eXtreme MultiLabel Classification tutorial notebook for Machine Learners (with video)
A set of ML/DL project notebooks.
The repository contains the code and notebooks for the tutorials on how to extract embedding features from pictures using the ResNext model. The quality and effectiveness of the techniques are proved by the clustering in the embedding space and the correlation of clusters with their corresponding labels.
A self-contained Google Colab Notebook that implements RAG using Postgres pgvector, pgai, and LLMs. Supports local-Ollama/OpenAI/Anthropic
This notebook explores the application of Regex and embedding techniques in Arabic Natural Language Processing (NLP). It covers the use of regular expressions for text parsing tasks and delves into various word embedding methods, including Word2Vec and FastText, for semantic analysis and representation of Arabic text data.
Basics of machine learning is END-TO-END Repository which includes very Basic Machine Learning Models and Notebook
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