I compare training a neural network in Keras with scikit-learn (MLPRegressor) in Jupyter Notebook.
I show how to train them in both packages and discuss important findings and differences in using them.
0:00 Introduction
0:25 What is scikit-learn?
1:00 sklearn.neural_network.MLPRegressor introduction
1:38 What is Keras?
2:45 Specifications of our neural network for this example
5:24 Dataset used in this example; from UCI Machine Learning repository
6:25 Import modules from sklearn.
7:55 Look at the dataset quickly
10:42 Instantiate the MLPRegressor module
10:59 Deep dive into the MLPRegressor module; Look at the arguments.
15:50 Train/fit MLPRegressor and compute errors
17:35 Keras neural network training begins here; import modules for training.
25:55 Conclusions from this exercise
32:50 Check out my other videos on forward and back propagation.