Neural Networks

What is all?

Scikit-learn

• An extremely popular Machine Learning library for python.

Perceptrons

• The simplest form of a neural network.

Gradient Descent

• A process by which Machine Learning algorithms learn to improve themselves based on the accuracy of their predictions.

Backpropagation

• The process by which neural networks learn how to improve individual parameters.

Numpy

• An extremely popular library for scientific computing in python.

Tensorflow

• One of the most popular python libraries for creating neural networks. It is maintained by Google.

We'll learn more about those.

About Linear Regression

Linear Regression Works Best When the Data is Linear

Linear regression produces a straight line model from the training data. If the relationship in the training data is not really linear, we'll need to either make adjustments (transform your training data), add some features or use another kind of model.

Linear Regression is Sensitive to Outliers

Linear regression tries to find a 'best fit' line among the training data. If our dataset has some outlying extreme values that don't fit a general pattern, they can have a surprisingly large effect.