI/I²C OLED display. Scope of work • Capture: Trigger the Pi Camera (libcamera or picamera2) and save a frame. • OCR: Use Tesseract, EasyOCR, or another open-source library to read text from the image. The input is always “text from images,” never scanned PDFs or live handwriting. • AI logic: Pass the recognised string to a simple question-answer routine (OpenAI API, Llama .cpp, or any efficient model you prefer) and return a concise, single-sentence reply. No lengthy explanations are needed. • Display: P...

I need an AI agent focused on trading execution. This agent will operate on the Nse employing a day trading strategy. Key requirements: - Execute trades based on AI-generated signals - Analyze market trends in real-time - Adapt to fast-moving market conditions Ideal skills and experience: - Expertise in AI and machine learning - Strong understanding of the NSE and day trading dynamics - Proven track record in developing trading algorithms I'm looking for a developer who can create a reliable and efficient AI trading agent.

# Lung Cancer Detection Using Machine Learning ## Project Overview I have developed a Machine Learning based Lung Cancer Detection system that predicts the likelihood of lung cancer using patient medical parameters and data analysis techniques. This project is suitable for: * Final year engineering students * Academic submissions * Research work * Machine Learning learning purposes * Healthcare AI projects ## Features * Data preprocessing and cleaning * Exploratory Data Analysis (EDA) * Machine Learning model training and testing * Accuracy evaluation and prediction system * Visualization graphs and reports * Easy-to-understand code structure * User-friendly implementation ## Technologies Used * Python * Scikit-learn * Pandas * NumPy * Matplotlib * Jupyter Notebook ## Deliverables...

보다 자세한 내용을 확인하시려면, 회원 가입 또는 로그인 절차가 필요합니다.

I need Python code for data processing tasks. Essential requirements: - Proficiency in Python - Experience with data processing libraries (e.g., Pandas, NumPy) - Ability to write efficient, clean, and well-documented code - Problem-solving skills for complex data challenges Ideal skills: - Background in data science or analytics - Knowledge of data visualization tools - Experience with large datasets and performance optimization Looking for freelancers who can deliver high-quality, reliable code within budget. Please provide relevant work experience in your bids.

I want a concise, hands-on guide that shows me exactly how to wire Claude AI into live trading on Binance, Zerodha, and Hyper Liquid. The goal is to have a small but solid framework I can run this weekend, capable of fully automated trading and rapid order execution. Here’s what the guide must cover: • Exchange integration – authenticated REST/WebSocket connections for all three platforms, plus secure key handling. • Prompt design – how to feed real-time price data into Claude, preserve trading context, and let the model decide when to buy or sell. • Trigger logic – code examples for scheduled, time-based checks and immediate actions when specific market conditions occur. • Order execution – sample functions that submit, confirm, an...

I am building a research-grade pipeline that focuses first and foremost on Diabetic Retinopathy (DR) grading, while keeping an eye on downstream extensions such as DME detection, retinal biomarker discovery, longitudinal modelling, cross-dataset generalisation and explainable retinal AI. Data at hand • Thousands of colour fundus photographs sourced from OLIVES, MMRDR and my own curated set. • Structured patient medical history accompanying a subset of those images. Core objectives 1. Train and validate a model that assigns the correct severity level to every DR image. 2. Surface early-stage indicators that could alert clinicians before conventional thresholds are reached. 3. Provide per-patient progression tracking so that sequential visits can be plotted and foreca...

I need a software solution that uses machine learning to assess apple quality, bruising, and diseases through images. The software should be compatible with either Windows and MacOS, and images will be uploaded via a camera interface. Key Requirements: - Machine learning integration for advanced image analysis - User-friendly camera interface for image capture Ideal Skills and Experience: - Expertise in machine learning and image processing - Experience in developing cross-platform software applications - Strong background in computer vision Please provide samples of previous work in similar domains.

We’re Hiring! Data Scientist | The Red Arc Location: Remote We’re looking for a passionate Data Scientist with 0 to 1 years of experience to join our growing team at The Red Arc. If you enjoy working with data, uncovering insights, and building intelligent solutions that drive better decisions, this opportunity could be a great fit. What we’re looking for: 0 to 1 Years of experience Degree in BE, BTech, BSc, MSc, or a related field in Computer Science, Data Science, Statistics, or Mathematics Strong foundation in Python, SQL, and data analysis Experience with data visualization tools such as Power BI, Tableau, or similar Familiarity with machine learning concepts and libraries like Pandas, NumPy, Scikit-learn Understanding of data cleaning, feature engineering, and mode...

I need a specialist to turn my Windows-based PC into a robust, private AI workstation. The core stack will revolve around Python and must run Llama locally through AnythingLLM while remaining flexible enough to load additional models as they mature. Key capabilities I’m after: • Decades-worth of data ingestion: PDFs, Word files, full Office docs and .eml email archives. • Context retention so I can resume a conversation or analysis session days later without re-feeding content. • Open WebUI access for convenient, browser-based interaction. • Clean restart behaviour, automated backups, and a path to scale out if I later bolt on extra GPUs or move to a small on-prem cluster. I already have the hardware; you bring the know-how to configure, script, and do...

Hello everyone, I am a developer specialized in automation systems and AI Agents. I have created an advanced automated assistance system for WhatsApp, designed for companies, professionals, and businesses that want to respond to customers quickly, efficiently, and professionally. The system works as a configurable AI assistant: it can respond based on your FAQs, your documents, your business rules, and the communication tone you prefer. It can handle frequently asked questions, provide information about services, assist customers with common requests, and transfer the conversation to a human operator when needed. The bot can be instructed to: respond with a formal, friendly, or commercial tone; follow the information provided by the company; avoid invented responses; manage multiple la...

I am putting together a small educational AI/ML project that detects diabetic retinopathy on the publicly-available OLIVES dataset. The goal is not only to build a working multimodal model (fundus images plus any supporting clinical metadata you find useful) but also to showcase clear explainability and rigorous evaluation so the project can be presented in an academic setting. Scope of work • Prepare the OLIVES dataset, handle any class imbalance, and document the preprocessing pipeline. • Design and train a multimodal architecture of your choice in Python—PyTorch, TensorFlow or another modern framework is fine—as long as the code is clean and reproducible. • Produce the quantitative metrics I need: Accuracy, Precision, F1-score, AUC and Cohen Kappa on a ...

I aim to build an advanced, research-grade Virtual Try-On (VTON) engine that can realistically place Tops (e.g., shirts, blouses), Bottoms (e.g., pants, skirts), and Full outfits (e.g., dresses, suits) onto a human model from nothing more than a single 2-D photograph. The workflow should centre on state-of-the-art deep generative techniques—diffusion models, flow-matching, and transformer-based architectures—so the final renders look genuinely photo-realistic, preserve garment texture, and respect body pose and occlusion. The system will be trained on a curated dataset I already possess, then fine-tuned to accept JPEG and PNG uploads at inference time. Clean, modular PyTorch (or equivalent) code, a reproducible training pipeline, and inference scripts that run on a single high...

health project of teleconsultation with the use of many ai features (more details will be discussed later on)

I need to turn our written AI-governance policies into a practical software toolkit that can guide, track, and report on every stage of model life-cycle management. The focus is implementation strategy: instead of advising on rules or ethics, the brief is to build a brand-new solution that embeds those rules directly into day-to-day workflows. The core objective is a governance tool (web-based or modular API) able to: • capture and store model documentation and approval checkpoints, • enforce policy gates before data ingestion, training, and deployment, • generate audit-ready logs for internal and external regulators, • surface real-time risk metrics on model drift, bias, and performance. I already have high-level requirements, user stories, and sample policy text; wh...

AI Engineer / AI Agent Architect – ERP Platform (Java, MySQL, SaaS) NOTE - PLEASE READ JD CAREFULLY, ONLY APPLY IF YOU HAVE RELEVANT EXPERIENCE WHICH IS READY FOR REVIEW We are developing a multi-tenant ERP platform currently built as a Java Spring Boot application with MySQL as the database and Angular as the frontend. Objective of the Role Design and implement an external AI intelligence layer that integrates with our existing ERP to provide: Business analytics and dashboards Predictive insights and forecasts Alerts, reminders, and anomaly detection Conversational ERP intelligence (AI Copilot) ( Ex - Show me purchase order for may 2026 month having order value above 1,00,000 INR ) The AI must be ERP-aware, secure, tenant-isolated, and production-ready. Key Responsibilitie...

I need a Windows-based desktop application that guides single-specialty ophthalmology hospitals all the way to NABH 2nd Edition accreditation readiness. The core workflow is already mapped out: • Hospital onboarding – simple profile setup with basic facility data. • Secure upload of every “master” policy, SOP, register and record. • Automatic AI sorting of each file into the correct NABH 2nd Edition chapter. • Real-time gap analysis showing which standards lack evidence. • Dynamic list of missing or obsolete documents. • Context-aware CAPA recommendations the quality team can download or print. • One-click mock audit that simulates assessor questions and scores responses. • Readiness score with a dated PDF report to ...

I have a collection of general-purpose images and need a complete Python-based pipeline that extracts meaningful features and classifies each image accurately. The project centres on image feature extraction and subsequent classification, so solid experience with OpenCV, scikit-learn or a deep-learning stack such as TensorFlow or PyTorch is essential. You will begin by deciding on (and justifying) an appropriate feature strategy—traditional descriptors like SIFT/ORB, transfer-learning from a CNN, or another proven method—then train and validate a classifier that reaches reliable accuracy on a held-out test set. Clean, well-commented code and clear, reproducible training steps are critical because I need to retrain the model as new data arrives. Deliverables • Python sour...

I have a CSV that logs product sales alongside TV, Radio, and Newspaper advertising spend. I want a clean, reproducible Python workflow that turns this data into an accurate sales-forecasting model and a concise set of insights for decision-makers. The raw file contains a few gaps, so your first step is to inspect, clean, and appropriately impute missing values. Once the data is tidy, explore it with Pandas, NumPy, Matplotlib, and Seaborn to surface correlations and outliers. For modelling, start with a well-documented Linear Regression approach using scikit-learn. If you see a clear uplift from adding regularisation or polynomial terms, feel free to include that comparison, but keep the final deliverable focused on a model that is simple to interpret and easy to retrain. Deliverables ...

我准备上线一套面向居家场景的智能监测系统，希望通过视觉与物联网技术，及早发现老人或慢病人群的高危状况并推送告警。 核心需求 1. 高危动作异常 —— 同时精准识别“摔倒”与“跌倒”，第一时间触发报警。 2. 状态失能异常 —— 既要判断“长时间静止不动”，也要捕捉“无自主行为”状态，实现持续跟踪。 3. 出入与行为节律 —— 对家门进出时间、频次和时段进行建模，结合如厕频率、徘徊轨迹、家电使用等行为模式，挖掘偏离日常规律的征兆。 4. 生理体征 —— 基于微动信号提取呼吸、心率等指标，与个人基线比较后给出健康风险提示。 我期望的交付 • 场景与传感器选型报告：摄像头、毫米波雷达、惯性传感器等可行性分析。 • 算法与模型：包含数据清洗、特征工程、深度学习或传统 CV/信号处理方案，需给出训练脚本与推理 API。 • 功能性原型：可在本地或边缘端实时运行，界面展示告警信息，并通过 MQTT/HTTP 推送到后台。 • 技术文档：部署指南、接口说明、测试用例及关键性能指标（例如跌倒检测准确率、误报率等）。 理想人选 熟悉 OpenCV、PyTorch/TensorFlow 或 mmWave SDK，对人体姿态估计、时序异常检测有实战经验；能在 Linux + Docker 环境里快速迭代；对养老、康复或智慧家居项目有交付记录更佳。 请附上相关案例、模型效果或仓库链接，让我能快速评估你的解决思路和交付能力。期待与你合作，把这套居家安全“护身符”尽快落地。

I’m building a Python-driven, agentic system that leans on Anthropic’s Claude API to remove as much manual effort as possible from my day-to-day e-commerce operations. The core objective is process automation: I want autonomous code that can watch key events, decide what has to happen next, and execute the required steps without human intervention. Right now the priority is e-commerce automation—things like order lifecycle handling, inventory syncs, customer-service ticket triage, and routine report generation. The architecture will likely involve a mix of Claude function-calling, LangChain (or a similar framework), and robust error-handling so that every agent knows when to escalate and when to retry. Deliverables • Well-documented Python modules that expose cle...

I need a Python-based algorithm to assist with trading NSE options using real-time market data. Key Requirements: - Optimize trading strategies - Implement risk management Ideal Skills and Experience: - Expertise in Python - Experience with real-time market data - Strong background in options trading and algorithm development - Ability to create predictive models and optimize trading strategies Please provide a portfolio of similar work.

Goal: Create a FULLY AUTOMATED process that takes a male audio file and converts it into a female voice. What you must do: 1) Take the male audio I provide 2) Convert it into a female voice 3) Upload the final audio into a Google Drive folder 4) Add the Google Drive link in your competition entry 5) Explain clearly what software/tools you will use 6) Explain clearly how you will automate the FULL process from start to finish Important: - The automation must run locally - The final voice must sound perfectly natural and human - The female voice must correctly reproduce the multiple emotions, tone and intonations from the original audio - The result must NOT sound robotic or AI-generated - The automation must be able to process multiple audio files - Do NOT clean the original audio more...

Title: AI/LLM Evaluation Methodology Reviewer — Pilot Study Audit (NDA, fixed-price, single reviewer) We are commissioning a hostile-but-fair methodology review of an internal pilot study before we expand it or commission independent validation. We are NOT looking for friendly feedback. We are looking for the strongest critique you can write. THE STUDY (outlined only; full materials shared under NDA): A pre-registered empirical pilot benchmarking nine prompting conditions on a single frontier large language model across a small stratified sample. Scoring is performed by a heuristic automated scorer plus a single LLM-as-judge validation pass on a random sample. Descriptive statistics only. Approximately 6,000 words of manuscript plus supporting methodology documentation and r...

I’m expanding a successful three-year program that pairs senior global talent with high-paying US software positions, and I need experienced engineers who can step into live technical interviews on behalf of our candidates. You’ll join calls, showcase deep expertise, and help secure offers; once a role is landed you receive a share of the ongoing salary—commissions can reach 70 %, and you may handle several roles at the same time for compound earnings. What you’ll do • Conduct technical and system-design interviews for roles across full-stack, AI/ML, data-science, and gaming domains, adapting your answers to each client’s stack. • Coordinate with our support team; we handle identity verification and provide the clean remote environment you need ...

I want to roll out an on-premise AI assistant that becomes the first place my team turns whenever they need information. Its core jobs are clear: instantly search our file system, answer everyday work questions, and surface multimedia assets—especially images and videos—without leaving our secure environment. Typical requests it must handle: • “Find the latest Expo 2025 PR article.” • “Show me the apple-tea campaign photos.” • “Pull the internal training video on onboarding.” Scope of work 1. Index and retrieve data from shared drives and cloud buckets while respecting existing permissions. 2. Support conversational querying so the assistant can answer questions in natural language, not just return file paths. 3...

I already have a working fake-news detector built on Python, BERT and the Hugging Face Transformers stack, wrapped in a Gradio demo. What I need now is a sharper, more insightful explainability layer. The detector currently calls both LIME and SHAP, but the outputs are basic and not yet integrated into a cohesive, user-friendly display. Your mission is to give equal weight to LIME and SHAP, tighten the faithfulness of their explanations, and surface the results through the existing Gradio interface so that journalists, fact-checkers and everyday readers can immediately see which words or phrases are driving each prediction and why. Key goals • Refactor or fine-tune the current LIME and SHAP pipelines so they handle longer articles without timeouts or memory issues. • Align ...

I need an experienced trainer to run an on-site learning program that blends Generative AI, broader Enterprise AI concepts, and solid Product Engineering practices. The participants will be interns who already code at an intermediate level; they grasp fundamentals but need guidance turning that knowledge into production-ready, AI-enabled features. You should be fully conversant with modern GenAI workflows—prompt engineering, fine-tuning large models, evaluation, and deployment—and be able to frame those topics in a way that links directly to real-world product engineering cycles. If your background also covers classic machine-learning, natural-language processing, or deep-learning stacks, all the better; we want the sessions to feel connected to the wider AI landscape. De...

AI-Orchestrated Hospitality ERP: Real-Time Worker Dispatch & Predictive Demand Logic ​The "Complicated" Core Requirements ​To solve this, a developer needs to master three distinct, overlapping domains: ​The Geo-Spatial Dispatch Engine: ​Instead of a static "ticket" system, the AI must calculate the "Cost of Service" based on a staff member's current location (GPS) and their active task queue. ​Complexity: Implementing a real-time proximity-based assignment algorithm that prevents "worker burnout" by balancing the load automatically. ​Predictive Staffing (The ML Layer): ​The system shouldn't just react to guests; it should predict them. It needs to ingest historical booking data, local weather APIs, and event calendars to forecast "...

AI-Orchestrated Hospitality ERP: Real-Time Worker Dispatch & Predictive Demand Logic ​The "Complicated" Core Requirements ​To solve this, a developer needs to master three distinct, overlapping domains: ​The Geo-Spatial Dispatch Engine: ​Instead of a static "ticket" system, the AI must calculate the "Cost of Service" based on a staff member's current location (GPS) and their active task queue. ​Complexity: Implementing a real-time proximity-based assignment algorithm that prevents "worker burnout" by balancing the load automatically. ​Predictive Staffing (The ML Layer): ​The system shouldn't just react to guests; it should predict them. It needs to ingest historical booking data, local weather APIs, and event calendars to forecast "...

我正在搭建一套基于 YOLOv8 的垃圾分类演示，需要完整的软硬件方案： • 软 件 – 使用 Python + YOLOv8 训练/部署模型，能在普通电脑上直接运行； – 摄像头以 USB 方式接入树莓派，再把画面实时传输到电脑； – 识别目标包含：塑料、纸张以及易拉罐，模型应能在画面上框出目标并同时在终端输出中文文字描述（如“检测到易拉罐”）； – 运行界面可为简单命令行或轻量 GUI，只要识别结果与文字描述同步显示即可； – 提供完整的源代码、模型权重、依赖清单与一键安装脚本。 • 硬 件 – 树莓派主板（任意 3/4/5 型号均可）+ 原厂摄像头模块； – 摄像头默认 USB 连接，可在本地测试无误后将整套硬件打包寄送给我（运费我承担）。 • 交付要求 1. 远程演示识别过程，确认三类垃圾均能被准确框选并输出文字； 2. 打包代码与文档（环境配置、使用说明、模型训练思路）； 3. 寄送硬件并提供收件追踪号； 4. 收到设备后，如有环境差异需协助我本地跑通。 如果你熟悉树莓派、YOLOv8 和 Python 部署，并具备打包邮寄能力，期待与你合作！

I want to roll out an on-premise AI assistant that becomes the first place my team turns whenever they need information. Its core jobs are clear: instantly search our file system, answer everyday work questions, and surface multimedia assets—especially images and videos—without leaving our secure environment. Typical requests it must handle: • “Find the latest Expo 2025 PR article.” • “Show me the apple-tea campaign photos.” • “Pull the internal training video on onboarding.” Scope of work 1. Index and retrieve data from shared drives and cloud buckets while respecting existing permissions. 2. Support conversational querying so the assistant can answer questions in natural language, not just return file paths. 3...

I need a purpose-built quotation management system for OR Technology that lets my team work faster and with fewer errors. At a minimum the solution must let me create professional quotes, send them in just a few clicks, and revisit each one later to see whether it is pending, accepted, or expired—all while keeping client details in a single, searchable place. I am leaning toward a browser-based interface so sales staff can access it from any device, yet I am open to alternative platforms if you can show a clear advantage in speed, reliability, or long-term maintenance. The design should support separate workspaces for administrators, sales representatives, and, optionally, clients who may log in to view or approve their own quotations. To keep future changes straightforward, please...

I have a clean, ready-to-use dataset and now need a complete predictive analysis pipeline built around it. The job is straightforward: take my data, explore it, engineer the right features, train and tune an appropriate model, and hand back production-ready code that I can rerun whenever new records arrive. Python is my preferred language, and I’m comfortable with common libraries such as pandas, scikit-learn, XGBoost, TensorFlow or PyTorch—feel free to choose whichever stack best fits the problem once you’ve inspected the data. Please keep everything reproducible: a single script or notebook, a clear , and comments that explain why each step was taken. Acceptance criteria • End-to-end code executes without errors on my machine. • Model delivers a measurab...

I need a full-featured online matrimony platform whose heart is an intelligent recommendation engine that pairs members according to their personality traits. The goal is to go beyond the typical age-and-location filtering and offer users scientifically grounded, trait-driven matches they will actually relate to. Here is what I want delivered: • A secure web (and/or mobile-friendly) application where new members can register, create rich profiles, complete a personality questionnaire, and upload photos. • A matching algorithm that processes questionnaire results and continuously refines recommendations, automatically presenting a ranked list of compatible profiles to each user. • Standard user functions such as private messaging, interest/like buttons, and match histor...