Artificial Neural Network for Regression Free course in 2024

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  • Post last modified:August 13, 2024
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Artificial Neural Network Create an ANN Regression model to predict a Combined Cycle Power Plant’s electrical energy output.

Artificial Neural Network for Regression course

Artificial Neural Network

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

The goal is to develop a data model that predicts the plant’s net hourly electrical energy output (EP) using available hourly average ambient variables.

Hands-on with Hadelin as he solves this complex, real-world Deep Learning challenge, which covers everything from data preprocessing to building and training an ANN using the Machine Learning library, Tensorflow 2.0, and Google Colab, a free, browser-based notebook environment that runs entirely in the browser.

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Check out what awaits you when you enroll:

Part 1: Data Preparation

Adding the dataset

dividing the dataset into training and test sets

Part 2: Creating an ANN

ANN Initialization

Including the first hidden layer and the input layer

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Including an output layer

Artificial

Creating the ANN

Part 3: Educating the ANN

On the training set, train the ANN model

Predicting the test set’s results

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More Information on Combined-Cycle Power Plants

A combined-cycle power plant is an electrical power plant that uses a Gas Turbine (GT) and a Steam Turbine (ST) in tandem to produce more electrical energy from the same fuel than a single-cycle power plant.

The gas turbine compresses air and combines it with a highly heated fuel. The hot air-fuel mixture flows through the blades, spinning them. To generate electricity, the fast-spinning gas turbine drives a generator. The exhaust (waste) heat emitted by the gas turbine’s exhaust stack is used by a Heat Recovery Steam Generator (HSRG) system to generate steam, which spins a steam turbine. The steam turbine powers a generator.

What you’ll discover

  • How to Use Python to Create an Artificial Neural Network
  • How to Perform Regression
  • How to Make Use of Google Colab

Are there any course prerequisites or requirements?

  • Deep Learning Fundamentals
  • Anyone interested in Machine Learning and Deep Learning should take this course.

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