Update README.md

Author: b7leung

README.md

@@ -1,30 +1,47 @@
 # Machine Learning Engineer - Flashcards
 
-These are flashcards I made to prepare for machine learning engineer interviews and review everything from my time doing research, taking classes, and independent study. Using them, I was able to get offers from several FAANG-like companies. Hopefully other people can benefit from them as well!
+These are flashcards I made to prepare for machine learning engineer interviews, and review everything from my years of ML research, classes, and independent study. Using them, I was able to get offers from several companies (including Google, Tesla, Samsung, Motional, UiPath, and TikTok). Hopefully other people can benefit from them as well!
 
-The PDFs in this repo are mostly for convenience. Check out the links below for the most up to date and animated versions, with additional links in the speaker notes:
+The PDFs in this repo are mostly for convenience. __Check out these presentation slide links for the most up to date and animated versions__, with additional links in the speaker notes:
 
-* [1 Computer Science](https://docs.google.com/presentation/d/1uGIda3-VgQqzA3KQUDieiuPPF2-dJsH9-c1sRv0gfRs/edit?usp=sharing)
-* [2 Machine Learning General](https://docs.google.com/presentation/d/1qSOwBrjEmZTXQqNqB9XRAV7QsB6SJrLZ4pZBCkpvzyA/edit?usp=sharing)
-* [3 Fundamentals for Computer Vision & Deep Learning](https://docs.google.com/presentation/d/1Ru9UPxlXnx7FZ3bxcQ-SH9TB6nHtOflYYA1N_UMzv2g/edit?usp=sharing)
-* [4 Selected Topics in Computer Vision & Deep Learning](https://docs.google.com/presentation/d/1tWWiKR-GI3uO0QKU-CBfLdGOvSyv-pD8g_kjuZvm4Mc/edit?usp=sharing)
+* [1 Computer Science Slides](https://docs.google.com/presentation/d/1uGIda3-VgQqzA3KQUDieiuPPF2-dJsH9-c1sRv0gfRs/edit?usp=sharing)
+* [2 Machine Learning General Slides](https://docs.google.com/presentation/d/1qSOwBrjEmZTXQqNqB9XRAV7QsB6SJrLZ4pZBCkpvzyA/edit?usp=sharing)
+* [3 Fundamentals for Computer Vision & Deep Learning Slides](https://docs.google.com/presentation/d/1Ru9UPxlXnx7FZ3bxcQ-SH9TB6nHtOflYYA1N_UMzv2g/edit?usp=sharing)
+* [4 Selected Topics in Computer Vision & Deep Learning Slides](https://docs.google.com/presentation/d/1tWWiKR-GI3uO0QKU-CBfLdGOvSyv-pD8g_kjuZvm4Mc/edit?usp=sharing)
 
 # Intended Scope and Audience
 
-The flashcards covers topics relating to computer science, classical machine learning, and modern deep learning with an emphasis on computer vision. They generally assume a good foundation in these topics, and a lot of technicaal terminology is used. I think the approach might be different depending on your current experience:
+The flashcards covers topics relating to computer science, classical machine learning, and modern deep learning with an emphasis on computer vision. They generally assume a good foundation in these topics, and a lot of technical terminology is used. I think the approach might be different depending on your current experience:
 
-* If you already have a good foundation  in ML, and want to review (e.g. to prep for interviews), you can probably use them as is
+* If you already have a good foundation in ML, and want to review (e.g. for work, to prep for interviews, or just for your knowledge), you can probably use them as-is and fill in any missing knowledge gaps
 
-* If you are newer to ML, and want to have an overview of what is out there, with the option to learn 
+* If you are newer to ML, this may provide a good overview of what is out there, and I'd suggest subsequently refering to other materials that are focused on education & learning (see "additional links" below)
 
-Note that some flashcards are more important than others. From my experience interviewing at 10+ companies, these are the most important slides:
+# Important Slides
 
-* 1
+Note that some ML flashcards are more important than others. From my experience interviewing at 10+ companies focusing on computer vision roles in 2022, these are the most important slides:
+
+* Machine Learning General: 1,
+* Fundamentals for Computer Vision & Deep Learning: 1,
+* Selected Topics in Computer Vision & Deep Learning: 1,
 
 # Contributing
 
+There may be errors in these slides, or things that I've missed. If so, feel free to make a post as an issue in github.
+
+__*Please mark the slide in question so others can easily find it, e.g. if you see an issue in Machine Learning General slide 14, add [1.14] to the title.*__
+
 # Additional Links & Resources
 
-# About Me
+If you're interviewing for MLE roles, conceptual ML knowledge is only a third of what you need to know. The other usual components are programming questions, and behaviorial questions based on projects you've done in the past. Here are some useful resources to help with everything:
+
+* The most useful resource I've found to learn about the MLE interview process holistically
+  * https://huyenchip.com/ml-interviews-book/
+* Useful course materials for ML from stanford and UC Berkeley
+  * http://cs231n.stanford.edu/
+  * https://fullstackdeeplearning.com/spring2021/
+* Resources for the programming portion
+  * https://www.crackingthecodinginterview.com/
+  * https://leetcode.com/