How to get started in Machine Learning
summary
Begins with concrete steps: take the Machine Learning Crash Course, build end-to-end projects on GitHub and Kaggle (NLP chatbots and Hugging Face models cited), earn the TensorFlow certificate (about 4,400 passers so far) and join community entry points — 80 TensorFlow user groups, 13 SIGs, RFCs (25 accepted last year), and ~2,500 contributors with 90,000 commits. Note gaps: 167 ML Google Developer Experts exist but only 26 are women, so mentorship and visible portfolios matter for landing that first role.
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chapters (18)
- 0:00Intro
- 1:00Welcome
- 8:04My background
- 14:05VRFCs
- 20:44Introduction
- 24:25My Journey
- 29:29QA
- 29:55Common misconceptions
- 30:22Women in ML
- 31:23Stats
- 32:56Mentorship
- 34:53Finding a mentor
- 37:27Getting a job in AI ML
- 39:09ML is not a job
- 40:30Kaggle competitions
- 41:51Data Science
- 42:58Impostor Syndrome
- 46:48Future Applications
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