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Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 16 - ConvNets and TreeRNNs
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Stanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher Manning - Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 16 - ConvNets and TreeRNNs

Master NLP and Deep Learning with Stanford's CS224N: Dive into word vectors, neural networks, transformers, and more. Transform language processing with cutting-edge lectures and tutorials. Unleash AI innovation with expert insights and practical skills!

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What you'll learn

Understand the fundamentals of natural language processing with deep learning techniques
Apply word vectors and language models to analyze textual data
Implement and train neural networks and sequence-to-sequence models
Explore advanced topics like self-attention, transformers, and brain-computer interfaces

This course includes

  • 27.5 hours of video
  • Certificate of completion
  • Access on mobile and TV

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For more information about Stanford's online Artificial Intelligence programs visit: https://stanford.io/ai This lecture covers ConvNets for NLP and Tree Recursive Neural Networks: 1. Course organization updates (5 mins) 2. Intro to CNNs (25 mins) 3. Simple CNN for Sentence Classification: Yoon (2014) (10 mins) 4. CNN potpourri (5 mins) 5. Deep CNN for Sentence Classification: Conneau et al. (2017) (10 mins) 6. Tree Recursive Neural Nets, briefly (15 mins) 7. Recursive Neural Tensor Networks and Sentiment Analysis (15 mins) To learn more about enrolling in this course visit: https://online.stanford.edu/courses/cs224n-natural-language-processing-deep-learning To follow along with the course schedule and syllabus visit: hhttps://web.stanford.edu/class/archive/cs/cs224n/cs224n.1246/ Professor Christopher Manning Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science Director, Stanford Artificial Intelligence Laboratory (SAIL)

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