PyTorch Tutorial: nn.LSTM скачать в хорошем качестве

PyTorch Tutorial: nn.LSTM

PyTorch LSTM: Long Short-Term Memory Networks - Complete Tutorial In this comprehensive tutorial, we explore Long Short-Term Memory (LSTM) networks in PyTorch. From basic concepts to advanced implementations, this video covers everything you need to know about LSTMs for deep learning applications. We'll walk through the LSTM architecture, parameter configurations, and practical examples including sequence classification, bidirectional LSTMs, multi-layer networks, and regularization techniques. Perfect for both beginners and intermediate practitioners looking to master recurrent neural networks in PyTorch. 📚 Topics Covered: • LSTM cell architecture and gates • Basic to advanced PyTorch implementations • Bidirectional and multi-layer configurations • Dropout and regularization strategies • Practical sequence classification example • Weight initialization and gradient analysis • Common pitfalls and best practices ⏱️ Timestamps: 00:00 PyTorch LSTM: Long Short-Term Memory Networks 01:22 LSTM Cell Architecture 02:05 Basic LSTM - Simplest Example 03:18 LSTM Parameters Documentation 04:04 Multi-Layer LSTM Network 06:06 Batch First Configuration 07:16 Bidirectional LSTM 09:16 Dropout for Regularization 10:30 LSTM with Projection 11:40 Practical Example: Sequence Classification 13:38 Weight Analysis and Initialization 15:28 Gradient Flow Analysis 17:19 Common Pitfalls and Solutions 17:52 Best Practices Summary