Linear regression and gradient descent
Outline
Outline
- Getting started
- For loops and lists
- Gradient descent
- Refactor code to use matrices
- Multiple linear regression: predicting molecular solvation energies
- Multiple linear regression using Scikit: predicting molecular solubilities
Videos
Videos
- Google Colab
- Python intro
- Pandas
- Bias and weights
- Loss function and L2 loss
- Matplotlib
- For loops
- Lists
- Gradient
- Gradient descent
- Epochs
- Learning rate
- Convergence
- Refactoring
- Matrices using Numpy
- Uncommenting blocks of code
- Random initialisation of weights
- Downloading data using wget
- More Pandas
- The ESOL/Delaney data set
- Scikit
Ideas for further coding projects
Ideas for further coding projects
Linear Regression
- Create a plot with with 5 lines for 5 different choices of b and w
- Create a a plot with 5 lines using b and w obtained after 10, 50, 100, 500, and 1000 iterations
Mutiple Linear Regression
- try using only some of the molecular descriptors to see if you get a lower error for the predicted solubilities
- Find the molecules with the 5 largest errors. Google their names to find the structures. Do they have anything in common?