Machine Learning A-Z™: Hands-On Python & R In Data Science
Learn to create Machine Learning Algorithms in Python and R from two Data Science experts. Code templates included.
- Descripción
- Currículum
- FAQ
- Reseñas
-------------------- Part 1: Data Preprocessing --------------------
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1
Applications of Machine Learning -
2
Why Machine Learning is the Future
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3
Important notes, tips & tricks for this course -
4
This PDF resource will help you a lot
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5
Updates on Udemy Reviews
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6
Installing Python and Anaconda (Mac, Linux & Windows)
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7
Update: Recommended Anaconda Version
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8
Installing R and R Studio (Mac, Linux & Windows)
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9
BONUS: Meet your instructors
-------------------- Part 2: Regression --------------------
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10
Welcome to Part 1 - Data Preprocessing
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11
Get the dataset
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12
Importing the Libraries
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13
Importing the Dataset
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14
For Python learners, summary of Object-oriented programming: classes & objects
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15
Missing Data
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Categorical Data
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WARNING - Update
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18
Splitting the Dataset into the Training set and Test set
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Feature Scaling
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And here is our Data Preprocessing Template!
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Data Preprocessing
Simple Linear Regression
Multiple Linear Regression
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How to get the dataset
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24
Dataset + Business Problem Description
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Simple Linear Regression Intuition - Step 1
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Simple Linear Regression Intuition - Step 2
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Simple Linear Regression in Python - Step 1
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Simple Linear Regression in Python - Step 2
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Simple Linear Regression in Python - Step 3
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Simple Linear Regression in Python - Step 4
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Simple Linear Regression in R - Step 1
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Simple Linear Regression in R - Step 2
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Simple Linear Regression in R - Step 3
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Simple Linear Regression in R - Step 4
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Simple Linear Regression
Polynomial Regression
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36
How to get the dataset
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37
Dataset + Business Problem Description
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Multiple Linear Regression Intuition - Step 1
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Multiple Linear Regression Intuition - Step 2
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Multiple Linear Regression Intuition - Step 3
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Multiple Linear Regression Intuition - Step 4
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Prerequisites: What is the P-Value?
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Multiple Linear Regression Intuition - Step 5
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Multiple Linear Regression in Python - Step 1
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Multiple Linear Regression in Python - Step 2
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Multiple Linear Regression in Python - Step 3
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Multiple Linear Regression in Python - Backward Elimination - Preparation
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Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !
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Multiple Linear Regression in Python - Backward Elimination - Homework Solution
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Multiple Linear Regression in Python - Automatic Backward Elimination
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Multiple Linear Regression in R - Step 1
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Multiple Linear Regression in R - Step 2
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Multiple Linear Regression in R - Step 3
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Multiple Linear Regression in R - Backward Elimination - HOMEWORK !
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Multiple Linear Regression in R - Backward Elimination - Homework Solution
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Multiple Linear Regression in R - Automatic Backward Elimination
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Multiple Linear Regression
Support Vector Regression (SVR)
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Polynomial Regression Intuition
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How to get the dataset
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Polynomial Regression in Python - Step 1
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Polynomial Regression in Python - Step 2
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Polynomial Regression in Python - Step 3
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Polynomial Regression in Python - Step 4
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Python Regression Template
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Polynomial Regression in R - Step 1
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Polynomial Regression in R - Step 2
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Polynomial Regression in R - Step 3
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Polynomial Regression in R - Step 4
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R Regression Template
Decision Tree Regression
Random Forest Regression
Evaluating Regression Models Performance
-------------------- Part 3: Classification --------------------
Logistic Regression
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Course details
Conferencias
27
Cuestionarios
1
Video
41 hours
Certificate of Completion
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