Machine Learning Regression Masterclass in Python

Name: Machine Learning Regression Masterclass in Python
Rating: 4.4 (566 reviews)

Build 8+ Practical Projects and Master Machine Learning Regression Techniques Using Python, Scikit Learn and Keras

(566 ratings)

5,220 students

Created by Dr. Ryan Ahmed, Ph.D., MBA, Ligency I Team, Mitchell Bouchard, Ligency Team

Last updated 8/2022

English

English [Auto]

What you'll learn

Master Python programming and Scikit learn as applied to machine learning regression
Understand the underlying theory behind simple and multiple linear regression techniques
Apply simple linear regression techniques to predict product sales volume and vehicle fuel economy
Apply multiple linear regression to predict stock prices and Universities acceptance rate
Cover the basics and underlying theory of polynomial regression
Apply polynomial regression to predict employees’ salary and commodity prices
Understand the theory behind logistic regression
Apply logistic regression to predict the probability that customer will purchase a product on Amazon using customer features
Understand the underlying theory and mathematics behind Artificial Neural Networks
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
Optimize ANNs hyper parameters such as number of hidden layers and neurons to enhance network performance
Apply ANNs to predict house prices given parameters such as area, number of rooms..etc
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 Error intuition, R-Squared intuition, Adjusted R-Squared and F-Test
Understand the underlying theory and intuition behind Lasso and Ridge regression techniques
Sample real-world, practical projects

Requirements

Machine Learning basics
PC with Internet connetion

Description

Artificial Intelligence (AI) revolution is here! The technology is progressing at a massive scale and is being widely adopted in the Healthcare, defense, banking, gaming, transportation and robotics industries.

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. According to a report released by Research and Markets, the global AI and machine learning technology sectors are expected to grow from $1.4B to $8.8B by 2022 and it is predicted that AI tech sector will create around 2.3 million jobs by 2020.

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.

Who this course is for:

Data Scientists who want to apply their knowledge on Real World Case Studies
Machine Learning Enthusiasts who look to add more projects to their Portfolio

Dr. Ryan Ahmed, Ph.D., MBA

Professor & Best-selling Instructor, 300K+ students

4.5 Instructor Rating
28,926 Reviews
303,064 Students
46 Courses

Ryan Ahmed is a best-selling Udemy instructor who is passionate about education and technology. Ryan's mission is to make quality education accessible and affordable to everyone. Ryan holds a Ph.D. degree in Mechanical Engineering from McMaster* University, with focus on Mechatronics and Electric Vehicle (EV) control. He also received a Master’s of Applied Science degree from McMaster, with focus on Artificial Intelligence (AI) and fault detection and an MBA in Finance from the DeGroote School of Business.

Ryan held several engineering positions at Fortune 500 companies globally such as Samsung America and Fiat-Chrysler Automobiles (FCA) Canada. Ryan has taught several courses on Science, Technology, Engineering and Mathematics to over 300,000+ students globally. He has over 25 published journal and conference research papers on state estimation, AI, Machine learning, battery modeling and EV controls. He is the co-recipient of the best paper award at the IEEE Transportation Electrification Conference and Expo (iTEC 2012) in Detroit, MI, USA.

Ryan is a Stanford Certified Project Manager (SCPM), certified Professional Engineer (P.Eng.) in Ontario, a member of the Society of Automotive Engineers (SAE), and a member of the Institute of Electrical and Electronics Engineers (IEEE). He is also the program Co-Chair at the 2017 IEEE Transportation and Electrification Conference (iTEC’17) in Chicago, IL, USA.

* McMaster University is one of only four Canadian universities consistently ranked in the top 100 in the world.

Ligency I Team

Helping Data Scientists Succeed

4.6 Instructor Rating
596,296 Reviews
2,163,536 Students
150 Courses

Hi there,

We are the Ligency team. You will be hearing from us when new Ligency courses are released, when we publish new podcasts, blogs, share cheatsheets and more!

We are here to help you stay on the cutting edge of Data Science and Technology.

See you in class,

Sincerely,

Ligency Team!

Mitchell Bouchard

B.S, Host @RedCapeLearning 500,000 + Students

4.5 Instructor Rating
33,664 Reviews
509,050 Students
74 Courses

Mitch is a Canadian filmmaker from Harrow Ontario, Canada. In 2016 he graduated from Dakota State University with a B.S, in Computer Graphics specializing in Film and Cinematic Arts.

Currently, Mitch operates as the Chairman of Red Cape Studios, Inc. where he continues his passion for filmmaking. He is also the Host of Red Cape Learning and Produces / Directs content for Red Cape Films.

He has reached over 500,000 + Students on Udemy and Produced more than 3X Best-Selling Courses.

Mitch is currently working Producing Online Educational Courses thru Red Cape Studios Inc.

Winning several awards at Dakota State University such as "1st Place BeadleMania", "Winner College 10th Anniversary Dordt Film Festival" as well as "Outstanding Artist Award College of Arts and Sciences".

Mitch has been Featured on CBC's "Windsors Shorts" Tv Show and was also the Producer/Director for TEDX Windsor, featuring speakers from across the Country.

Ligency Team