In this course, you will journey with SuperDataScience Team to teach you Build 8+ Practical Projects and Master Machine Learning Regression Techniques Using Python, Scikit Learn and Keras. Once joined the course, you will get 10.5 hours of an on-demand video guide, and 73 lectures in total. Don’t Hesitate To Enrol Now As There Is A FREE 30 Day 100% Money Back Guarantee, if you are not satisfied with the course. If you’re interested in Machine Learning Regression Masterclass in Python which is taught by Dr. Ryan Ahmed, Ph.D., MBA, Kirill Eremenko, Hadelin de Ponteves, and Mitchell Bouchard, try this course today.
What you will learn from the Machine Learning Regression Masterclass in Python Online Course
Here are some of the things you’ll be able to do after taking this course:
Upon completion of the course, you will be able to master Python programming and Scikit learn as applied to machine learning regression
Upon completing this course, you will understand the underlying theory behind simple and multiple linear regression techniques
You will learn to apply simple linear regression techniques to predict product sales volume and vehicle fuel economy
You will learn to apply multiple linear regression to predict stock prices and Universities acceptance rate
You will learn to cover the basics and underlying theory of polynomial regression
You will learn to apply polynomial regression to predict employees’ salary and commodity prices
Upon completing this course, you will understand the theory behind logistic regression
You will learn to apply logistic regression to predict the probability that customer will purchase a product on Amazon using customer features
Upon completing this course, you will understand the underlying theory and mathematics behind Artificial Neural Networks
This course is an excellent way to learn how to train network weights and biases and select the proper transfer functions
Train Artificial Neural Networks (ANNs) using back propagation and gradient descent methods
You will learn to optimize ANNs hyper parameters such as number of hidden layers and neurons to enhance network performance
You will learn to apply ANNs to predict house prices given parameters such as area, number of rooms..etc
You will learn to assess the performance of trained Machine learning models using KPI (Key Performance indicators) such as Mean Absolute error, Mean squared Error, and Root Mean Squared You will learn to error intuition, R-Squared intuition, Adjusted R-Squared and F-Test
Upon completing this course, you will understand the underlying theory and intuition behind Lasso and Ridge regression techniques
You will learn to sample real-world, practical projects
And much more!
Who is the Machine Learning Regression Masterclass in Python course target
This course is perfect for Data Scientists who want to apply their knowledge on Real World Case Studies
This course is perfect for Machine Learning Enthusiasts who look to add more projects to their Portfolio, then this course will change your life!
Enroll in This Online Course Now!
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