LLM Chronicles #4.1: Recurrent Neural Networks for Modelling Sequential Data скачать в хорошем качестве

LLM Chronicles #4.1: Recurrent Neural Networks for Modelling Sequential Data

In this episode we'll look at how to model sequences of data, such as natural language, using Recurrent Neural Networks. We'll peak into the implementation of an RNN layer, looking at all the operations involved in the forward pass. Finally, we'll look at how good they are at remembering information from the past and at common issues that arise during training (vanishing and exploding gradients). We'll finish by looking at how Long short-term memory cells can help mitigate some of these issues. Series website: https://llm-chronicles.com/ 🖹 Download the mindmap for this episode here: Recurrent Neural Networks: https://llm-chronicles.com/pdfs/llm-c... 👇 Refer to the pinned comment at the top for updated corrections and clarifications. 🕤 Timestamps: 00:26 - Modeling Sequential Data 01:46 - Recurrent Neural Networks 02:24 - Compact Representation of RNNs 03:10 - Forward Pass of an RNN layer 04:42 - RNN Architectures (one-to-many, many-to-one, many-to-many) 06:32 - Long-Term Memory Issues 07:22 - Vanishing and Exploding Gradients 08:30 - LSTM/GRU Cells 📚 References & Acknowledgements: Illustrated Guide to LSTM's and GRU's: A step by step explanation:    • Illustrated Guide to LSTM's and GRU's: A s...