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booklist

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from al

data-engineer-roadmap

Roadmap to becoming a data engineer in 2021

data-engineering-roadmap

Roadmap for Data Engineering

deep-learning-ml-and-tensorflow

Examples of linear regression, logistic regression, and deep learning implementations such as Transformers, gans, cnns, rnns, and more using Tensorflow. The code examples here are discussed in my books: Deep Learning Algorithms, and Getting Started with Deep Learning -->> Link.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

machine-learning-specialization-coursera

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

ml-commons

ml-commons provides a set of common machine learning algorithms, e.g. k-means, or linear regression, to help developers build ML related features within OpenSearch.

mlops-basics

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

zat

Zeek Analysis Tools (ZAT): Processing and analysis of Zeek network data with Pandas, scikit-learn, Kafka and Spark