Object Detection on Custom Dataset with YOLO - Fine-Tuning with PyTorch and Python Tutorial
Fine-tune YOLO v5 for custom object detection using PyTorch. Learn model installation, training, evaluation, and application on a clothing dataset.
Neural Network Programming - Deep Learning with PyTorch
Learn to build and train neural networks using PyTorch, covering tensor operations, CNN architecture, data preparation, training loops, and performance optimization techniques for deep learning projects.
Python Is Weird
Explore Python's quirks and lesser-known features, from the walrus operator to string interning, in this engaging tutorial that challenges your understanding of the language.
Learning Machine Learning Efficiently
Discover an efficient approach to learning machine learning, exploring the landscape, optimal paths, and practical strategies for mastering this complex field.
Custom Audio PyTorch Dataset with Torchaudio
Learn to create a custom audio dataset using PyTorch and torchaudio, focusing on the UrbanSound8K dataset. Explore basic I/O functions in torchaudio and implement essential dataset class methods.
Diffusion Models - PyTorch Implementation
Learn to implement and train diffusion models in PyTorch, covering unconditional and conditional versions, classifier-free guidance, and exponential moving average. Gain hands-on experience with state-of-the-art generative AI techniques.
How to Train Object Detection Transformer on Custom Dataset
Learn to train Object Detection Transformers using DETR, from environment setup to custom dataset training and model evaluation. Covers PyTorch, COCO datasets, and PyTorch Lightning for efficient deep learning workflows.
Stanford Seminar - Fastai: A Layered API for Deep Learning
Explore fastai, a deep learning library offering high-level components for quick results and low-level components for research flexibility, built on a layered architecture with Python and PyTorch.
Automatic Image Captioning with Vision Transformer and GPT-2
Learn how to generate descriptive captions for images using Python and PyTorch in this 16-minute tutorial. Explore the process of automatic image captioning with the pre-trained 'nlpconnect/vit-gpt2-image-captioning' model from Hugging Face. Set up the V…
Scaling AI in Production with PyTorch
Learn to scale AI in production using PyTorch, covering resilient distributed platforms, TorchServe, and strategic partner initiatives for a robust ecosystem.
Data and Machine Learning at League of Legends
Explore unique data challenges in video games, focusing on model deployment and evolving ML stacks in League of Legends since 2009.
Machine Learning Tools: Skyline and RL-Scope for Performance Optimization
Explore Skyline and RL-Scope, two innovative tools for optimizing machine learning performance. Learn about interactive profiling, visualization, and debugging for PyTorch networks and cross-stack profiling for deep reinforcement learning.
Leaner, Greener and Faster PyTorch Inference with Quantization
Explore PyTorch quantization techniques to optimize neural networks, reducing size and improving speed without sacrificing accuracy. Learn implementation strategies and real-world applications.
Finding Training Inefficiencies with CentML DeepView
Optimize deep learning model training with DeepView. Gain insights into performance bottlenecks, enhance resource utilization, and achieve significant throughput improvements through intuitive visualizations and targeted optimizations.
Scale and Accelerate Distributed Model Training in Kubernetes Clusters
Orchestrate and accelerate distributed deep learning workloads across multiple GPUs and nodes using Kubernetes, Kubeflow PytorchJob, RDMA, RoCE, and SRIOV for near-linear performance scaling.
DIY AI: Build and Train Your Own Model with PyTorch
Dive into building and training a custom AI model using PyTorch, Python, and Jupyter Labs. Learn step-by-step techniques to create a deployable model for Raspberry Pi or other computers.
Deep Learning With TensorFlow
Learn TensorFlow basics, deep learning concepts, and practical applications through comprehensive tutorials and hands-on projects. Explore neural networks, computer vision, and natural language processing.
Understanding the Machine Learning Process and Embedding Models into Apps
Learn to build ML models with Azure ML and VS Code, operationalize them in apps, and implement MLOps practices. Covers PyTorch Lightning, model prediction, and integration with DevOps and Kubernetes.
AI Show Live - PyTorch Enterprise
Explore PyTorch Enterprise on Azure with Alon Bochman: Learn about the collaboration, features, and benefits of this exciting announcement from Microsoft's AI Show Live.
Intro to PyTorch Tutorial - Building Fashion Recognizer
Learn to build a fashion recognizer using PyTorch in this hands-on tutorial. Covers core functionality, network architecture, loss functions, optimizers, and TensorBoard integration for effective model training.
Get Started with PyTorch
Explore PyTorch's fundamentals, from data handling to model building and deployment. Learn about its unique features, strong community, and ecosystem for effective deep learning development.