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

00:00
005 Simple Linear Regression in Python – Step 2a.mp4

00:00
006 Simple Linear Regression in Python – Step 2b.mp4

00:00
007 Simple Linear Regression in Python – Step 3.mp4

00:00
008 Simple Linear Regression in Python – Step 4a.mp4

00:00
009 Simple Linear Regression in Python – Step 4b.mp4

00:00
010 Simple Linear Regression in Python – Additional Lecture.html

00:00
011 Simple Linear Regression in R – Step 1.mp4

00:00
012 Simple Linear Regression in R – Step 2.mp4

00:00
013 Simple Linear Regression in R – Step 3.mp4

00:00
014 Simple Linear Regression in R – Step 4a.mp4

00:00
015 Simple Linear Regression in R – Step 4b.mp4

00:00
Section Quiz

07 – Multiple Linear Regression

001 Dataset + Business Problem Description.mp4

00:00
002 Multiple Linear Regression Intuition.mp4

00:00
003 Assumptions of Linear Regression.mp4

00:00
004 Multiple Linear Regression Intuition – Step 3.mp4

00:00
005 Multiple Linear Regression Intuition – Step 4.mp4

00:00
006 Understanding the P-Value.mp4

00:00
007 Multiple Linear Regression Intuition – Step 5.mp4

00:00
008 Multiple Linear Regression in Python – Step 1a.mp4

00:00
009 Multiple Linear Regression in Python – Step 1b.mp4

00:00
010 Multiple Linear Regression in Python – Step 2a.mp4

00:00
011 Multiple Linear Regression in Python – Step 2b.mp4

00:00
012 Multiple Linear Regression in Python – Step 3a.mp4

00:00
013 Multiple Linear Regression in Python – Step 3b.mp4

00:00
014 Multiple Linear Regression in Python – Step 4a.mp4

00:00
015 Multiple Linear Regression in Python – Step 4b.mp4

00:00
016 Multiple Linear Regression in Python – Backward Elimination.html

00:00
017 Multiple Linear Regression in Python – EXTRA CONTENT.html

00:00
018 Multiple Linear Regression in R – Step 1a.mp4

00:00
019 Multiple Linear Regression in R – Step 1b.mp4

00:00
020 Multiple Linear Regression in R – Step 2a.mp4

00:00
021 Multiple Linear Regression in R – Step 2b.mp4

00:00
022 Multiple Linear Regression in R – Step 3.mp4

00:00
023 Multiple Linear Regression in R – Backward Elimination – HOMEWORK !.mp4

00:00
024 Multiple Linear Regression in R – Backward Elimination – Homework Solution.mp4

00:00
025 Multiple Linear Regression in R – Automatic Backward Elimination.html

00:00
external-links.txt

00:00
Section Quiz

08 – Polynomial Regression

001 Polynomial Regression Intuition.mp4

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

00:00
003 Polynomial Regression in Python – Step 1b.mp4

00:00
004 Polynomial Regression in Python – Step 2a.mp4

00:00
005 Polynomial Regression in Python – Step 2b.mp4

00:00
006 Polynomial Regression in Python – Step 3a.mp4

00:00
007 Polynomial Regression in Python – Step 3b.mp4

00:00
008 Polynomial Regression in Python – Step 4a.mp4

00:00
009 Polynomial Regression in Python – Step 4b.mp4

00:00
010 Polynomial Regression in R – Step 1a.mp4

00:00
011 Polynomial Regression in R – Step 1b.mp4

00:00
012 Polynomial Regression in R – Step 2a.mp4

00:00
013 Polynomial Regression in R – Step 2b.mp4

00:00
014 Polynomial Regression in R – Step 3a.mp4

00:00
015 Polynomial Regression in R – Step 3b.mp4

00:00
016 Polynomial Regression in R – Step 3c.mp4

00:00
017 Polynomial Regression in R – Step 4a.mp4

00:00
018 Polynomial Regression in R – Step 4b.mp4

00:00
019 R Regression Template – Step 1.mp4

00:00
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

00:00
003 SVR in Python – Step 1a.mp4

00:00
004 SVR in Python – Step 1b.mp4

00:00
005 SVR in Python – Step 2a.mp4

00:00
006 SVR in Python – Step 2b.mp4

00:00
007 SVR in Python – Step 2c.mp4

00:00
008 SVR in Python – Step 3.mp4

00:00
009 SVR in Python – Step 4.mp4

00:00
010 SVR in Python – Step 5a.mp4

00:00
011 SVR in Python – Step 5b.mp4

00:00
012 SVR in R – Step 1.mp4

00:00
013 SVR in R – Step 2.mp4

00:00
Section Quiz

10 – Decision Tree Regression

001 Decision Tree Regression Intuition.mp4

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

00:00
003 Decision Tree Regression in Python – Step 1b.mp4

00:00
004 Decision Tree Regression in Python – Step 2.mp4

00:00
005 Decision Tree Regression in Python – Step 3.mp4

00:00
006 Decision Tree Regression in Python – Step 4.mp4

00:00
007 Decision Tree Regression in R – Step 1.mp4

00:00
008 Decision Tree Regression in R – Step 2.mp4

00:00
009 Decision Tree Regression in R – Step 3.mp4

00:00
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

00:00
003 Preparation of the Regression Code Templates – Step 2.mp4

00:00
004 Preparation of the Regression Code Templates – Step 3.mp4

00:00
005 Preparation of the Regression Code Templates – Step 4.mp4

00:00
006 THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION! – STEP 1.mp4

00:00
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

00:00
006 Logistic Regression in Python – Step 2a.mp4

00:00
007 Logistic Regression in Python – Step 2b.mp4

00:00
008 Logistic Regression in Python – Step 3a.mp4

00:00
009 Logistic Regression in Python – Step 3b.mp4

00:00
010 Logistic Regression in Python – Step 4a.mp4

00:00
011 Logistic Regression in Python – Step 4b.mp4

00:00
012 Logistic Regression in Python – Step 5.mp4

00:00
013 Logistic Regression in Python – Step 6a.mp4

00:00
014 Logistic Regression in Python – Step 6b.mp4

00:00
015 Logistic Regression in Python – Step 7a.mp4

00:00
016 Logistic Regression in Python – Step 7b.mp4

00:00
017 Logistic Regression in Python – Step 7c.mp4

00:00
018 Logistic Regression in Python – Step 7 (Colour-blind friendly image).html

00:00
019 Logistic Regression in R – Step 1.mp4

00:00
020 Logistic Regression in R – Step 2.mp4

00:00
021 Logistic Regression in R – Step 3.mp4

00:00
022 Logistic Regression in R – Step 4.mp4

00:00
023 Warning – Update.html

00:00
024 Logistic Regression in R – Step 5a.mp4

00:00
025 Logistic Regression in R – Step 5b.mp4

00:00
026 Logistic Regression in R – Step 5c.mp4

00:00
027 Logistic Regression in R – Step 5 (Colour-blind friendly image).html

00:00
028 R Classification Template.mp4

00:00
029 Machine Learning Regression and Classification BONUS.html

00:00
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

00:00
004 Types of Kernel Functions.mp4

00:00
005 Non-Linear Kernel SVR (Advanced).mp4

00:00
006 Kernel SVM in Python – Step 1.mp4

00:00
007 Kernel SVM in Python – Step 2.mp4

00:00
008 Kernel SVM in R – Step 1.mp4

00:00
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

00:00
005 Naive Bayes in Python – Step 1.mp4

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

00:00
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

00:00
006 K-Means Clustering in Python – Step 1b.mp4

00:00
007 K-Means Clustering in Python – Step 2a.mp4

00:00
008 K-Means Clustering in Python – Step 2b.mp4

00:00
009 K-Means Clustering in Python – Step 3a.mp4

00:00
010 K-Means Clustering in Python – Step 3b.mp4

00:00
011 K-Means Clustering in Python – Step 3c.mp4

00:00
012 K-Means Clustering in Python – Step 4.mp4

00:00
013 K-Means Clustering in Python – Step 5a.mp4

00:00
014 K-Means Clustering in Python – Step 5b.mp4

00:00
015 K-Means Clustering in Python – Step 5c.mp4

00:00
016 K-Means Clustering in R – Step 1.mp4

00:00
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

00:00
004 Hierarchical Clustering in Python – Step 1.mp4

00:00
005 Hierarchical Clustering in Python – Step 2a.mp4

00:00
006 Hierarchical Clustering in Python – Step 2b.mp4

00:00
007 Hierarchical Clustering in Python – Step 2c.mp4

00:00
008 Hierarchical Clustering in Python – Step 3a.mp4

00:00
009 Hierarchical Clustering in Python – Step 3b.mp4

00:00
010 Hierarchical Clustering in R – Step 1.mp4

00:00
011 Hierarchical Clustering in R – Step 2.mp4

00:00
012 Hierarchical Clustering in R – Step 3.mp4

00:00
013 Hierarchical Clustering in R – Step 4.mp4

00:00
014 Hierarchical Clustering in R – Step 5.mp4

00:00
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

00:00
004 Upper Confidence Bound in Python – Step 2.mp4

00:00
005 Upper Confidence Bound in Python – Step 3.mp4

00:00
006 Upper Confidence Bound in Python – Step 4.mp4

00:00
007 Upper Confidence Bound in Python – Step 5.mp4

00:00
008 Upper Confidence Bound in Python – Step 6.mp4

00:00
009 Upper Confidence Bound in Python – Step 7.mp4

00:00
010 Upper Confidence Bound in R – Step 1.mp4

00:00
011 Upper Confidence Bound in R – Step 2.mp4

00:00
012 Upper Confidence Bound in R – Step 3.mp4

00:00
013 Upper Confidence Bound in R – Step 4.mp4

00:00
Section Quiz

33 – Thompson Sampling

001 Thompson Sampling Intuition.mp4

00:00
002 Algorithm Comparison UCB vs Thompson Sampling.mp4

00:00
003 Thompson Sampling in Python – Step 1.mp4

00:00
004 Thompson Sampling in Python – Step 2.mp4

00:00
005 Thompson Sampling in Python – Step 3.mp4

00:00
006 Thompson Sampling in Python – Step 4.mp4

00:00
007 Additional Resource for this Section.html

00:00
008 Thompson Sampling in R – Step 1.mp4

00:00
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

00:00
004 Classical vs Deep Learning Models.mp4

00:00
005 Bag-Of-Words Model.mp4

00:00
006 Natural Language Processing in Python – Step 1.mp4

00:00
007 Natural Language Processing in Python – Step 2.mp4

00:00
008 Natural Language Processing in Python – Step 3.mp4

00:00
009 Natural Language Processing in Python – Step 4.mp4

00:00
010 Natural Language Processing in Python – Step 5.mp4

00:00
011 Natural Language Processing in Python – Step 6.mp4

00:00
012 Natural Language Processing in Python – BONUS.html

00:00
013 Homework Challenge.html

00:00
014 Natural Language Processing in R – Step 1.mp4

00:00
015 Warning – Update.html

00:00
016 Natural Language Processing in R – Step 2.mp4

00:00
017 Natural Language Processing in R – Step 3.mp4

00:00
018 Natural Language Processing in R – Step 4.mp4

00:00
019 Natural Language Processing in R – Step 5.mp4

00:00
020 Natural Language Processing in R – Step 6.mp4

00:00
021 Natural Language Processing in R – Step 7.mp4

00:00
022 Natural Language Processing in R – Step 8.mp4

00:00
023 Natural Language Processing in R – Step 9.mp4

00:00
024 Natural Language Processing in R – Step 10.mp4

00:00
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

00:00
003 The Activation Function.mp4

00:00
004 How do Neural Networks work.mp4

00:00
005 How do Neural Networks learn.mp4

00:00
006 Gradient Descent.mp4

00:00
007 Stochastic Gradient Descent.mp4

00:00
008 Backpropagation.mp4

00:00
009 Business Problem Description.mp4

00:00
010 ANN in Python – Step 1.mp4

00:00
011 ANN in Python – Step 2.mp4

00:00
012 ANN in Python – Step 3.mp4

00:00
013 ANN in Python – Step 4.mp4

00:00
014 ANN in Python – Step 5.mp4

00:00
015 ANN in R – Step 1.mp4

00:00
016 ANN in R – Step 2.mp4

00:00
017 ANN in R – Step 3.mp4

00:00
018 ANN in R – Step 4 (Last step).mp4

00:00
019 Deep Learning Additional Content.html

00:00
020 EXTRA CONTENT ANN Case Study.html

00:00
Section Quiz

37 – Convolutional Neural Networks

001 Plan of attack.mp4

00:00
002 What are convolutional neural networks.mp4

00:00
003 Step 1 – Convolution Operation.mp4

00:00
004 Step 1(b) – ReLU Layer.mp4

00:00
005 Step 2 – Pooling.mp4

00:00
006 Step 3 – Flattening.mp4

00:00
007 Step 4 – Full Connection.mp4

00:00
008 Summary.mp4

00:00
009 Softmax & Cross-Entropy.mp4

00:00
010 CNN in Python – Step 1.mp4

00:00
011 CNN in Python – Step 2.mp4

00:00
012 CNN in Python – Step 3.mp4

00:00
013 CNN in Python – Step 4.mp4

00:00
014 CNN in Python – Step 5.mp4

00:00
015 CNN in Python – FINAL DEMO!.mp4

00:00
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

1 year 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