AI Learning Land's repositories
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.
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