From Software Engineering to Machine Learning - Santiago Valdarrama
We talked about:
00:00 DataTalks.Club intro
03:19 Santiago’s background
06:33 “Transitioning to ML” vs “Adding ML as a skill”
08:02 Getting over the fear of math for software developers
13:00 Learning by explaining
16:11 Seven lessons I learned about starting a career in machine learning
17:25 Lesson 1 – Take the first step
19:09 Lesson 2 – Learning is a marathon, not a sprint
20:38 Lesson 3 – If you want to go quickly, go alone. If you want to go far, go together.
22:18 Lesson 4 – Do something with the knowledge you gain
25:00 Lesson 5 – ML is not just math. Math is not scary.
26:39 Lesson 6 – Your ability to analyze a problem is the most important skill. Coding is secondary.
29:05 Lesson 7 – You don’t need to know every detail
33:10 Tools and frameworks needed to transition to machine learning
36:19 Problem-based learning vs Top-down learning
38:23 Learning resources
41:09 Santiago’s favorite books
42:08 Santiago’s course on transitioning to machine learning
44:01 Improving coding skills
45:27 Building solutions without machine learning
46:39 Becoming a better engineer
52:19 What is the difference between machine learning and data science?
55:10 Getting into machine learning - Reiteration
56:37 Getting past the math
59:54 Conclusion
Links:
Santiago's Twitter: / svpino
Santiago's course: https://gumroad.com/svpino#kBjbC
Pinned tweet with a roadmap: / 1400798154732212230
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