Practical Deep Learning - AI Sat week-1 (We start AI Saturday syllabus from this week, so as per syllabus week-1)
Today's resources: https://colab.research.google.com/drive/1t5ttbhQxDNIHVWsTTP8aSopfZpXljT9R
Preparation for week 7 of AI Saturday Hyderabad(10/2/2018)
Defined Syllabus:
Practical Deep Learning Using the free and proven Fast.ai v2 materials, this is perfect for beginners in deep learning and machine learning, with some prior Python programming experience and high school math knowledge – and it’d get you to a stage where you can implement cutting-edge deep learning models, in just 14 weeks! No worries if you have no Python programming experience, feel free to reach out and we’d be happy to advise on what you can use to learn the basics of Python – you can certainly get up to speed if you work hard in these few weeks, just make sure you get up to speed so you don't fall behind the rest of the crowd!
We will watch the lectures as a group, stop the video for discussion at any point if anyone has a question or a for a key concept that requires in-depth discussion, and also breakout into small groups for the in-lecture exercises – removing any obstacles along the way, making sure that you can progress through the course confidently if you stick with us – that’s our commitment to you for your time investment!
What would we cover this week?
- Q&A with the explanation of Fast.ai Lesson 1 & 2
- Introduction and Overview of Deep Learning
Google Cloud: https://medium.com/@jamsawamsa/running-a-google-cloud-gpu-for-fast-ai-for-free-5f89c707bae6
Google Collab: https://towardsdatascience.com/fast-ai-lesson-1-on-google-colab-free-gpu-d2af89f53604
Paperspace: https://github.com/reshamas/fastai_deeplearn_part1/blob/master/tools/paperspace.md
Floydhub: https://github.com/YuelongGuo/floydhub.fast.ai/blob/master/README.md
Prep Resources: It is IMPORTANT to complete all the pre-req in order to followup with this week's sessions.
- Fast.ai (Complete both of them)
- Part 1 Lessons: http://course.fast.ai/lessons/lesson1.html
- Part 2 Lessons: http://course.fast.ai/lessons/lesson2.html
- Stanford STAT385 Theories of Deep Learning (go through all the pdf, try to complete all 8 videos)
- list: https://stats385.github.io/readings
- Reading Lecture slides: https://stats385.github.io/lecture_slides
- Lecture videos: https://www.youtube.com/watch?v=KrTqxmS1-L4&list=PLhWmdj1YUpdT-UwCLVRNX509hZrKqZ83V