Artificial Neural Network for Regression

via Udemy

Overview

Delve into the world of Artificial Intelligence with our cutting-edge course on "Artificial Neural Network for Regression", offered through Udemy. This meticulously designed course aims to equip you with the knowledge and skills to construct an ANN Regression model to accurately predict the electrical energy output of a Combined Cycle Power Plant.

Course Highlights:

Master the implementation of Artificial Neural Networks in Python.
Understand the principles and applications of Regression.
Explore the functionalities of Google Colab for efficient computing.

Join AI virtuoso Hadelin de Ponteves on a comprehensive journey through the creation of an ANN Regression model from scratch. This course is structured to enhance your Deep Learning competencies by engaging in practical hands-on activities that involve solving real-world challenges.

This free course walks you through a case study centered around predicting the net hourly electrical energy output (EP) of a Combined Cycle Power Plant using available hourly average ambient variables. From data preprocessing to model training, learn every step in detail with the aid of Tensorflow 2.0 and Google Colab, the revolutionary cloud-based computing environment.

Course Structure:

Part 1: Data Preprocessing - Importing data, splitting the dataset into training and test sets.
Part 2: Building an ANN - Initialization, adding layers, and compiling the ANN.
Part 3: Training the ANN - Model training, result prediction on the test set.

Additionally, gain valuable insights into the operation and efficiency of Combined-Cycle Power Plants. Learn how CCCPs leverage both Gas Turbines (GT) and Steam Turbines (ST) to produce significantly more electrical energy than their single-cycle counterparts, making them a vital study in energy production.

Categories include Python Courses, Deep Learning Courses, Neural Networks Courses, and Regression Analysis Courses, showcasing a comprehensive learning path for anyone eager to dive into the world of AI and machine learning.