Machine Learning A-Z™: AI/ Python & R + ChatGPT Bonus (2023)

About Course

Learn Machine Learning from scratch with this comprehensive course, completely free on Theetay! This course, originally from Udemy, is taught by a Data Scientist and Machine Learning expert, covering everything from basic concepts to advanced algorithms like Deep Learning.

Gain practical skills in Python and R, two of the most popular programming languages for Machine Learning. Choose the language that best suits your career goals, or learn both!

This course is packed with real-world case studies and hands-on exercises, allowing you to apply what you learn immediately. Explore topics like:

Data Preprocessing
Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification
Clustering: K-Means, Hierarchical Clustering
Association Rule Learning: Apriori, Eclat
Reinforcement Learning: Upper Confidence Bound, Thompson Sampling
Natural Language Processing: Bag-of-words model and algorithms for NLP
Deep Learning: Artificial Neural Networks, Convolutional Neural Networks
Dimensionality Reduction: PCA, LDA, Kernel PCA
Model Selection & Boosting: k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost

This course is perfect for beginners and experienced professionals alike. Access valuable resources, including Python and R code templates, to build your own Machine Learning projects. Start your Machine Learning journey today, completely free on Theetay!

Master Machine Learning on Python & R
Have a great intuition of many Machine Learning models
Make accurate predictions
Make powerful analysis
Make robust Machine Learning models
Create strong added value to your business
Use Machine Learning for personal purpose
Handle specific topics like Reinforcement Learning, NLP and Deep Learning
Handle advanced techniques like Dimensionality Reduction
Know which Machine Learning model to choose for each type of problem
Build an army of powerful Machine Learning models and know how to combine them to solve any problem

Course Content

01 – Welcome to the course! Here we will help you get started in the best conditions

001 Welcome Challenge!.html

00:00
002 Machine Learning Demo – Get Excited!.mp4

00:00
003 Get all the Datasets, Codes and Slides here.html

00:00
004 How to use the ML A-Z folder & Google Colab.mp4

00:00
005 Installing R and R Studio (Mac, Linux & Windows).mp4

00:00
006 BONUS Use ChatGPT to Boost your ML Skills.html

00:00
Section Quiz

02 – ——————– Part 1 Data Preprocessing ——————–

03 – Data Preprocessing in Python

001 Getting Started – Step 1.mp4

00:00
002 Getting Started – Step 2.mp4

00:00
003 Importing the Libraries.mp4

00:00
004 Importing the Dataset – Step 1.mp4

00:00
005 Importing the Dataset – Step 2.mp4

00:00
006 Importing the Dataset – Step 3.mp4

00:00
007 For Python learners, summary of Object-oriented programming classes & objects.html

00:00
008 Taking care of Missing Data – Step 1.mp4

00:00
009 Taking care of Missing Data – Step 2.mp4

00:00
010 Encoding Categorical Data – Step 1.mp4

00:00
011 Encoding Categorical Data – Step 2.mp4

00:00
012 Encoding Categorical Data – Step 3.mp4

00:00
013 Splitting the dataset into the Training set and Test set – Step 1.mp4

00:00
014 Splitting the dataset into the Training set and Test set – Step 2.mp4

00:00
015 Splitting the dataset into the Training set and Test set – Step 3.mp4

00:00
016 Feature Scaling – Step 1.mp4

00:00
017 Feature Scaling – Step 2.mp4

00:00
018 Feature Scaling – Step 3.mp4

00:00
019 Feature Scaling – Step 4.mp4

00:00
Section Quiz

04 – Data Preprocessing in R

001 Getting Started.mp4

00:00
002 Dataset Description.mp4

00:00
003 Importing the Dataset.mp4

00:00
004 Taking care of Missing Data.mp4

00:00
005 Encoding Categorical Data.mp4

00:00
006 Splitting the dataset into the Training set and Test set – Step 1.mp4

00:00
007 Splitting the dataset into the Training set and Test set – Step 2.mp4

00:00
008 Feature Scaling – Step 1.mp4

00:00
009 Feature Scaling – Step 2.mp4

00:00
010 Data Preprocessing Template.mp4

00:00
Section Quiz

05 – ——————– Part 2 Regression ——————–

06 – Simple Linear Regression

002 Ordinary Least Squares.mp4

00:00
003 Simple Linear Regression in Python – Step 1a.mp4

00:00
004 Simple Linear Regression in Python – Step 1b.mp4

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005 Simple Linear Regression in Python – Step 2a.mp4

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006 Simple Linear Regression in Python – Step 2b.mp4

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007 Simple Linear Regression in Python – Step 3.mp4

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008 Simple Linear Regression in Python – Step 4a.mp4

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009 Simple Linear Regression in Python – Step 4b.mp4

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010 Simple Linear Regression in Python – Additional Lecture.html

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011 Simple Linear Regression in R – Step 1.mp4

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012 Simple Linear Regression in R – Step 2.mp4

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013 Simple Linear Regression in R – Step 3.mp4

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014 Simple Linear Regression in R – Step 4a.mp4

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015 Simple Linear Regression in R – Step 4b.mp4

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Section Quiz

07 – Multiple Linear Regression

001 Dataset + Business Problem Description.mp4

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002 Multiple Linear Regression Intuition.mp4

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003 Assumptions of Linear Regression.mp4

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004 Multiple Linear Regression Intuition – Step 3.mp4

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005 Multiple Linear Regression Intuition – Step 4.mp4

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006 Understanding the P-Value.mp4

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007 Multiple Linear Regression Intuition – Step 5.mp4

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008 Multiple Linear Regression in Python – Step 1a.mp4

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009 Multiple Linear Regression in Python – Step 1b.mp4

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010 Multiple Linear Regression in Python – Step 2a.mp4

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011 Multiple Linear Regression in Python – Step 2b.mp4

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012 Multiple Linear Regression in Python – Step 3a.mp4

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013 Multiple Linear Regression in Python – Step 3b.mp4

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014 Multiple Linear Regression in Python – Step 4a.mp4

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015 Multiple Linear Regression in Python – Step 4b.mp4

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016 Multiple Linear Regression in Python – Backward Elimination.html

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017 Multiple Linear Regression in Python – EXTRA CONTENT.html

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018 Multiple Linear Regression in R – Step 1a.mp4

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019 Multiple Linear Regression in R – Step 1b.mp4

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020 Multiple Linear Regression in R – Step 2a.mp4

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021 Multiple Linear Regression in R – Step 2b.mp4

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022 Multiple Linear Regression in R – Step 3.mp4

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023 Multiple Linear Regression in R – Backward Elimination – HOMEWORK !.mp4

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024 Multiple Linear Regression in R – Backward Elimination – Homework Solution.mp4

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025 Multiple Linear Regression in R – Automatic Backward Elimination.html

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external-links.txt

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Section Quiz

08 – Polynomial Regression

001 Polynomial Regression Intuition.mp4

00:00
002 Polynomial Regression in Python – Step 1a.mp4

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003 Polynomial Regression in Python – Step 1b.mp4

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004 Polynomial Regression in Python – Step 2a.mp4

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005 Polynomial Regression in Python – Step 2b.mp4

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006 Polynomial Regression in Python – Step 3a.mp4

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007 Polynomial Regression in Python – Step 3b.mp4

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008 Polynomial Regression in Python – Step 4a.mp4

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009 Polynomial Regression in Python – Step 4b.mp4

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010 Polynomial Regression in R – Step 1a.mp4

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011 Polynomial Regression in R – Step 1b.mp4

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012 Polynomial Regression in R – Step 2a.mp4

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013 Polynomial Regression in R – Step 2b.mp4

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014 Polynomial Regression in R – Step 3a.mp4

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015 Polynomial Regression in R – Step 3b.mp4

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016 Polynomial Regression in R – Step 3c.mp4

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017 Polynomial Regression in R – Step 4a.mp4

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018 Polynomial Regression in R – Step 4b.mp4

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019 R Regression Template – Step 1.mp4

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020 R Regression Template – Step 2.mp4

00:00
Section Quiz

09 – Support Vector Regression (SVR)

001 SVR Intuition (Updated!).mp4

00:00
002 Heads-up on non-linear SVR.mp4

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003 SVR in Python – Step 1a.mp4

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004 SVR in Python – Step 1b.mp4

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005 SVR in Python – Step 2a.mp4

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006 SVR in Python – Step 2b.mp4

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007 SVR in Python – Step 2c.mp4

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008 SVR in Python – Step 3.mp4

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009 SVR in Python – Step 4.mp4

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010 SVR in Python – Step 5a.mp4

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011 SVR in Python – Step 5b.mp4

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012 SVR in R – Step 1.mp4

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013 SVR in R – Step 2.mp4

00:00
Section Quiz

10 – Decision Tree Regression

001 Decision Tree Regression Intuition.mp4

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002 Decision Tree Regression in Python – Step 1a.mp4

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003 Decision Tree Regression in Python – Step 1b.mp4

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004 Decision Tree Regression in Python – Step 2.mp4

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005 Decision Tree Regression in Python – Step 3.mp4

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006 Decision Tree Regression in Python – Step 4.mp4

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007 Decision Tree Regression in R – Step 1.mp4

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008 Decision Tree Regression in R – Step 2.mp4

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009 Decision Tree Regression in R – Step 3.mp4

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010 Decision Tree Regression in R – Step 4.mp4

00:00
Section Quiz

11 – Random Forest Regression

12 – Evaluating Regression Models Performance

13 – Regression Model Selection in Python

001 Make sure you have this Model Selection folder ready.html

00:00
002 Preparation of the Regression Code Templates – Step 1.mp4

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003 Preparation of the Regression Code Templates – Step 2.mp4

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004 Preparation of the Regression Code Templates – Step 3.mp4

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005 Preparation of the Regression Code Templates – Step 4.mp4

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006 THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! – STEP 1.mp4

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007 THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! – STEP 2.mp4

00:00
008 Conclusion of Part 2 – Regression.html

00:00
Section Quiz

14 – Regression Model Selection in R

15 – ——————– Part 3 Classification ——————–

16 – Logistic Regression

002 Logistic Regression Intuition.mp4

00:00
003 Maximum Likelihood.mp4

00:00
004 Logistic Regression in Python – Step 1a.mp4

00:00
005 Logistic Regression in Python – Step 1b.mp4

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006 Logistic Regression in Python – Step 2a.mp4

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007 Logistic Regression in Python – Step 2b.mp4

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008 Logistic Regression in Python – Step 3a.mp4

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009 Logistic Regression in Python – Step 3b.mp4

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010 Logistic Regression in Python – Step 4a.mp4

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011 Logistic Regression in Python – Step 4b.mp4

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012 Logistic Regression in Python – Step 5.mp4

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013 Logistic Regression in Python – Step 6a.mp4

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014 Logistic Regression in Python – Step 6b.mp4

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015 Logistic Regression in Python – Step 7a.mp4

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016 Logistic Regression in Python – Step 7b.mp4

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017 Logistic Regression in Python – Step 7c.mp4

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018 Logistic Regression in Python – Step 7 (Colour-blind friendly image).html

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019 Logistic Regression in R – Step 1.mp4

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020 Logistic Regression in R – Step 2.mp4

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021 Logistic Regression in R – Step 3.mp4

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022 Logistic Regression in R – Step 4.mp4

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023 Warning – Update.html

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024 Logistic Regression in R – Step 5a.mp4

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025 Logistic Regression in R – Step 5b.mp4

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026 Logistic Regression in R – Step 5c.mp4

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027 Logistic Regression in R – Step 5 (Colour-blind friendly image).html

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028 R Classification Template.mp4

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029 Machine Learning Regression and Classification BONUS.html

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030 EXTRA CONTENT Logistic Regression Practical Case Study.html

00:00
Section Quiz

17 – K-Nearest Neighbors (K-NN)

18 – Support Vector Machine (SVM)

19 – Kernel SVM

001 Kernel SVM Intuition.mp4

00:00
002 Mapping to a higher dimension.mp4

00:00
003 The Kernel Trick.mp4

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004 Types of Kernel Functions.mp4

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005 Non-Linear Kernel SVR (Advanced).mp4

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006 Kernel SVM in Python – Step 1.mp4

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007 Kernel SVM in Python – Step 2.mp4

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008 Kernel SVM in R – Step 1.mp4

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009 Kernel SVM in R – Step 2.mp4

00:00
010 Kernel SVM in R – Step 3.mp4

00:00
Section Quiz

20 – Naive Bayes

001 Bayes Theorem.mp4

00:00
002 Naive Bayes Intuition.mp4

00:00
003 Naive Bayes Intuition (Challenge Reveal).mp4

00:00
004 Naive Bayes Intuition (Extras).mp4

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005 Naive Bayes in Python – Step 1.mp4

00:00
006 Naive Bayes in Python – Step 2.mp4

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007 Naive Bayes in Python – Step 3.mp4

00:00
008 Naive Bayes in R – Step 1.mp4

00:00
009 Naive Bayes in R – Step 2.mp4

00:00
010 Naive Bayes in R – Step 3.mp4

00:00
Section Quiz

21 – Decision Tree Classification

22 – Random Forest Classification

23 – Classification Model Selection in Python

24 – Evaluating Classification Models Performance

25 – ——————– Part 4 Clustering ——————–

26 – K-Means Clustering

002 K-Means Clustering Intuition.mp4

00:00
003 The Elbow Method.mp4

00:00
004 K-Means++.mp4

00:00
005 K-Means Clustering in Python – Step 1a.mp4

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006 K-Means Clustering in Python – Step 1b.mp4

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007 K-Means Clustering in Python – Step 2a.mp4

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008 K-Means Clustering in Python – Step 2b.mp4

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009 K-Means Clustering in Python – Step 3a.mp4

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010 K-Means Clustering in Python – Step 3b.mp4

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011 K-Means Clustering in Python – Step 3c.mp4

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012 K-Means Clustering in Python – Step 4.mp4

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013 K-Means Clustering in Python – Step 5a.mp4

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014 K-Means Clustering in Python – Step 5b.mp4

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015 K-Means Clustering in Python – Step 5c.mp4

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016 K-Means Clustering in R – Step 1.mp4

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017 K-Means Clustering in R – Step 2.mp4

00:00
Section Quiz

27 – Hierarchical Clustering

001 Hierarchical Clustering Intuition.mp4

00:00
002 Hierarchical Clustering How Dendrograms Work.mp4

00:00
003 Hierarchical Clustering Using Dendrograms.mp4

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004 Hierarchical Clustering in Python – Step 1.mp4

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005 Hierarchical Clustering in Python – Step 2a.mp4

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006 Hierarchical Clustering in Python – Step 2b.mp4

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007 Hierarchical Clustering in Python – Step 2c.mp4

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008 Hierarchical Clustering in Python – Step 3a.mp4

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009 Hierarchical Clustering in Python – Step 3b.mp4

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010 Hierarchical Clustering in R – Step 1.mp4

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011 Hierarchical Clustering in R – Step 2.mp4

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012 Hierarchical Clustering in R – Step 3.mp4

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013 Hierarchical Clustering in R – Step 4.mp4

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014 Hierarchical Clustering in R – Step 5.mp4

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015 Conclusion of Part 4 – Clustering.html

00:00
Section Quiz

28 – ——————– Part 5 Association Rule Learning ——————–

29 – Apriori

30 – Eclat

31 – ——————– Part 6 Reinforcement Learning ——————–

32 – Upper Confidence Bound (UCB)

002 Upper Confidence Bound (UCB) Intuition.mp4

00:00
003 Upper Confidence Bound in Python – Step 1.mp4

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004 Upper Confidence Bound in Python – Step 2.mp4

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005 Upper Confidence Bound in Python – Step 3.mp4

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006 Upper Confidence Bound in Python – Step 4.mp4

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007 Upper Confidence Bound in Python – Step 5.mp4

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008 Upper Confidence Bound in Python – Step 6.mp4

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009 Upper Confidence Bound in Python – Step 7.mp4

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010 Upper Confidence Bound in R – Step 1.mp4

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011 Upper Confidence Bound in R – Step 2.mp4

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012 Upper Confidence Bound in R – Step 3.mp4

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013 Upper Confidence Bound in R – Step 4.mp4

00:00
Section Quiz

33 – Thompson Sampling

001 Thompson Sampling Intuition.mp4

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002 Algorithm Comparison UCB vs Thompson Sampling.mp4

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003 Thompson Sampling in Python – Step 1.mp4

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004 Thompson Sampling in Python – Step 2.mp4

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005 Thompson Sampling in Python – Step 3.mp4

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006 Thompson Sampling in Python – Step 4.mp4

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007 Additional Resource for this Section.html

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008 Thompson Sampling in R – Step 1.mp4

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009 Thompson Sampling in R – Step 2.mp4

00:00
Section Quiz

34 – ——————– Part 7 Natural Language Processing ——————–

001 Welcome to Part 7 – Natural Language Processing.html

00:00
002 NLP Intuition.mp4

00:00
003 Types of Natural Language Processing.mp4

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004 Classical vs Deep Learning Models.mp4

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005 Bag-Of-Words Model.mp4

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006 Natural Language Processing in Python – Step 1.mp4

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007 Natural Language Processing in Python – Step 2.mp4

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008 Natural Language Processing in Python – Step 3.mp4

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009 Natural Language Processing in Python – Step 4.mp4

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010 Natural Language Processing in Python – Step 5.mp4

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011 Natural Language Processing in Python – Step 6.mp4

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012 Natural Language Processing in Python – BONUS.html

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013 Homework Challenge.html

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014 Natural Language Processing in R – Step 1.mp4

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015 Warning – Update.html

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016 Natural Language Processing in R – Step 2.mp4

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017 Natural Language Processing in R – Step 3.mp4

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018 Natural Language Processing in R – Step 4.mp4

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019 Natural Language Processing in R – Step 5.mp4

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020 Natural Language Processing in R – Step 6.mp4

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021 Natural Language Processing in R – Step 7.mp4

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022 Natural Language Processing in R – Step 8.mp4

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023 Natural Language Processing in R – Step 9.mp4

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024 Natural Language Processing in R – Step 10.mp4

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025 Homework Challenge.html

00:00
Section Quiz

35 – ——————– Part 8 Deep Learning ——————–

36 – Artificial Neural Networks

001 Plan of attack.mp4

00:00
002 The Neuron.mp4

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003 The Activation Function.mp4

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004 How do Neural Networks work.mp4

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005 How do Neural Networks learn.mp4

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006 Gradient Descent.mp4

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007 Stochastic Gradient Descent.mp4

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008 Backpropagation.mp4

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009 Business Problem Description.mp4

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010 ANN in Python – Step 1.mp4

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011 ANN in Python – Step 2.mp4

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012 ANN in Python – Step 3.mp4

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013 ANN in Python – Step 4.mp4

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014 ANN in Python – Step 5.mp4

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015 ANN in R – Step 1.mp4

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016 ANN in R – Step 2.mp4

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017 ANN in R – Step 3.mp4

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018 ANN in R – Step 4 (Last step).mp4

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019 Deep Learning Additional Content.html

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020 EXTRA CONTENT ANN Case Study.html

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Section Quiz

37 – Convolutional Neural Networks

001 Plan of attack.mp4

00:00
002 What are convolutional neural networks.mp4

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003 Step 1 – Convolution Operation.mp4

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004 Step 1(b) – ReLU Layer.mp4

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005 Step 2 – Pooling.mp4

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006 Step 3 – Flattening.mp4

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007 Step 4 – Full Connection.mp4

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008 Summary.mp4

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009 Softmax & Cross-Entropy.mp4

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010 CNN in Python – Step 1.mp4

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011 CNN in Python – Step 2.mp4

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012 CNN in Python – Step 3.mp4

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013 CNN in Python – Step 4.mp4

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014 CNN in Python – Step 5.mp4

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015 CNN in Python – FINAL DEMO!.mp4

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016 Deep Learning Additional Content #2.html

00:00
Section Quiz

38 – ——————– Part 9 Dimensionality Reduction ——————–

39 – Principal Component Analysis (PCA)

40 – Linear Discriminant Analysis (LDA)

41 – Kernel PCA

42 – ——————– Part 10 Model Selection & Boosting ——————–

43 – Model Selection

44 – XGBoost

45 – Exclusive Offer

Add this certificate to your resume to demonstrate your skills & increase your chances of getting noticed.

Student Ratings & Reviews

4.0

Total 1 Rating

0 Rating

1 Rating

0 Rating

Mahad Mateen

3 months ago

The course was really good

About Course

What Will You Learn?

Course Content

01 – Welcome to the course! Here we will help you get started in the best conditions

001 Welcome Challenge!.html

002 Machine Learning Demo – Get Excited!.mp4

003 Get all the Datasets, Codes and Slides here.html

004 How to use the ML A-Z folder & Google Colab.mp4

005 Installing R and R Studio (Mac, Linux & Windows).mp4

006 BONUS Use ChatGPT to Boost your ML Skills.html

Section Quiz

02 – ——————– Part 1 Data Preprocessing ——————–

001 Welcome to Part 1 – Data Preprocessing.html

002 The Machine Learning process.mp4

003 Splitting the data into a Training and Test set.mp4

004 Feature Scaling.mp4

Section Quiz

03 – Data Preprocessing in Python

001 Getting Started – Step 1.mp4

002 Getting Started – Step 2.mp4

003 Importing the Libraries.mp4

004 Importing the Dataset – Step 1.mp4

005 Importing the Dataset – Step 2.mp4

006 Importing the Dataset – Step 3.mp4

007 For Python learners, summary of Object-oriented programming classes & objects.html

008 Taking care of Missing Data – Step 1.mp4

009 Taking care of Missing Data – Step 2.mp4

010 Encoding Categorical Data – Step 1.mp4

011 Encoding Categorical Data – Step 2.mp4

012 Encoding Categorical Data – Step 3.mp4

013 Splitting the dataset into the Training set and Test set – Step 1.mp4

014 Splitting the dataset into the Training set and Test set – Step 2.mp4

015 Splitting the dataset into the Training set and Test set – Step 3.mp4

016 Feature Scaling – Step 1.mp4

017 Feature Scaling – Step 2.mp4

018 Feature Scaling – Step 3.mp4

019 Feature Scaling – Step 4.mp4

Section Quiz

04 – Data Preprocessing in R

001 Getting Started.mp4

002 Dataset Description.mp4

003 Importing the Dataset.mp4

004 Taking care of Missing Data.mp4

005 Encoding Categorical Data.mp4

006 Splitting the dataset into the Training set and Test set – Step 1.mp4

007 Splitting the dataset into the Training set and Test set – Step 2.mp4

008 Feature Scaling – Step 1.mp4

009 Feature Scaling – Step 2.mp4

010 Data Preprocessing Template.mp4

Section Quiz

05 – ——————– Part 2 Regression ——————–

001 Welcome to Part 2 – Regression.html

06 – Simple Linear Regression

002 Ordinary Least Squares.mp4

003 Simple Linear Regression in Python – Step 1a.mp4

004 Simple Linear Regression in Python – Step 1b.mp4

005 Simple Linear Regression in Python – Step 2a.mp4

006 Simple Linear Regression in Python – Step 2b.mp4

007 Simple Linear Regression in Python – Step 3.mp4

008 Simple Linear Regression in Python – Step 4a.mp4

009 Simple Linear Regression in Python – Step 4b.mp4

010 Simple Linear Regression in Python – Additional Lecture.html

011 Simple Linear Regression in R – Step 1.mp4

012 Simple Linear Regression in R – Step 2.mp4

013 Simple Linear Regression in R – Step 3.mp4

014 Simple Linear Regression in R – Step 4a.mp4

015 Simple Linear Regression in R – Step 4b.mp4

Section Quiz

07 – Multiple Linear Regression

001 Dataset + Business Problem Description.mp4

002 Multiple Linear Regression Intuition.mp4

003 Assumptions of Linear Regression.mp4

004 Multiple Linear Regression Intuition – Step 3.mp4

005 Multiple Linear Regression Intuition – Step 4.mp4

006 Understanding the P-Value.mp4

007 Multiple Linear Regression Intuition – Step 5.mp4

008 Multiple Linear Regression in Python – Step 1a.mp4

009 Multiple Linear Regression in Python – Step 1b.mp4

010 Multiple Linear Regression in Python – Step 2a.mp4

011 Multiple Linear Regression in Python – Step 2b.mp4