kaparthy's repositories
ML-Webinar
Machine Learning with sklearn tutorials (for Pearson)
automl18
Hands-on With Google AutoML: Training
ai-for-big-data
This is part of the Artificial Intelligence live course, hosted by Packtpub. In this repository, you can find information to build your environment and the files of the coding exercises that will be covered during the live session.
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Kafka.jl
Client for Apache Kafka in Julia
Math-of-Machine-Learning-Course-by-Siraj
Implements common data science methods and machine learning algorithms from scratch in python. Intuition and theory behind the algorithms is also discussed.
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners with Latest APIs
Beginning-Application-Development-with-TensorFlow-and-Keras
Learn to design, develop, train, and deploy TensorFlow and Keras models as real-world applications
Machine_Learning_Journey
This is the Curriculum for "Machine Learning Journey" By Siraj Raval on Youtube
azure_machine_learning
This is the code for "Azure Machine Learning" By Siraj Raval on Youtube
pym
Python for you and me book
functional_intro_to_python
A functional, Data Science focused introduction to Python
stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
ThinkPython2
LaTeX source and supporting code for Think Python, 2nd edition, by Allen Downey.
ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
aima-java
Java implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
aima-python
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
pandas_for_everyone
Repository to accompany "Pandas for Everyone"
handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
workshops
A few exercises for use at events.
kinesis-streaming-intro
Code example for the article "Introduction to Stream Processing"
BusinessAnalytics
Grad level course in Business Analytics at NYU
Tiny-Python-3.6-Notebook
This repository contains the text for the Tiny Python 3.6 Notebook.
Stat295
This repository contains code related to STAT 295 Introduction to Statistical Learning.
deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"