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

Deep Learning Specialization by Andrew Ng (Coursera)
- Topics: Deep Neural Networks, CNNs, Sequence models, etc.
- Link to Course
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

Stanford's Natural Language Processing with Deep Learning (CS224N)
- Course Videos
- Course Page
Implement Basic NLP tasks:
- Text classification, named entity recognition, sentiment analysis.
- Link to GitHub Repos

Month 4: Deep Learning in Production

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

Month 5: Advanced NLP Techniques

Hugging Face's Transformers Library
- Documentation & Tutorials
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.
Practical NLP Book
- Link to Book's Github

Month 6: Introduction to Large Language Models (LLMs)

OpenAI's GPT-2 & GPT-3 Papers
- Dive deep into the architecture, training procedure, and innovations.
- Link to OpenAI's Blog & Papers

Month 7: Experiment, Implement & Fine-tune Models

Deep Learning for Text and Sequences (Coursera/DeepLearning.AI)
- Course Link
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

Research Paper Reading & Implementation
- Select papers from NLP conferences (ACL, NAACL, EMNLP) and attempt replication.
AI Ethics in NLP
- Fairness and Abstraction in Sociotechnical Systems by Selbst et al.
- Ethics in NLP Course
NLP Best Practices
- Microsoft's NLP Best Practices GitHub

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.

guyvani/GenerativeAITutorials

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