Artificial Neural Network for Regression

Course Cover

5

(1)

compare button icon

Course Features

icon

Duration

1 hour

icon

Delivery Method

Online

icon

Available on

Lifetime Access

icon

Accessibility

Desktop, Laptop

icon

Language

English

icon

Subtitles

English

icon

Level

Intermediate

icon

Teaching Type

Self Paced

icon

Video Content

1 hour

Course 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? In this course, I 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 collab, the free, browser based notebook environment that runs completely in the cloud. It is a game changing interface that will supercharge your machine learning toolkit.

Course Overview

projects-img

Post Course Interactions

projects-img

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Deep Learning Basics

What You Will Learn

Predictive Analytics

Regression

Linear Regression

Random Forest Algorithm

Support Vector Machines (SVM) Algorithm

Programming for Regression using Scikit-Learn

Course Instructors

Mohamad Mahjoub

Instructor

Cybersecurity expert
Course Cover