Master Regression and Feedforward Networks [2024]

Master Regression and Feedforward Networks [2024], available at $54.99, has an average rating of 5, with 20 lectures, based on 50 reviews, and has 124 subscribers.

You will learn about Master Regression, Regression analysis, and Prediction both in theory and practice Master Regression models from simple Regression models to Polynomial Multiple Regression models and advanced Multivariate Polynomial Multiple Regression models Use Machine Learning Automatic Model Creation and Feature Selection Use Regularization of Regression models and to regularize regression models with Lasso and Ridge Regression Use Decision Tree, Random Forest, and Voting Regression models Use Feedforward Multilayer Networks and Advanced Regression model Structures Use effective advanced Residual analysis and tools to judge models’ goodness-of-fit plus residual distributions Use the Statsmodels and Scikit-learn libraries for Regression supported by Matplotlib, Seaborn, Pandas, and Python Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources Option: To use the Anaconda Distribution (for Windows, Mac, Linux) Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages This course is ideal for individuals who are Anyone who wants to learn to master Regression and Prediction or Anyone who wants to learn about Automatic Model Creation or Anyone who wants to learn advanced Data Science and Machine Learning plus improve their capabilities and productivity It is particularly useful for Anyone who wants to learn to master Regression and Prediction or Anyone who wants to learn about Automatic Model Creation or Anyone who wants to learn advanced Data Science and Machine Learning plus improve their capabilities and productivity.

Enroll now: Master Regression and Feedforward Networks [2024]

Summary

Title: Master Regression and Feedforward Networks [2024]

Price: $54.99

Average Rating: 5

Number of Lectures: 20

Number of Published Lectures: 20

Number of Curriculum Items: 20

Number of Published Curriculum Objects: 20

Original Price: $22.99

Quality Status: approved

Status: Live

What You Will Learn

Master Regression, Regression analysis, and Prediction both in theory and practice
Master Regression models from simple Regression models to Polynomial Multiple Regression models and advanced Multivariate Polynomial Multiple Regression models
Use Machine Learning Automatic Model Creation and Feature Selection
Use Regularization of Regression models and to regularize regression models with Lasso and Ridge Regression
Use Decision Tree, Random Forest, and Voting Regression models
Use Feedforward Multilayer Networks and Advanced Regression model Structures
Use effective advanced Residual analysis and tools to judge models’ goodness-of-fit plus residual distributions
Use the Statsmodels and Scikit-learn libraries for Regression supported by Matplotlib, Seaborn, Pandas, and Python
Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources
Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages

Who Should Attend

Anyone who wants to learn to master Regression and Prediction
Anyone who wants to learn about Automatic Model Creation
Anyone who wants to learn advanced Data Science and Machine Learning plus improve their capabilities and productivity

Target Audiences

Anyone who wants to learn to master Regression and Prediction
Anyone who wants to learn about Automatic Model Creation
Anyone who wants to learn advanced Data Science and Machine Learning plus improve their capabilities and productivity

Welcome to the course Master Regression and Feedforward Networks!

This course will teach you to master Regression, Regression analysis, and Prediction with a large number of advanced Regression techniques for purposes of Prediction and Machine Learning Automatic Model Creation, so-called true machine intelligence or AI.

You will learn to handle advanced model structures for prediction tasks, and you will learn modeling theory and several useful ways to prepare a dataset for Data Analysis with Regression Models.

You will learn to:

Master Regression, Regression analysis, and Prediction both in theory and practice
Master Regression models from simple linear Regression models to Polynomial Multiple Regression models and advanced Multivariate Polynomial Multiple Regression models
Use Machine Learning Automatic Model Creation and Feature Selection
Use Regularization of Regression models and to regularize regression models with Lasso and Ridge Regression
Use Decision Tree, Random Forest, and Voting Regression models
Use Feedforward Multilayer Networks and Advanced Regression model Structures
Use effective advanced Residual analysis and tools to judge models’ goodness-of-fit plus residual distributions.
Use the Statsmodels and Scikit-learn libraries for Regression supported by Matplotlib, Seaborn, Pandas, and Python
Cloud computing: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources.
Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work life.
And much more…

This course is an excellent way to learn to master Regression and Prediction!

Regression and Prediction are the most important and commonly used tools for modeling, prediction, AI, and forecasting.

This course is designed for everyone who wants to

learn to master Regression and Prediction
learn about Automatic Model Creation
learn advanced Data Science and Machine Learning plus improve their capabilities and productivity

Requirements:

Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
Access to a computer with an internet connection
The course only uses costless software
Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included
Some Python and Pandas skills are necessary. If you lack these, the course “Master Regression and Prediction with Pandas and Python” includes all knowledge you need.

This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Master Regression and Prediction.

Enroll now to receive 10+ hours of video tutorials with manually edited English captions, and a certificate of completion after completing the course!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Setup of the Anaconda Cloud Notebook

Lecture 3: Download and installation of the Anaconda Distribution (optional)

Lecture 4: The Conda Package Management System (optional)

Chapter 2: Master Regression and Prediction

Lecture 1: Regression, Prediction, and Supervised Learning. Section Overview (I)

Lecture 2: The Traditional Simple Regression Model (II)

Lecture 3: The Traditional Simple Regression Model (III)

Lecture 4: Some practical and useful modelling concepts (IV)

Lecture 5: Some practical and useful modelling concepts (V)

Lecture 6: Linear Multiple Regression model (VI)

Lecture 7: Linear Multiple Regression model (VII)

Lecture 8: Multivariate Polynomial Multiple Regression models (VIII)

Lecture 9: Multivariate Polynomial Multiple Regression models (VIIII)

Lecture 10: Regression Regularization, Lasso and Ridge models (X)

Lecture 11: Decision Tree Regression models (XI)

Lecture 12: Random Forest Regression (XII)

Lecture 13: Voting Regression (XIII)

Chapter 3: Advanced Machine Learning Models

Lecture 1: Overview

Lecture 2: Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron

Lecture 3: Feedforward Multi-Layer Perceptron for Prediction

Instructors

Henrik Johansson
Instructor at Udemy

Rating Distribution

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5 stars: 50 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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