My adventure in learning Python, machine learning (ML), and deep learning (DL).
My goal is to document my progress at learning Python ML and DL on a GitHub repo.
Author: Jennifer E. Yoon
Coursera, Deep Learning AI Specialization:
Class 1: Neural Networks and Deep Learning
Class 2: Improving Deep Neural Networks
Class 3: Structuring Machine Learning Projects
Class 4: Convolutional Neural Networks
Class 5: Sequence Models
Additional class: Introduction to TensorFlow
Udemy.com, Data Science and Machine Learning Bootcamp class
Author code so your dollars will support the author rather than Udemy.
Udemy.com, Introduction to PyTorch (2nd Meetup)
Links: to add
Jake VanderPlas, Python Data Science Handbook (c 2017)
Francois Chollet, Deep Learning with Python (c 2018)
James, Witten, Hastie, Tibshirani, Introduction to Statistical Learning with R
See books folder for more resources.
Folder structure will be either by topic or by class name.
- CS231n - folder for learning Stanford class Convolutional Neural Networks for Visual Recognition.
- dlai - folder for Coursera.com DeepLearning.AI Specialization classes.
- fastai - deep learning classes by fast.ai.
I am also a member of a Meetup group in Sterling, Virginia that is studying data science classes together. Our group is focusing on Coursera Deep Learning AI Specialization, starting in September 2019 and continuing into 2020.
Correcting My Errors
Use a pull request to make corrections or to share additional information. Typos and grammatical fixes are always welcome. Supporting information on any of the topics are also welcome.
- Started on 7/17/2019 as a Github public repo.
- August and September 2019, add folders for CS231n, dlai (deep learning .ai), Chollet-DLPy book, Vanderplas machine learning book.
- February-March 2020, update dlai folders for more classes.