ayushsunny / deep-learning-resources

This is a list of resources curated from the Slack channel for Udacity's first phase of AI Track scholarship challenge

Deep Learning Resources

Preface?

• What is it?

  This is a list of resources curated from the Slack channel for Udacity's first phase of AI Track scholarship challenge

• Why use it?

  As the Slack channel will have multiple conversations going on. I thought best to consolidate all the resources into one repository for anyone to access any time without having to go through all the conversations.

• How to contribute?

  All are welcome to open a Pull Request or raise an issue, with the content you would like to share

  • What kind of content?

    Text tutorials, video resources, youtube playlists, self-paced learning courses, ebooks... I hope you get the point.

    All and any form of content can be shared here.

Contributors

• Akhil Pillai
• Priyavrat Misra

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Self-Paced Tutorials

Artificial Intelligence, Machine Learning, Deep Learning and stuff

• CS231n: Convolutional Neural Networks for Visual Recognition This course is a deep dive into details of the deep learning architectures. Students will learn to implement, train and debug their own neural networks. The final assignment will involve training a multi-million parameter convolutional neural network and applying it on the largest image classification dataset (ImageNet). Much of the background and materials of this course will be drawn from the ImageNet Challenge.
  • Video Lectures by Andrej Karpathy, instructor CS231n.
  • Notes to accompany the Stanford CS class CS231n: Convolutional Neural Networks for Visual Recognition
  • Python Numpy Tutorial
• Coursera: Introduction to Deep Learning & Neural Networks with Keras This course will introduce you to the field of deep learning
• Practical Deep Learning for Coders Step by step introduction to Deep learning stuff!
  • Pre-Requisite: You’ve been coding for at least a year, and also that (if you haven’t used Python before) you’ll be putting in the extra time to learn whatever Python you need as you go. (For learning Python, we have a list of python learning resources available.)
• Elements of AI The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. The courses combine theory with practical exercises and can be completed at your own pace.
• Coursera: ML with Python This course dives into the basics of machine learning
• Youtube: Machine Learning Recipes with Josh Gordon (offered on Google Developers Youtube Channel)
• Coursera: Machine Learning by Andrew NG. This is a course for you if are new to this world!
• Coursera: Deep Learning by Andrew NG. A 5-course specialization focusing on various concepts of deep learning with in-depth and simple explanation.

Python

• Full Stack Python Build, Deploy and Operate Python Applications
• Scipy Lecture Notes One document to learn numerics, science, and data with Python

Math

• Youtube: 3Blue1Brown by Grant Sanderson, is combination of math and entertainment. The goal is for explanations to be driven by animations and for difficult problems to be made simple with changes in perspective.
• Khan Academy great resource to learn all the math from the ground up.
• MIT 18.06: Linear Algebra by Prof. Gilbert Strang.

Ebooks/Text Tutorials

Free

• The Deep Learning textbook by Ian Goodfellow and Yoshua Bengio and Aaron Courville
• Machine Learning Mastery! by Jason Brownlee
• Python Data Science Handbook by Jake VanderPlas
• Quantitative Economics with Python by by Thomas J. Sargent and John Stachurski. This website presents a set of lectures on quantitative economic modeling in Python

Paid

• The Hundred-page Machine Learning Book by Andriy Burkov

Coding Environment

• Google Colab Colaboratory is a free Jupyter notebook environment provided by Google. If your local workstation cannot take the workload, Google Colab is the platform to use.

Blogs

• Andrej Karpathy , director of artificial intelligence and Autopilot Vision at Tesla.
• Christopher Olah

Articles

• Clearing the Confusion: AI vs Machine Learning vs Deep Learning Differences
• Keras or PyTorch as your first deep learning framework
• Keras vs TensorFlow vs PyTorch : Comparison of the Deep Learning Frameworks
• Keras vs Pytorch for Deep Learning