Winston Dodson's repositories
public_open_source_projects
This is a public repo for open source public projects
MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
handson-ml2
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.
accel-brain-code
The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.
data
Data Sets for Machine Learning Practice
pycaret
An open-source, low-code machine learning library in Python
Ideal-Gas-Simulation-To-Verify-Maxwell-Boltzmann-distribution
Simulation of an Ideal Gas to Verify Maxwell-Boltzmann distribution
plotly-tutorial
This Jupyter Notebook condenses the Plotly API into one easy to use document with examples
elegant-scipy
1st Edition of Elegant SciPy (O'Reilly Publishers)
U-Net_Lung-Segmentation
Application of U-Net in Lung Segmentation-Pytorch
enhancement_proposals
Enhancement proposals for scikit-learn: structured discussions and rational for large additions and modifications
pyclustering
pyclustring is a Python, C++ data mining library.
Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
binder_test
this a test of the Binder app
dataviz
A book covering the fundamentals of data visualization
handson-unsupervised-learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
Medium-SoftClusteringWeights
Code and data to accompany the Medium article on soft k-means weights
Feature-Engineering-Made-Easy
Feature Engineering Made Easy, published by Packt
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
feature-engineering-book
Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
mltutorial
Machine Learning Tutorial in IPython Notebooks