Deep_Learning
Repo for housing my experiments with Deep Learning along with notes taken from the Deep Learning Specialization series of courses from Deeplearning.ai and Coursera.org.
Huge shout out to Andrew Ng! Who is brilliant and inspirational!
Check out the DeepLearning specalization HERE
Contents
This repo contains dozens of Jupyter notebooks which each cover one or two primary concepts. For copyright reasons the majority of this project is contained within git ignored folders (sorry)! But if you find the contents of this repo interesting or helpful, I strongly encourage you to enroll in Ng's course =).
In addition, I will be slowly adding several datasets, some models, and code experiments using Tensorflow, Keras, and (soon) PyTorch.
If there are any mistakes in my notes, or major topics that are not covered, please reach out and let me know, and happy learning!
Folder Contents
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Machine_Learning : Notes and examples from the beginner level IBM Machine Learning Specialization on Coursera.org
- Scikit Learn : Notes and experiments building ML systems using the user-friendly Python library Scikit Learn
- pytorch : Machine Learning projects using the slightly more advanced PyTorch framework
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Deep_Learning Notes and examples from the intermediate level DeepLearning.ai Specalization on Coursera.org
- Mostly consists of examples that use NumPy to create networks from scratch and the frameworks of TensorFlow and Keras
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resources : markdown file containing links to useful websites and .pdfs that I have used while learning Deep Learning
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data : collection of datasets (mostly .csv files right now) that I have used while experimenting with Deep Learning and Data analytics