Deep Learning Models in Keras – Exploratory Data Analysis (EDA)
Introduction
Deep learning is one of the most interesting and promising areas of artificial intelligence (AI) and machine learning currently. With great advances in technology and algorithms in recent years, deep learning has opened the door to a new era of AI applications.
In many of these applications, deep learning algorithms performed equal to human experts and sometimes surpassed them.
Python has become the go-to language for Machine Learning and many of the most popular and powerful deep learning libraries and frameworks like TensorFlow, Keras, and PyTorch are built in Python.
In this article, we’ll be performing Exploratory Data Analysis (EDA) on a dataset before Data Preprocessing and finally, building a Deep Learning Model in Keras and evaluating it.
Why Keras?
Keras is a deep learning API built on top of TensorFlow. TensorFlow is an end-to-end machine learning platform that allows developers to create and deploy machine learning models. TensorFlow was developed and used by Google; though it released under an open-source license in 2015.
Keras provides a high-level API for TensorFlow. It makes it really easy to build different types