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.

A game theoretic approach to explain the output of any machine learning model.

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

Notebooks and code for the book "Introduction to Machine Learning with Python"

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

Slides and code from our TensorFlow workshop.

An educational demonstration of breaking the Enigma machine

Hunting for passwords with deep learning

Hands-On Machine Learning for Cybersecurity, published by Packt

The implementation of the Seq2Seq model for web attack detection. The Seq2Seq model is usually used in Neural Machine Translation. The main goal of this project is to demonstrate the relevance of t…

Active C&C Detector

Network intrusions classification using algorithms such as Support Vector Machine (SVM), Decision Tree, Naive Baye, K-Nearest Neighbor (KNN), Logistic Regression and Random Forest.

Machine Learning on dataset HTTP CSIC 2010

Machine learning enabled dropper

Machine Learning hands-on exercises (March-June 2018)

Machine Learning hands-on exercises (February-May 2019)

Security Weaknesses in Machine Learning

Playing around with IDS data in Keras

Learning Data Science By Coding

Tuto sur le deep learning en francais.