# Artificial Neural Network for Regression

Build an ANN Regression model to predict the electrical energy output of a Combined Cycle Power Plant
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How to implement an Artificial Neural Network in Python
How to do Regression

## Requirements

• Deep Learning Basics

## Description

Are you ready to flex your Deep Learning skills by learning how to build and implement an Artificial Neural Network using Python from scratch?

Testing your skills with practical courses is one of the best and most enjoyable ways to learn data science…and now we’re giving you that chance for FREE.

In this free course, AI expert Hadelin de Ponteves guides you through a case study that shows you how to build an ANN Regression model to predict the electrical energy output of a Combined Cycle Power Plant.

The objective is to create a data model that predicts the net hourly electrical energy output (EP) of the plant using available hourly average ambient variables.

Go hands-on with Hadelin in solving this complex, real-world Deep Learning challenge that covers everything from data preprocessing to building and training an ANN, while utilizing the Machine Learning library, Tensorflow 2.0, and Google Colab, the free, browser-based notebook environment that runs completely in the cloud. It’s a game-changing interface that will supercharge your Machine Learning toolkit.

Check out what’s in store for you when you enroll:

Part 1: Data Preprocessing

• Importing the dataset

• Splitting the dataset into the training set and test set

Part 2: Building an ANN

• Initializing the ANN

• Adding the input layer and the first hidden layer

• Compiling the ANN

Part 3: Training the ANN

• Training the ANN model on the training set

• Predicting the results of the test set

A combined-cycle power plant is an electrical power plant in which a Gas Turbine (GT) and a Steam Turbine (ST) are used in combination to produce more electrical energy from the same fuel than that would be possible from a single cycle power plant.

The gas turbine compresses air and mixes it with a fuel heated to a very high temperature. The hot air-fuel mixture moves through the blades, making them spin. The fast-spinning gas turbine drives a generator to generate electricity. The exhaust (waste) heat escaped through the exhaust stack of the gas turbine is utilized by a Heat Recovery Steam Generator (HSRG) system to produce steam that spins a steam turbine. This steam turbine drives a generator to produce additional electricity. CCCP is assumed to produce 50% more energy than a single power plant.

## Who this course is for:

• Anyone interested in Machine Learning and Deep Learning

## Instructors

Serial Tech Entrepreneur
• 4.5 Instructor Rating
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Hadelin is an online entrepreneur who has created 30+ top-rated educational e-courses to the world on new technology topics such as Artificial Intelligence, Machine Learning, Deep Learning, Blockchain and Cryptocurrencies. He is passionate about bringing this knowledge to the world and help as much people as possible. So far more than 1.7 million students have subscribed to his courses.

Helping Data Scientists Succeed
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