Syväoppiminen Jobs

I have a curated set of roughly 700 post-operative periapical X-rays taken after root canal treatments by dental students. I need a computer-vision model, built in Python with TensorFlow or PyTorch, that can automatically assess each case and return two outputs: • a numeric score that can be used in our grading spreadsheet, and • a concise feedback report highlighting strengths and mistakes. The evaluation must cover the accuracy of the root-canal pathway, cleanliness of the treated area, and overall completion quality. I will provide a detailed rubric with additional sub-criteria so the model can translate radiographic findings into tutor-style comments. Your job is to design, train, and validate the model, then package an inference script that accepts a single X-ray or...

I need a fully working supervised learning model built from scratch, trained on my data, and delivered with clean, well-commented code. Although the focus is supervised learning, I also want to explore a clustering approach for initial data exploration and feature engineering, so the workflow should accommodate both phases gracefully. Here’s what I expect: • A brief, plain-English plan outlining the supervised objective (classification or regression, as appropriate once we review the dataset) and how clustering will support data insights. • End-to-end code in Python, preferably using scikit-learn, pandas, NumPy, and (if deep learning proves beneficial) TensorFlow or PyTorch. • Reproducible training pipeline: data loading, preprocessing, feature engineering, model...

I run a highly successful U.S.-based IT staffing firm that has flourished since 2000, and it is time for us to add a robust, agent-centric AI/ML capability across the organisation. I need an expert who can design and deliver an online, intensive programme that upskills our current employees and future employees in three core domains—Python, machine-learning algorithms, natural-language processing, and computer vision. Most importanty enable them to become powerful Agentic Developer or Lead Agnetic Developers—while introducing the latest agentic development patterns that tie them all together. Here is what I am looking for: • A practitioner-level curriculum that moves quickly from fundamentals to production-grade agent frameworks (think LangChain-style tool orchestration...

I'm looking for an AI expert to develop specialized software with image recognition capabilities, specifically focused on face recognition. Key Requirements: - The software must accurately recognize and process faces in various conditions. - Ideally, it should be able to identify individuals, but I'm open to suggestions based on your expertise. Skills and Experience: - Expertise in AI and machine learning - Strong background in image recognition technologies - Experience in developing robust and accurate face recognition systems - Proficiency in relevant programming languages (e.g., Python, TensorFlow) - Previous projects in similar domains would be a plus Please share your relevant experience and approach to this project.

I need a robust YOLO model that spots vehicles with high accuracy. Because I do not yet have a labeled dataset, the job begins with sourcing or capturing varied vehicle images and annotating them in classic YOLO format. Once the dataset is in place, the next step is to train and validate the network—YOLOv5 or YOLOv8 are both fine as long as the final mAP holds up under real-world conditions. Please apply best-practice augmentation, tune hyper-parameters, and track training with clear metrics so I can reproduce the results later in PyTorch. Deliverables • Curated and fully annotated vehicle image dataset (bounding-box labels in YOLO txt format) • Trained YOLO weights and configuration files • Short report summarising dataset composition, training settings, and ev...

I want to push AI beyond conventional data science by weaving arcane principles into its learning loop. My main focus is using arcane magic in AI learning, and the concrete goal is to enhance AI capabilities in a way that can ultimately be patented. The assignment is twofold. First, capture and translate specific occult concepts (sigils, correspondences, ritual structures, energetic patterns) into a machine-learning friendly form. Second, show how my practice of controlled heat regeneration in the body can be measured and streamed back as a live feature that influences model behavior, giving the system a science-meets-powers edge. Deliverables • A concise theoretical framework that links named arcane elements to established ML techniques, written in a style suitable for a patent sub...

I need a turnkey, camera-based solution that automatically counts plastic totes as they move through the rear door of each of my 100 refrigerated trucks. The goal is simple: every tote that goes in or out must be logged accurately without asking the driver to press a button, scan a tag, or slow down the loading process. Miscounts today cost real money; the new system must work in the messy, unpredictable environment of an active loading dock, not in a lab. Environment & constraints • Lighting varies from bright daylight to total darkness inside the trailer, and weather changes constantly when the door is open. • Drivers may step in front of the lens, so brief occlusion is inevitable. • Totes often travel in stacks of two to five, so the software has to identify an...

Project Description: We are looking for an experienced PyTorch optimization expert to accelerate the DOVE (Video Super-Resolution) model. The goal is to achieve an end-to-end inference speedup of 1.5x to 1.8x using strictly training-free methods. Acceptable Optimization Techniques (Training-Free only): You are free to explore and combine the following training-free approaches: Token-level routing, Token Merging (ToMe), or Token Pruning. Post-Training Quantization (PTQ). Attention simplification (e.g., efficient attention mechanisms). Coordination/Synergy optimization between VAE and DiT. Core Requirements: Target Model: DOVE (Repository: ) Acceleration Target: 1.5x - 1.8x end-to-end inference speedup. Hardware Baseline: The speedup must be achieved and evaluated on a high-end NVID...

**PROJECT DOCUMENT: FREELANCER REQUIREMENT – ANPR SDK DEVELOPMENT** Development of Offline ANPR (Automatic Number Plate Recognition) SDK Project Objective: To develop a high-performance, offline ANPR SDK capable of real-time license plate detection and recognition from IP camera streams, optimized for Indian road conditions. **Project Scope:** The selected freelancer/team will be responsible for designing and developing a modular ANPR SDK that can be integrated into edge devices or local servers. The SDK must process live RTSP streams and provide structured outputs via APIs. **Functional Requirements:** 1. Real-time video stream processing (RTSP / IP cameras) 2. Vehicle and number plate detection 3. Character segmentation and OCR 4. Output structured data: * Vehicle numbe...

I’m looking to develop an end-to-end machine learning application focused on classification. The core objective is straightforward: feed the model with curated data, train it to distinguish between the defined classes, and expose the resulting predictions through a clean interface or API that I can plug into my existing workflow. You’ll be free to select the most appropriate algorithms—whether that ends up being a tried-and-true random forest, gradient boosting, or deep-learning architecture—as long as the final system is accurate, explainable where possible, and easy for me to retrain when fresh data comes in. I value clear, commented code (Python preferred), a concise README, and a demonstration notebook or script that shows how to prepare the data, fit the model...

I'm seeking experienced ML/AI engineers for a development project. The primary task will be model training and tuning. Key Requirements: - Expertise in ML/AI frameworks (TensorFlow, PyTorch, etc.) - Experience with model training and hyperparameter tuning - Strong background in data processing and cleaning - Familiarity with algorithm development Ideal Skills: - Advanced knowledge in machine learning algorithms - Proficiency in Python and relevant libraries (scikit-learn, pandas, etc.) - Problem-solving skills and ability to work independently - Good communication skills for collaboration Please provide relevant experience and approach to the task.

I need a straightforward desktop application built in Python that can spot two key classes—Person and Mobile—in a sample video and draw clear bounding boxes with the class name over each detection. This is purely for demonstration and learning, so the implementation should stay clean and easy to read, ideally relying on OpenCV together with a pre-trained YOLO model (v5, v8, or any recent weight file you are comfortable with). How the app should behave • Load a local MP4 (or similar) sample video. • Run real-time inference frame-by-frame, highlighting every detected person or mobile phone. • Display the processed video in a simple desktop window; no fancy UI is needed beyond the live frame and the FPS readout. • Keep all dependencies to standard libr...

Hi, I am looking for a basic AI object detection demo. Requirement: - Detect common objects like person, bottle, mobile, etc. - Should work using webcam or sample video - Output should show bounding boxes with object names This is mainly for learning/demo purpose, so it doesn't have to be very advanced. Preferred: - Python with OpenCV or any simple framework - Basic explanation of how it works Deliverables: - Working demo (video or live) - Source code - Short explanation Budget is limited, but if work is good, I may come back with more tasks. Thank you.

I’m putting together a deep-learning workflow that can read MRI scans and immediately show why it reached each conclusion. The core of the job is to train a high-performing model on my MRI dataset and then weave in SHAP for feature-level interpretation and Grad-CAM for pixel-level heat-maps. The system needs to surface three kinds of insight for every study that runs through it: • a clear diagnosis justification that highlights the decisive regions of each image, • tailored treatment recommendations drawn from the predicted class probabilities, and • patient-specific risk factors ranked by SHAP values. I already have raw MRI images and basic labels; you would handle the full pipeline—from preprocessing and augmentation through model tuning, inference,...

Busco un desarrollador o arquitecto de soluciones de IA con experiencia comprobable en la implementación de agentes de voz automatizados de baja latencia. El objetivo es gestionar un volumen de 5,700 llamadas mensuales (aprox. 28,000 minutos) de forma eficiente y con costos de infraestructura optimizados. Requerimientos Técnicos (Stack Obligatorio): Para este proyecto, NO buscamos soluciones cerradas (tipo Vapi o Retell). Queremos una arquitectura basada en componentes que nos permita escalar sin márgenes excesivos por minuto. El candidato debe dominar: Orquestación: LiveKit o similares para el manejo de WebRTC y transporte de audio. STT (Speech-to-Text): Deepgram (Nova-2) por su baja latencia. LLM (Cerebro): Implementación vía Groq (usando Lla...

I need an experienced deep-learning engineer who can move fast to build a production-ready image-classification model. The system must take raw images, preprocess them, and reliably return the correct class label with clear confidence scores. Because I’m aiming for deployment straight away, please structure the code so I can drop it into a REST or gRPC service later. You are free to choose the framework you’re most comfortable with—TensorFlow, PyTorch, or another modern library—as long as the final solution is reproducible on a single high-end GPU. Expect to work with a labelled dataset of roughly 100k images; if additional augmentation or cleaning pipelines are needed, include them in your approach. Accuracy matters, but I’m also watching inference speed, so...

I need an Ubuntu 24.04 virtual machine running on VMware to pick up my NVIDIA card so I can run machine-learning workloads. The job is purely the installation and configuration of everything required for the guest OS to recognise and fully utilise the GPU (nvidia-smi must work). Key points • VMware host is already installed and stable; you decide whether PCI passthrough, vGPU or another VMware feature makes most sense. • Inside the VM I will need the correct NVIDIA driver, CUDA toolkit and cuDNN ready for TensorFlow or PyTorch later on. • Once complete I should be able to launch a quick test script that confirms the GPU is visible from within Ubuntu. Deliverable A step-by-step session (screenshare or detailed command log) that leaves the VM running and the GPU oper...

I already have a complete image-based dataset and now I want a robust Convolutional Neural Network built around it. I need your help choosing or designing the right architecture, training it from scratch or with transfer learning, and then packaging the finished model so I can reuse it easily for inference. You can work in TensorFlow/Keras, PyTorch or any modern deep-learning stack you prefer—as long as the code is clean, well-commented and fully reproducible. At the end I expect: • Source code for preprocessing, training and evaluation • Trained model weights plus a simple predict/inference script • A concise report of the hyper-parameters you settled on and the metrics you achieved on my hold-out data If something in my dataset format needs adjustment, let m...

Saya ingin memperdalam keahlian Analisis Data dengan fokus pada Pembelajaran Mesin untuk Pemrosesan Bahasa Alami (NLP). Saya mencari seorang mentor berpengalaman yang dapat membimbing saya secara terstruktur, praktis, dan bertahap hingga saya mampu membangun model NLP sederhana secara mandiri. Lingkup kerja yang saya bayangkan: • Merancang kurikulum mingguan yang mencakup dasar-dasar statistik, pembersihan & vektorisasi teks, word embeddings, model klasik (Naïve Bayes, SVM) hingga model neural network modern seperti LSTM, Transformer, dan BERT. • Mengadakan sesi daring terjadwal (±1–2 jam tiap pertemuan) dengan kombinasi penjelasan konsep dan live coding menggunakan Python, Pandas, scikit-learn, serta PyTorch atau TensorFlow. • Menyiapkan tugas pra...

I’m looking for an agile researcher who can jump between Machine Learning, Deep Learning, Computer Vision and core Electrical Engineering work without missing a beat. Most of what I send your way will sit at the intersection of data-driven algorithms and classic engineering analysis: think rapid literature scans, model prototyping in Python (TensorFlow / PyTorch), quick-turn MATLAB or Simulink simulations, and concise technical write-ups that translate results into clear engineering insights. The project stream is firmly rooted in Electrical Engineering, so an ability to frame ML findings in terms of circuits, signal behaviour, power-system performance or similar contexts is essential. Speed matters—I often need same-day clarifications or iterative tweaks—yet I never com...

The project centers on building a production-ready TensorFlow 2.x model that classifies tabular data delivered to us through an internal API. I have the API specifications and sample payloads ready; you will turn those streams into a clean training pipeline, engineer the right features, and iterate until the classifier meets our performance targets in real-world tests. Scope of work • Data pipeline – pull the API data, handle preprocessing, and produce TensorFlow-friendly datasets for train/val/test splits. • Model development – design, train, and tune a deep learning architecture suitable for tabular inputs (e.g., wide & deep, Transformer, or other proven structures). • Optimization – experiment with hyperparameters, regularization, and callback...