In this machine learning tutorial, you will learn the fundamentals of machine learning using the programming languages Python and R. This course is the perfect introduction to machine learning for beginners that aim to improve their programming skills. First you will learn how to setup the right software. Then you will learn what models are, how to use them in Python and R and you will have plenty of exercises and projects along the way. Get the complete Machine Learning Masterclass with a 90% discount: https://www.udemy.com/course/machine-learning-data-science-masterclass/?couponCode=YTMLMAY20 And the complete Python Masterclass with a 90% discount https://www.udemy.com/course/the-complete-python-masterclass/?couponCode=YTMLMAY20 Download the course material used in this video: https://drive.google.com/open?id=1bOIIL1n8MAr2fi4m1GaZoEhQOZvuBRHA tutorialsEU offers you free video tutorials about programming and development for complete beginners up to experienced programmers. Stay tuned and subscribe to tutorialsEU: https://goo.gl/rBFh3x #MachineLearning #MachineLearningTutorial #Python #Tutorials #TutorialsEU #R #ML 0:00:00 Intro with my face in it 0:03:42 WHY Machine Learning? 0:07:35 Python or R - which one to choose? 0:12:00 Installing the required tools 0:17:53 Crash Course - our jupyter environment 0:25:29 Installing R and R Studio 0:28:48 Crash Course R and R Studio 0:39:31 Intro Vectors 0:43:41 Intro Data Tables 0:47:15 What is a model? 0:51:30 Problems where machine learning is used 0:55:37 Intuition - Linear Regression 0:59:18 More in Linear Regression 1:05:58 How to support the channel and get even more sweet Machine Learning knowledge 1:06:28 Python import data and draw graphic 1:11:56 Python Linear Regression Part 1 1:17:30 Python Linear Regression Part 2 1:22:24 R Linear Regression Part 1 1:31:16 R Linear Regression Part 2 1:36:46 R Linear Regression Part 3 1:38:14 R Linear Regression Part 4 1:42:22 Excursus - Why Quadratic? 1:48:58 Intro Project - Used Cars Price Prediction 1:53:33 Python sample project 2:00:05 R Sample Solution Used Cars 2:07:43 Train and Test Data Intro 2:11:09 Python Train Test Part 1 2:16:57 Python Train Test Part 2 2:20:53 Python Train Test Challenge 2:22:06 R Train Test Part 1 2:28:21 R Train Test Part 2 2:35:31 R Train Test Challenge 2:36:34 Intuition Linear Regression multiple variables part 1 2:43:13 Intuition Linear Regression multiple variables part 2 2:47:21 Python Linear Regression multiple variables part 1 2:53:40 Python Linear Regression multiple variables part 2 2:59:41 R Linear Regression multiple variables 3:05:46 R squared part 1 3:09:36 R squared part 2 3:14:03 Python R2 calculation 3:20:12 Python Compare Models via R2 3:26:50 R - R2 Calculation 3:33:26 R - Compare models with R2 3:40:53 Intro Project R2 3:43:49 Python Project R2 calculation 3:46:32 R Project calculate R2 3:51:22 Data Types Part 1 3:55:02 Numerica and Nominal data 4:00:06 Ordinal Data 4:05:02 Python working with nominal data 4:10:24 Python linear regression with nominal data 4:15:13 R Nominal Data and linear regression 4:24:12 Why can we get rid of a column? 4:35:42 Polynomial Regression Part 1 4:44:44 Polynomial Regression Part 2 4:47:32 Python Polynomial Regression Part 1 4:55:59 Python Polynomial Regression Part 2 5:03:23 R Polynomial Regression Part 1 5:09:59 R Polynomial Regression Part 2 5:14:53 Practice Project Diamond Data 5:17:43 Python Sample Solution Diamonds 5:21:03 R Sample Solution Diamonds 5:27:18 R Vectors and Matrices 5:31:37 R - Access Elements of Vectors 5:38:34 R - Naming Elements 5:42:23 R - Matrices 5:47:53 R - Naming Matrices 5:51:14 R - Datatables 5:58:28 Vectorizing Calculations 6:01:06 Why Numpy 6:08:41 Numpy Arrays 6:13:40 Numpy Arrays application 6:16:25 Numpy Matrices 6:24:01 NP Where Function