This post is the first part of Deep Learning with Keras series. This series aims to introduce the Keras deep learning library and how to use it to train various deep learning models. We will cover topics such as regression, classification, convolution, recurrent networks, transfer learning and many others. The...
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## Apache Spark ML Tutorial - Part 3

### Classification

In this part of the series, we will put together everything we have learned to train a classification model. The objective is to learn how to build a complete classification workflow from the beginning to the end.

## An Intuitive Explanation to AutoEncoders

### and how to implement them in Keras

Many of the recent deep learning models rely on extracting complex features from data. The goal is to transform the input from its raw format, to another representation calculated by the neural network. This representation contains features that describe hidden unique characteristics about the input.

## How Do Machines Learn?

### Machine Learning Concepts Explained for the Non Computer Science People

Recently, there has been a lot of fuss about the word Learning. We always hear about machine learning, deep learning, learning algorithms, etc. But what does this really mean? Did scientists find a way to create a brain-like component and implement it inside machines? Is it just a marketing word...
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## Apache Spark ML Tutorial - Part 2

### Feature Transformation

In the previous article we talked about Spark ML and how to use it for training a regression model. This article focus on Feature Transformation. We will understand the concepts and how to implement them directly in Spark ML.