Flower - A Friendly Federated Learning Framework

Jargon from the functional programming world in simple terms!

Statistical Rethinking course winter 2022

Mega list of 1 on 1 meeting questions compiled from a variety to sources

Collection of notebooks about quantitative finance, with interactive python code.

📚A practical approach to learning machine learning.

Simple and ready-to-use tutorials for TensorFlow

Simple and comprehensive tutorials in TensorFlow

A collection of various awesome lists for hackers, pentesters and security researchers

This note presents in a technical though hopefully pedagogical way the three most common forms of neural network architectures: Feedforward, Convolutional and Recurrent.

💯 Technical and non-technical tips for rocking your coding interview.

The fast.ai deep learning library, lessons, and tutorials

TensorFlow Tutorial and Examples for beginners

TensorFlow tutorials and best practices.

A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding).

An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.

Building a scalable foundation for deep learning

Lime: Explaining the predictions of any machine learning classifier

Learn how to design large scale systems. Prep for the system design interview.

Bare bones Python implementations of some of the fundamental Machine Learning models and algorithms.

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

HTML5/EPUB3 version of SICP

A complete daily plan for studying to become a machine learning engineer.

A curated list of awesome computer vision resources

Lessons in the Fundamentals of Scala

A curated list of awesome lists

A python tutorial on bayesian modeling techniques (PyMC3)

Dive into Machine Learning with Python Jupyter notebook and scikit-learn

Data Science Python Notebooks: Spark, Hadoop MapReduce, HDFS, AWS, Kaggle, scikit-learn, matplotlib, pandas, NumPy, SciPy, and various command lines. https://bit.ly/data-notes