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Python Train Test Challenge
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Classroom Contents
Machine Learning Fundamentals with Python and R
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- 1 Intro with my face in it
- 2 WHY Machine Learning?
- 3 Python or R - which one to choose?
- 4 Installing the required tools
- 5 Crash Course - our jupyter environment
- 6 Installing R and R Studio
- 7 Crash Course R and R Studio
- 8 Intro Vectors
- 9 Intro Data Tables
- 10 What is a model?
- 11 Problems where machine learning is used
- 12 Intuition - Linear Regression
- 13 More in Linear Regression
- 14 How to support the channel and get even more sweet Machine Learning knowledge
- 15 Python import data and draw graphic
- 16 Python Linear Regression Part 1
- 17 Python Linear Regression Part 2
- 18 R Linear Regression Part 1
- 19 R Linear Regression Part 2
- 20 R Linear Regression Part 3
- 21 R Linear Regression Part 4
- 22 Excursus - Why Quadratic?
- 23 Intro Project - Used Cars Price Prediction
- 24 Python sample project
- 25 R Sample Solution Used Cars
- 26 Train and Test Data Intro
- 27 Python Train Test Part 1
- 28 Python Train Test Part 2
- 29 Python Train Test Challenge
- 30 R Train Test Part 1
- 31 R Train Test Part 2
- 32 R Train Test Challenge
- 33 Intuition Linear Regression multiple variables part 1
- 34 Intuition Linear Regression multiple variables part 2
- 35 Python Linear Regression multiple variables part 1
- 36 Python Linear Regression multiple variables part 2
- 37 R Linear Regression multiple variables
- 38 R squared part 1
- 39 R squared part 2
- 40 Python R2 calculation
- 41 Python Compare Models via R2
- 42 R - R2 Calculation
- 43 R - Compare models with R2
- 44 Intro Project R2
- 45 Python Project R2 calculation
- 46 R Project calculate R2
- 47 Data Types Part 1
- 48 Numerica and Nominal data
- 49 Ordinal Data
- 50 Python working with nominal data
- 51 Python linear regression with nominal data
- 52 R Nominal Data and linear regression
- 53 Why can we get rid of a column?
- 54 Polynomial Regression Part 1
- 55 Polynomial Regression Part 2
- 56 Python Polynomial Regression Part 1
- 57 Python Polynomial Regression Part 2
- 58 R Polynomial Regression Part 1
- 59 R Polynomial Regression Part 2
- 60 Practice Project Diamond Data
- 61 Python Sample Solution Diamonds
- 62 R Sample Solution Diamonds
- 63 R Vectors and Matrices
- 64 R - Access Elements of Vectors
- 65 R - Naming Elements
- 66 R - Matrices
- 67 R - Naming Matrices
- 68 R - Datatables
- 69 Vectorizing Calculations
- 70 Why Numpy
- 71 Numpy Arrays
- 72 Numpy Arrays application
- 73 Numpy Matrices
- 74 NP Where Function
