### Learning AI from basics
Adjunct Stanford Prof - Ashwin Rao : My recommendation is this sequence:
- Linear Algebra Basics: https://math.mit.edu/~gs/linearalgebra/ila6/indexila6.html
- Probability and Statistics: https://www.amazon.com/Statistical-Inference-George-Casella/dp/0534243126
- Deep Learning (much better than Goodfellow book in my opinion): https://www.amazon.com/Understanding-Deep-Learning-Simon-Prince/dp/0262048647

### [[Common AI ML terms]]
[[AI Use Cases by Industry.pptx]]
[[AI driven Personalization at Scale.pdf]]
Applications: 
[[Generative AI]]

![[Pasted image 20230816165324.png|400]]

### AI use cases in daily lives
1. Spotify songs based on my mood or time of the day
2. ChatGPT creating personalized day plan given a prompt
3. Google ads based on targeting persona profile
4. ChatGPT to summarize meeting notes into actions
5. Google Maps navigation based on real-time traffic and historical data
6. Netflix recommendations on what to watch next
7. Dynamic pricing on Amazon
8. Email spam filters
9. Facebook/Instagram feed based on personalization ML algorithm 

### Insightful reads
- [State of AI Report 2022](https://www.stateof.ai/) - PDF [[State of AI Report 2022 - ONLINE.pdf]]
- ##### Metrics for ML analyses
	- Azure AutoML: [Demo Recording](https://dell.zoom.us/rec/play/_C1fR6_JM0SC2AqDy8ZX2A_AogtXQvzIa1mRYu7gyjUw9NZMQlvz3QvP0c6KQyAtKAFd453iQ4QNp3_T.yXOaeYNNhKUHzc8N?continueMode=true&_x_zm_rtaid=lhOYnMc8RPW_9t96mfitig.1651622823187.8421dd046285d6157e3dcc8bbe466a63&_x_zm_rhtaid=62) Password: yM7kQ7?1
- 6 part article: [The Step-By-Step PM Guide to Building Machine Learning Based Products | by Yael Gavish | Medium](https://medium.com/@yaelg/product-manager-pm-step-by-step-tutorial-building-machine-learning-products-ffa7817aa8ab)
- [[Tyler Bellamey]] explained on learning steps
- [[Reinforcement learning - Ashwin Rao.pdf]]