AI Show - AI Playground & Cognitive Services Vision APIs
Explore Azure Machine Learning Designer, VS Code ML extension, and PyTorch basics with experts. Demystify ML and NLP concepts while learning about Cognitive Services and AI Playground development.
Learning Machine Learning with .NET, PyTorch and the ONNX Runtime
Explore machine learning with .NET, PyTorch, and ONNX Runtime. Learn model training, accuracy assessment, and cross-framework interoperability for efficient ML development and deployment.
New Capabilities in Form Recognizer and PyTorch in Visual Studio Code - Episode 6
Explore new Form Recognizer capabilities for efficient document processing and learn about PyTorch integration in Visual Studio Code to enhance machine learning development workflows.
What's New in Cognitive Search and Cool Frameworks with PyTorch - Episode 5
Explore Azure Cognitive Search's semantic capabilities, PyTorch frameworks, and a Rock Paper Scissors project in this informative session covering AI advancements and practical applications.
Scaling ML Workloads with PyTorch
Explore techniques for scaling machine learning workloads with PyTorch, including distributed training, memory optimization, and profiling tools for large-scale model development.
AI Show Live - Azure Form Recognizer, Deep Learning Container with PyTorch and AzureML
Explore Azure Form Recognizer, PyTorch containers, and ONNX Runtime optimizations in this comprehensive livestream featuring demos, Q&As, and expert insights on cutting-edge AI technologies.
Tensorflow, Pytorch and OpenCV Setup with CUDA
The series covers settingup tensorflow with and without CUDA and contains the basics of jupyter notebook.
PyTorch Tutorials - Complete Beginner Course
Comprehensive guide to PyTorch: from basics to advanced concepts, covering tensors, neural networks, and model deployment. Ideal for beginners seeking practical skills.
PyTorch - Deep Learning with Python
Explore deep learning and neural networks using Python and PyTorch, covering data handling, model building, training, and analysis, with a focus on convolutional networks and GPU acceleration.
PyTorch Zero to All
Learn essential machine learning and deep learning concepts using PyTorch, covering linear models, neural networks, CNNs, and RNNs in a comprehensive series of lectures.
Pytorch Tutorial
Learn PyTorch fundamentals, from installation to advanced applications. Master tensors, backpropagation, and deep learning techniques for real-world data science projects.
PyTorch for Python 3.5
Learn PyTorch fundamentals, from linear models to advanced CNNs. Master gradient descent, back-propagation, regression, and neural network architectures for efficient deep learning implementation.
NLP with BERT
Explore transformers and BERT in NLP, covering their architecture, applications, and hands-on implementation using PyTorch. Learn about sequence-to-sequence models, text summarization, and practical use cases.
PyTorch and the Journey in Open Source - Keynote by Soumith Chintala
Soumith Chintala discusses PyTorch's journey, principles, and ecosystem, exploring its development, community impact, and future directions in deep learning and open-source collaboration.
Inference with Torch-TensorRT Deep Learning Prediction for Beginners - CPU vs CUDA vs TensorRT
Accelerate deep learning inference using Torch-TensorRT. Compare CPU, CUDA, and TensorRT performance with ResNet50 for image classification. Hands-on tutorial covers setup, implementation, and benchmarking.
HuggingFace Crash Course - Sentiment Analysis, Model Hub, Fine Tuning
Comprehensive introduction to HuggingFace and Transformers library, covering sentiment analysis, Model Hub exploration, and fine-tuning techniques for NLP tasks.
Autoencoder in PyTorch - Theory & Implementation
Learn to implement Autoencoders in PyTorch, covering theory, data loading, simple and CNN architectures, training loops, and image plotting. Gain practical deep learning skills through hands-on coding.
PyTorch Time Sequence Prediction With LSTM - Forecasting Tutorial
Learn to predict time sequences using PyTorch and LSTMs. Create sine waves, build an LSTM model, implement a training loop, and perform final testing for accurate forecasting.
Deep Learning With PyTorch - Full Course
Comprehensive PyTorch tutorial covering fundamentals, advanced concepts, and practical implementations for deep learning, from tensor basics to CNNs and transfer learning.
SPLADE - The First Search Model to Beat BM25
Explore SPLADE, a groundbreaking sparse embedding model for AI-powered search. Learn its advantages over traditional methods, implementation techniques, and potential future developments in vector search technology.
Enhancing Old Videos to Full HD Using AI Tools - Video Restoration Tutorial
Discover how to transform old, low-quality videos into full HD using AI-powered video enhancement tools, Python libraries, and GPU processing for superior resolution and clarity.