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A 8-month syllabus to get up to Speed on NLP and LLMs. From Zero to Hero

Month 1-2: Deep Dive into Deep Learning Fundamentals

  1. Deep Learning Specialization by Andrew Ng (Coursera)
    • Topics: Deep Neural Networks, CNNs, Sequence models, etc.
    • Link to Course
  2. Book: Deep Learning by Goodfellow, Bengio, and Courville.
    • Focus especially on the chapters related to RNNs and LSTMs.
    • Link to Book

Month 3: Natural Language Processing (NLP) Basics

  1. Stanford's Natural Language Processing with Deep Learning (CS224N)
  2. Implement Basic NLP tasks:

Month 4: Deep Learning in Production

  1. Full Stack Deep Learning Course
    • Topics: Infrastructure, Tooling, Data Management, Modeling, Deployment, Monitoring, Maintenance.
    • Course Link
  2. Additional Reading:
    • Building Machine Learning Powered Applications: Going from Idea to Product by Emmanuel Ameisen.

Month 5: Advanced NLP Techniques

  1. Hugging Face's Transformers Library
  2. Research Papers:
    • Attention is All You Need by Vaswani et al.
    • BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding by Devlin et al.
  3. Practical NLP Book

Month 6: Introduction to Large Language Models (LLMs)

  1. OpenAI's GPT-2 & GPT-3 Papers

Month 7: Experiment, Implement & Fine-tune Models

  1. Deep Learning for Text and Sequences (Coursera/DeepLearning.AI)
  2. Work on a Project
    • Choose an NLP problem.
    • Implement a solution using a transformer model.
    • Kaggle or NLP Progress for datasets.

Month 8: Research, Ethics, and Best Practices

  1. Research Paper Reading & Implementation
    • Select papers from NLP conferences (ACL, NAACL, EMNLP) and attempt replication.
  2. AI Ethics in NLP
  3. NLP Best Practices

Throughout these 8 months, constantly keep track of new research, articles, and tutorials. The field of NLP and LLMs is fast-paced, so staying updated will be key to your success.

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This repo contains tutorials on Generative Artificial intelligence, including LLMs

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