
Introduction to Linear Algebra for Applied Machine Learning with Python
Linear algebra is to machine learning as flour to bakery: every machine learning model is based in linear algebra, as every cake is based in flour. It is not the only ingredient, of course. Machine learning models need vector calculus, probability, and optimization, as cakes need sugar, eggs, and butter....

Introduction to Linear Regression  mathematics and application with Python
Linear regression is among the most widely used tools in machine learning. Linear models are linear simply because the outputs are modeled as linear combinations of input vectors. Hence, we want to learn a function $f$ that describes with as little error as possible, the linear relationship between inputs and...

The Recurrent Neural Network  Theory and Implementation of the Elman Network and LSTM
Learning objectives Understand the principles behind the creation of the recurrent neural network Obtain intuition about difficulties training RNNs, namely: vanishing/exploding gradients and longterm dependencies Obtain intuition about mechanics of backpropagation through time BPTT Develop a Long ShortTerm memory implementation in Keras Learn about the uses and limitations of RNNs...