Pinned Repositories
arctic
High performance datastore for time series and tick data
Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
dynamic-tweet_collector
An implementation of the Paper "Adaptive Method for Following Dynamic Topics on Twitter (Tamer Elsayed, Walid Magdy) in Python using the Natural Language Toolkit and sklearn. Still under construction.
fantasy-basketball
Predicting the NBA player performance and optimising lineups for Draft Kings. Capstone Project for Machine Learning Engineer Nanodegree by Udacity.
KaggleMiniCourses
Kaggle Mini Courses
keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.
kython
A collection of common python stuff I use
mit-deep-learning-book-pdf
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
NBA-Draft-Model-2018
Jupyter notebook that outlines the process of creating a machine learning predictive model. Predicts the peak "Wins Shared" by the current draft prospects based on numerous features such as college stats, projected draft pick, physical profile and age. I try out multiple models and pick the best performing one for the data from my judgement.
nba-fantasy-selector
Simple Fantasy draft selector
jwb970's Repositories
jwb970/arctic
High performance datastore for time series and tick data
jwb970/Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
jwb970/dynamic-tweet_collector
An implementation of the Paper "Adaptive Method for Following Dynamic Topics on Twitter (Tamer Elsayed, Walid Magdy) in Python using the Natural Language Toolkit and sklearn. Still under construction.
jwb970/fantasy-basketball
Predicting the NBA player performance and optimising lineups for Draft Kings. Capstone Project for Machine Learning Engineer Nanodegree by Udacity.
jwb970/KaggleMiniCourses
Kaggle Mini Courses
jwb970/keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on Theano and TensorFlow.
jwb970/kython
A collection of common python stuff I use
jwb970/mit-deep-learning-book-pdf
MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville
jwb970/NBA-Draft-Model-2018
Jupyter notebook that outlines the process of creating a machine learning predictive model. Predicts the peak "Wins Shared" by the current draft prospects based on numerous features such as college stats, projected draft pick, physical profile and age. I try out multiple models and pick the best performing one for the data from my judgement.
jwb970/nba-fantasy-selector
Simple Fantasy draft selector
jwb970/nba_api
An API Client package to access the APIs for NBA.com
jwb970/pkglib
Company-centric Python packaging and testing library
jwb970/PY-Image_Recognition
Building an algorithm capable of successfully recognising and classifying hand-written digits. Source of data is MNIST Dataset.
jwb970/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
jwb970/PythonTrainingExercises
Code to exercise your Python knowledge.
jwb970/udacity-machine-learning-nano-degree
Project Files for the Udacity Machine Learning Engineer Nano Degree