Descending into ML: Linear Regression
A complete list of videos from Google, in case you can’t get the videos on the official website just like me
- Introducing ML
2. Framing
3. Descending into ML
4. Reducing Loss
5.First Steps with TensorFlow
6.Generalization
7.Training and Test Sets
08 Validation https://www.youtube.com/watch?v=gvnn3HoPg-Y
09 Representation https://www.youtube.com/watch?v=MiC5H_ASTGU
10 Feature Crosses https://www.youtube.com/watch?v=JlkXvxwL2zE
11 Regularization for Simplicity https://www.youtube.com/watch?v=y0N-rSt_9gU
12 Logistic Regression https://www.youtube.com/watch?v=u-_4S5l-Cuw
13 Classification https://www.youtube.com/watch?v=uKSOY0yOHEQ
14 Regularization for Sparcity https://www.youtube.com/watch?v=l6MDlWF09QU
15 Intro to Neural Nets https://www.youtube.com/watch?v=a-L4qZ2Z6qc
16 Training Neural Nets https://www.youtube.com/watch?v=ysl2GR3q4mA
17 Multi-class Neural Nets https://www.youtube.com/watch?v=-QGVDx6jOio
18 Embeddings https://www.youtube.com/watch?v=rvt_Mv0IMok
https://developers.google.com/machine-learning/crash-course/descending-into-ml/linear-regression
