Stars
Python Data Science Handbook: full text in Jupyter Notebooks
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
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.
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Natural Language Processing Tutorial for Deep Learning Researchers
The "Python Machine Learning (1st edition)" book code repository and info resource
Jupyter notebooks from the scikit-learn video series
A collection of IPython notebooks covering various topics.
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
comparing stand up comedians using natural language processing
Tutorials and training material for the H2O Machine Learning Platform
Resources for "Natural Language Processing" Coursera course.
Code base for the Learning PySpark book (in preparation)
Interactive Azure Sentinel Notebooks provides security insights and actions to investigate anomalies and hunt for malicious behaviors.
Music recommender using deep learning with Keras and TensorFlow
Introduction to generative adversarial networks, with code to accompany the O'Reilly tutorial on GANs
Tutorial on creating your own GAN in Tensorflow
Code for a tutorial on Bayesian Statistics by Allen Downey.
Tutorial on GANs
My solutions to DataCamp projects (now only Python)
introduction to text analytics in python training for odsc west 2018
A 60 days+ streak of daily learning of ML/DL/Maths concepts through projects
In general, a learning problem considers a set of n samples of data and then tries to predict properties of unknown data. If each sample is more than a single number and, for instance, a multi-dime…
Implementation of Adversarial Autoencoder with Theano
Clustering a UCI customers dataset using Kmeans in Scikit Learn
Problem Description Predict employee attrition Employee Attrition is a huge problem across industries and generally costs the company a lot for hiring, retraining, productivity and work loss for ea…