Upgrade to Pro — share decks privately, control downloads, hide ads and more …

How to Organize an ML Study Jam - WTM WiDS 2019

How to Organize an ML Study Jam - WTM WiDS 2019

I gave a talk on how to organize an ML Study Jam at the joint event of Women Techmakers & Women in Data Science Lightning Talks meetup.

There are tons of great resources, for example, courses from tensorflow.org, Udacity, Coursera, MIT, Fast.ai, and Kaggle Learn.

Hopefully this helps you whether you are organizing an ML Study Jam for your meetup, a study group or study ML on your own.

Margaret Maynard-Reid

August 26, 2019
Tweet

More Decks by Margaret Maynard-Reid

Other Decks in Technology

Transcript

  1. How to Organize an ML Study Jam Best practices &

    learning resources Margaret Maynard-Reid ML GDE @margaretmz Women Techmakers & Women in Data Science Lightning Talks, 8/26/2019 1
  2. @margaretmz | @WTMSeattle | @GDGSeattle Why run an ML Study

    Jam? Because ML skills are in high demand ML is the “Software 2.0” (Andrej Karpathy), every engineer and non engineer should learn the basics of ML. 3
  3. @margaretmz | @WTMSeattle | @GDGSeattle Before • Remind attendees of

    prerequisites prior to the event • Identify content Study Jams best practices During • Talks • Hands-on • Coaches • Demos • Swags After • Social media & photos • Follow-up 4 Single day or multiple day sessions My blog post on How to Organize a Study Jam
  4. @margaretmz | @WTMSeattle | @GDGSeattle ML prerequisites Python & Python

    libs • Python basics • Numpy - low level math operations • Matplotlib - data visualization • Pandas - data manipulation Calculus • Derivative • Gradient • Chain rule Algebra & linear algebra Stats 5
  5. @margaretmz | @WTMSeattle | @GDGSeattle Google Colab What is Google

    Colab? • Jupyter Notebook ◦ stored on Google Drive ◦ running on Google’s VM in the cloud • Free GPU and TPU! • TensorFlow is already installed • Save and share from your Drive • Save directly to GitHub Check out these learning resources • My blog on Colab • TF team’s blog on Colab • Laurence’ Video Build a deep neural network in 4 mins with TensorFlow in Colab • Paige’s video How to take advantage of GPUs & TPUs for your ML project • Sam’s blog Keras on TPUs in Colab 6
  6. @margaretmz | @WTMSeattle | @GDGSeattle Study Jam content Where to

    find the ML content? From challenging to easy, mix and match these strategies Use existing content Write your own Invite an expert 7
  7. @margaretmz | @WTMSeattle | @GDGSeattle Write your own content Pros:

    • Re-use your own code, tutorial and blog posts • Greatest flexibility Cons: • Time consuming 8
  8. @margaretmz | @WTMSeattle | @GDGSeattle Blog.tensorflow.org TensorFlow on Youtube TensorFlow

    on Twitter #AskTensorFlow #TensorFlowMeets TensorFlow Dev Summit 2019 9 Start with tensorflow.org
  9. @margaretmz | @WTMSeattle | @GDGSeattle MOOCs Udacity, Coursera and MIT

    all have deep learning course with TensorFlow 2.0 Fast.ai uses PyTorch and has two lessons on Swift for TensorFlow 2 month, intermediate 1 month, 4 courses 5 session. 9 lectures 2 parts 14 lessons link link link link 10
  10. @margaretmz | @WTMSeattle | @GDGSeattle Machine Learning Crash Course Developed

    by Google Pros: • Great ML fundamentals • Nice animated explanations, for example - ◦ Optimizing learning rate ◦ Backpropagation • Complete ML glossary Cons: • TensorFlow code in outdated version 11
  11. @margaretmz | @WTMSeattle | @GDGSeattle Qwiklabs 12 Go to qwiklabs.com

    and search for “ML”: • Baseline: Data, ML, AI • Advanced ML: ML Infrastructure • Intro to ML: Image Processing • Intro to ML: Language Processing • Intermediate ML: TensorFlow on GCP
  12. @margaretmz | @WTMSeattle | @GDGSeattle How to read research papers

    • Arxiv.org • arxiv-sanity.com • Papers with code 16
  13. Thank you! Follow me on Twitter, Medium & GitHub to

    learn more about on-device ML, TensorFlow & computer vision. @margaretmz @margaretmz margaretmz Margaret Maynard-Reid ML GDE @margaretmz North America GDE Summit 17