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Overview
Natural Language Processing (NLP) with Sequence-to-sequence (seq2seq), Attention, CNNs, RNNs, and Memory Networks! What you'll learn: Build a text classification system (can be used for spam detection, sentiment analysis, and similar problems)Build a neural machine translation system (can also be used for chatbots and question answering)Build a sequence-to-sequence (seq2seq) modelBuild an attention modelBuild a memory network (for question answering based on stories)Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion Ever wondered how AI technologies like...
Syllabus
- Welcome
- Recurrent Neural Networks, Convolutional Neural Networks, and Word Embeddings
- Bidirectional RNNs
- Sequence-to-sequence models (Seq2Seq)
- Attention
- Memory Networks
- Keras and Tensorflow 2 Basics
- Course Conclusion
- Appendix / FAQ Intro
- Setting Up Your Environment (FAQ by Student Request)
Instructor
Lazy Programmer Inc.
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