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Master Regression and Feedforward Networks [2026]
Master Regression analysis and Prediction with Regression Models, Feedforward Neural Networks, and XGBoost Regression
5.086 reviews968 learners
- All Levels
- 12h 47m video
- 21 lectures
- English
- Captions
- Updated 2026
Taught by Henrik Johansson
- 12h 47m of on-demand video
- 21 lectures across 3 sections
- One-off payment — no subscription
- Lifetime access on web and mobile
- Closed captions (English)
Curriculum
3 sections21 lectures12h 47m total
- Introduction10:53
- Setup of the Anaconda Cloud Notebook20:47
- Download and installation of the Anaconda Distribution (optional)20:39
- The Conda Package Management System (optional)46:52
- Regression, Prediction, and Supervised Learning. Section Overview (I)10:15
- The Traditional Simple Regression Model (II)35:08
- The Traditional Simple Regression Model (III)38:00
- Some practical and useful modelling concepts (IV)13:01
- Some practical and useful modelling concepts (V)13:01
- Linear Multiple Regression model (VI)57:00
- Linear Multiple Regression model (VII)36:24
- Multivariate Polynomial Multiple Regression models (VIII)10:13
- Multivariate Polynomial Multiple Regression models (VIIII)1:06:05
- Regression Regularization, Lasso and Ridge models (X)1:29:52
- Decision Tree Regression models (XI)1:15:26
- Random Forest Regression (XII)1:09:18
- Voting Regression (XIII)48:00
- Overview2:54
- Artificial Neural Networks, Feedforward Networks, and the Multi-Layer Perceptron19:10
- Feedforward Multi-Layer Perceptron for Prediction28:50
- eXtreme Gradient Boosting Regression (XGBoost)55:49
About this course
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 and eXtreme Gradient Boosting Regression for prediction tasks. You will learn modeling theory and several useful ways to prepare a dataset for Da…
Before you start
- 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
Who it’s for
- 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
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