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Course content
Sections:
38
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Activities:
0
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Resources:
339
- 002-Machine Learning Demo Get Excited
- 004-How to use the ML A Z folder Google Colab
- 005-Installing R and R Studio Mac Linux Windows
- 008-The Machine Learning process
- 009-Splitting the data into a Training and Test set
- 010-Feature Scaling
- 011-Getting Started Step 1
- 012-Getting Started Step 2
- 013-Importing the Libraries
- 014-Importing the Dataset Step
- 015-Importing the Dataset Step 2
- 016-Importing the Dataset Step 3
- 019-Taking care of Missing Data Step 1
- 020-Taking care of Missing Data Step 2
- 022-Encoding Categorical Data Step 1
- 023-Encoding Categorical Data Step 2
- 024-Encoding Categorical Data Step 3
- 026-Splitting the dataset into the Training set and Test set Step 1
- 027-Splitting the dataset into the Training set and Test set Step 2
- 028-Splitting the dataset into the Training set and Test set Step 3
- 030-Feature Scaling Step 1
- 031-Feature Scaling Step 2
- 032-Feature Scaling Step 3
- 033-Feature Scaling Step 4
- 035-Getting Started
- 036-Dataset Description
- 037-Importing the Dataset
- 038-Taking care of Missing Data
- 039-Encoding Categorical Data
- 040-Splitting the dataset into the Training set and Test set Step 1
- 041-Splitting the dataset into the Training set and Test set Step 2
- 042-Feature Scaling Step 1
- 043-Feature Scaling Step 2
- 044-Data Preprocessing Template
- 047-Simple Linear Regression Intuition
- 048-Ordinary Least Squares
- 049-Simple Linear Regression in Python Step 1a
- 050-Simple Linear Regression in Python Step 1b
- 051-Simple Linear Regression in Python Step 2a
- 052-Simple Linear Regression in Python Step 2b
- 053-Simple Linear Regression in Python Step 3
- 055-Simple Linear Regression in Python Step 4b
- 057-Simple Linear Regression in R Step 1
- 058-Simple Linear Regression in R Step 2
- 059-Simple Linear Regression in R Step 3
- 060-Simple Linear Regression in R Step 4a
- 061-Simple Linear Regression in R Step 4b
- 063-Dataset Business Problem Description
- 064-Multiple Linear Regression Intuition
- 065-Assumptions of Linear Regression
- 066-Multiple Linear Regression Intuition Step 3
- 067-Multiple Linear Regression Intuition Step 4
- 068-Understanding the P Value
- 069-Multiple Linear Regression Intuition Step 5
- 070-Multiple Linear Regression in Python Step 1a
- 071-Multiple Linear Regression in Python Step 1b
- 072-Multiple Linear Regression in Python Step 2a
- 073-Multiple Linear Regression in Python Step 2b
- 074-Multiple Linear Regression in Python Step 3a
- 075-Multiple Linear Regression in Python Step 3b
- 076-Multiple Linear Regression in Python Step 4a
- 077-Multiple Linear Regression in Python Step 4b
- 080-Multiple Linear Regression in R Step 1a
- 081-Multiple Linear Regression in R Step 1b
- 082-Multiple Linear Regression in R Step 2a
- 083-Multiple Linear Regression in R Step 2b
- 084-Multiple Linear Regression in R Step 3
- 085-Multiple Linear Regression in R Backward Elimination HOMEWORK
- 086-Multiple Linear Regression in R Backward Elimination Homework Solution
- 087-Multiple Linear Regression in R Automatic Backward Elimination
- 090-Polynomial Regression in Python Step 1a
- 091-Polynomial Regression in Python Step 1b
- 092-Polynomial Regression in Python Step 2a
- 093-Polynomial Regression in Python Step 2b
- 094-Polynomial Regression in Python Step 3a
- 095-Polynomial Regression in Python Step 3b
- 096-Polynomial Regression in Python Step 4a
- 097-Polynomial Regression in Python Step 4b
- 098-Polynomial Regression in R Step 1a
- 099-Polynomial Regression in R Step 1b
- 100-Polynomial Regression in R Step 2a
- 101-Polynomial Regression in R Step 2b
- 102-Polynomial Regression in R Step 3a
- 103-Polynomial Regression in R Step 3b
- 104-Polynomial Regression in R Step 3c
- 105-Polynomial Regression in R Step 4a
- 106-Polynomial Regression in R Step 4b-
- 107-R Regression Template Step 1
- 108-R Regression Template Step 2
- 110-SVR Intuition Updated
- 111-Heads up on non linear SVR
- 110-SVR Intuition Updated
- 113-SVR in Python Step 1b
- 114-SVR in Python Step 2a
- 115-SVR in Python Step 2b
- 116-SVR in Python Step 2c
- 117-SVR in Python Step 3
- 118-SVR in Python Step 4
- 119-SVR in Python Step 5a
- 120-SVR in Python Step 5b
- 121-SVR in R Step 1
- 122-SVR in R Step 2
- 124-Decision Tree Regression Intuition-
- 125-Decision Tree Regression in Python Step 1a
- 126-Decision Tree Regression in Python Step 1b
- 127-Decision Tree Regression in Python Step 2
- 128-Decision Tree Regression in Python Step 3
- 129-Decision Tree Regression in Python Step 4
- 130-Decision Tree Regression in R Step 1
- 131-Decision Tree Regression in R Step 2
- 133-Decision Tree Regression in R Step 4
- 135-Random Forest Regression Intuition
- 136-Random Forest Regression in Python Step 1
- 137-Random Forest Regression in Python Step 2
- 138-Random Forest Regression in R Step 1
- 139-Random Forest Regression in R Step 2
- 140-Random Forest Regression in R Step 3
- 142-R Squared Intuition
- 143-Adjusted R Squared Intuition
- 146-Preparation of the Regression Code Templates Step 1
- 147-Preparation of the Regression Code Templates Step 2
- 148-Preparation of the Regression Code Templates Step 3
- 149-Preparation of the Regression Code Templates Step 4
- 150-THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION STEP 1
- 151-THE ULTIMATE DEMO OF THE POWERFUL REGRESSION CODE TEMPLATES IN ACTION STEP 2
- 153-Evaluating Regression Models Performance Homework s Final Part
- 154-Interpreting Linear Regression Coefficients
- 157-What is Classification
- 158-Logistic Regression Intuition
- 159-Maximum Likelihood
- 60-Logistic Regression in Python Step 1a
- 161-Logistic Regression in Python Step 1b
- 162-Logistic Regression in Python Step 2a
- 163-Logistic Regression in Python Step 2b
- 164-Logistic Regression in Python Step 3a
- 165-Logistic Regression in Python Step 3b
- 166-Logistic Regression in Python Step 4a
- 167-Logistic Regression in Python Step 4b
- 168-Logistic Regression in Python Step 5
- 169-Logistic Regression in Python Step 6a
- 170-Logistic Regression in Python Step 6b
- 171-Logistic Regression in Python Step 7a
- 172-Logistic Regression in Python Step 7b
- 173-Logistic Regression in Python Step 7c
- 175-Logistic Regression in R Step 1
- 176-Logistic Regression in R Step 2
- 177-Logistic Regression in R Step 3
- 178-Logistic Regression in R Step 4
- 180-Logistic Regression in R Step 5a
- 181-Logistic Regression in R Step 5b
- 182-Logistic Regression in R Step 5c
- 184-R Classification Template
- 188-K Nearest Neighbor Intuition
- 189-K NN in Python Step 1
- 190-K NN in Python Step 2
- 191-K NN in Python Step 3
- 192-K NN in R Step 1
- 193-K NN in R Step 2
- 194-K NN in R Step 3
- 196-SVM Intuition
- 197-SVM in Python Step 1
- 198-SVM in Python Step 2
- 199-SVM in Python Step 3
- 200-SVM in R Step 1
- 201-SVM in R Step 2
- 203-Kernel SVM Intuition
- 204-Mapping to a higher dimension
- 205-The Kernel Trick
- 206-Types of Kernel Functions
- 207-Non Linear Kernel SVR Advanced
- 208-Kernel SVM in Python Step 1
- 209-Kernel SVM in Python Step 2
- 210-Kernel SVM in R Step 1
- 211-Kernel SVM in R Step 2
- 212-Kernel SVM in R Step 3
- 214-Bayes Theorem
- 215-Naive Bayes Intuition
- 216-Naive Bayes Intuition Challenge Reveal
- 217-Naive Bayes Intuition Extras
- 218-Naive Bayes in Python Step 1
- 219-Naive Bayes in Python Step 2
- 220-Naive Bayes in Python Step 3
- 221-Naive Bayes in R Step 1
- 222-Naive Bayes in R Step 2
- 223-Naive Bayes in R Step 3
- 225-Decision Tree Classification Intuition
- 226-Decision Tree Classification in Python Step 1
- 227-Decision Tree Classification in Python Step 2
- 228-Decision Tree Classification in R Step 1
- 229-Decision Tree Classification in R Step 2
- 230-Decision Tree Classification in R Step 3
- 232-Random Forest Classification Intuition
- 233-Random Forest Classification in Python Step 1
- 234-Random Forest Classification in Python Step 2
- 235-Random Forest Classification in R Step 1
- 236-Random Forest Classification in R Step 2
- 237-Random Forest Classification in R Step 3
- 240-Confusion Matrix Accuracy Ratios
- 241-ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION STEP 1
- 242-ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION STEP 2
- 243-ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION STEP 3
- 244-ULTIMATE DEMO OF THE POWERFUL CLASSIFICATION CODE TEMPLATES IN ACTION STEP 4
- 245-False Positives False Negatives
- 246-Accuracy Paradox
- 247-CAP Curve
- 248-CAP Curve Analysis
- 252-What is Clustering Supervised vs Unsupervised Learning
- 253-K Means Clustering Intuition
- 254-The Elbow Method
- 255-K Means
- 257-K Means Clustering in Python Step 1b
- 258-K Means Clustering in Python Step 2a
- 259-K Means Clustering in Python Step 2b
- 260-K Means Clustering in Python Step 3a
- 261-K Means Clustering in Python Step 3b
- 262-K Means Clustering in Python Step 3c
- 263-K Means Clustering in Python Step 4
- 264-K Means Clustering in Python Step 5a
- 265-K Means Clustering in Python Step 5b
- 266-K Means Clustering in Python Step 5c
- 267-K Means Clustering in R Step 1
- 268-K Means Clustering in R Step 2
- 270-Hierarchical Clustering Intuition
- 271-Hierarchical Clustering How Dendrograms Work
- 272-Hierarchical Clustering Using Dendrograms
- 273-Hierarchical Clustering in Python Step 1
- 274-Hierarchical Clustering in Python Step 2a
- 275-Hierarchical Clustering in Python Step 2b
- 276-Hierarchical Clustering in Python Step 2c
- 278-Hierarchical Clustering in Python Step 3b
- 279-Hierarchical Clustering in R Step 1
- 280-Hierarchical Clustering in R Step 2
- 281-Hierarchical Clustering in R Step 3
- 282-Hierarchical Clustering in R Step 4
- 283-Hierarchical Clustering in R Step 5
- 287-Apriori Intuition
- 288-Apriori in Python Step 1
- 289-Apriori in Python Step 2
- 290-Apriori in Python Step 3
- 291-Apriori in Python Step 4
- 292-Apriori in R Step 1
- 293-Apriori in R Step 2
- 294-Apriori in R Step 3
- 296-Eclat Intuiti
- 297-Eclat in Python
- 298-Eclat in R
- 301-The Multi Armed Bandit Problem
- 302-Upper Confidence Bound UCB Intuition
- 303-Upper Confidence Bound in Python Step 1
- 304-Upper Confidence Bound in Python Step 2
- 305-Upper Confidence Bound in Python Step 3
- 306-Upper Confidence Bound in Python Step 4
- 307-Upper Confidence Bound in Python Step 5
- 308-Upper Confidence Bound in Python Step 6
- 309-Upper Confidence Bound in Python Step 7
- 310-Upper Confidence Bound in R Step 1
- 311-Upper Confidence Bound in R Step 2
- 312-Upper Confidence Bound in R Step 3
- 313-Upper Confidence Bound in R Step 4
- 315-Thompson Sampling Intuition
- 316-Algorithm Comparison UCB vs Thompson Sampling
- 317-Thompson Sampling in Python Step 1
- 318-Thompson Sampling in Python Step 2
- 319-Thompson Sampling in Python Step 3
- 320-Thompson Sampling in Python Step 4
- 322-Thompson Sampling in R Step 1
- 323-Thompson Sampling in R Step 2
- 325-Welcome to Part 7 Natural Language Processing
- 327-Types of Natural Language Processing
- 328-Classical vs Deep Learning Models
- 329-Bag Of Words Model
- 330-Natural Language Processing in Python Step 1
- 331-Natural Language Processing in Python Step 2
- 332-Natural Language Processing in Python Step 3
- 333-Natural Language Processing in Python Step 4
- 334-Natural Language Processing in Python Step 5
- 335-Natural Language Processing in Python Step 6
- 338-Natural Language Processing in R Step 1
- 340-Natural Language Processing in R Step 2
- 341-Natural Language Processing in R Step 3
- 342-Natural Language Processing in R Step 4
- 343-Natural Language Processing in R Step 5
- 344-Natural Language Processing in R Step 6
- 345-Natural Language Processing in R Step 7
- 346-Natural Language Processing in R Step 8
- 347-Natural Language Processing in R Step 9
- 348-Natural Language Processing in R Step 10
- 352-What is Deep Learning
- 354-Plan of attack
- 355-The Neuron
- 356-The Activation Function
- 357-How do Neural Networks work
- 358-How do Neural Networks learn
- 359-Gradient Descent
- 360-Stochastic Gradient Descent
- 361-Backpropagation
- 362-Business Problem Description
- 363-ANN in Python Step 1
- 364-ANN in Python Step 2
- 365-ANN in Python Step 3
- 366-ANN in Python Step 4
- 367-ANN in Python Step 5
- 368-ANN in R Step 1
- 369-ANN in R Step 2
- 370-ANN in R Step 3
- 371-ANN in R Step 4 Last step
- 375-Plan of attack
- 376-What are convolutional neural networks
- 377-Step 1 Convolution Operation
- 378-Step 1 b
- 379-Step 2 Pooling
- 380-Step 3 Flattening
- 381-Step 4 Full Connection
- 382-Summary
- 383-Softmax Cross Entropy
- 384-CNN in Python Step 1
- 385-CNN in Python Step 2
- 386-CNN in Python Step 3
- 387-CNN in Python Step 4
- 388-CNN in Python Step 5
- 389-CNN in Python FINAL DEMO
- 393-Principal Component Analysis PCA Intuition
- 394-PCA in Python Step 1
- 395-PCA in Python Step 2
- 396-PCA in R Step 1
- 397-PCA in R Step 2
- 398-PCA in R Step 3
- 400-Linear Discriminant Analysis LDA Intuition
- 401-LDA in Python
- 402-LDA in R
- 404-Kernel PCA in Python
- 405-Kernel PCA in R
- 407-k Fold Cross Validation in Python
- 408-Grid Search in Python
- 409-k Fold Cross Validation in R
- 410-Grid Search in R
- 411-XGBoost in Python
- 413-XGBoost in R
- 415-Logistic Regression Intuition