Ridge Regression for Beginners!

Video Description

Hello everyone and welcome to this tutorial on Machine learning Ridge Regression. Machine Learning is a subfield of Artificial Intelligence that enables machines to improve at a given task with experience. Machine Learning is an extremely hot topic; the demand for experienced machine learning engineers and data scientists has been steadily growing in the past 5 years. Here’s a link to my new machine learning regression course on Udemy: https://www.udemy.com/machine-learning-regression-masterclass-in-python/ Subscribe to my channel to get the latest updates, we will be releasing new videos on weekly basis: https://www.youtube.com/channel/UC76VWNgXnU6z0RSPGwSkNIg/videos The purpose of this course is to provide students with knowledge of key aspects of machine learning regression techniques in a practical, easy and fun way. Regression is an important machine learning technique that works by predicting a continuous (dependant) variable based on multiple other independent variables. Regression strategies are widely used for stock market predictions, real estate trend analysis, and targeted marketing campaigns. The course provides students with practical hands-on experience in training machine learning regression models using real-world dataset. This course covers several technique in a practical manner, including: Simple Linear Regression Multiple Linear Regression Polynomial Regression Logistic Regression Decision trees regression Ridge Regression Lasso Regression Artificial Neural Networks for Regression analysis Regression Key performance indicators The course is targeted towards students wanting to gain a fundamental understanding of machine learning regression models. Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to any student with basic programming knowledge. Students who enroll in this course will master machine learning regression models and can directly apply these skills to solve real world challenging problems.