Building and Experimenting with Deep Learning, Transformers, and Generative AI.

• Machine Learning & GenAI

Educational Notebooks w/ Scikit-Learn, GPT, Cohere, Embeddings, LangChain and Pydantic for: (i) Binary / Multiclass Classification; (ii) Clustering and Topic Modelling, and (iii) Transformers Attention Visualization.

• Practical Deep Learning

Learn how to build and deploy a Neural Network from scratch.

• Transformer101

Annotated implementation in PyTorch of the Transformer model introduced in the paper 'Attention Is All You Need'

• AI Frameworks: PyTorch | LangChain | LlamaIndex | HuggingFace
• Libraries: Pandas | Pydantic | Scikit-Learn
• Vector Databases: PineCone | Weaviate
• Building Blocks: Embed-v3 | Cohere-Connectors
• DevTools: Jupyter Notebooks | Docker | GitHub Actions
• LLM APIs: OpenAI | Cohere | Anthropic-Claude