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1 - Welcome to the course Here we will help you get started in the best conditions
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10 - Decision Tree Regression
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11 - Random Forest Regression
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12 - Evaluating Regression Models Performance
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13 - Regression Model Selection in Python
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14 - Regression Model Selection in R
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15 - Part 3 Classification
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16 - Logistic Regression
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17 - KNearest Neighbors KNN
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18 - Support Vector Machine SVM
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19 - Kernel SVM
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2 - Part 1 Data Preprocessing
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20 - Naive Bayes
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21 - Decision Tree Classification
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22 - Random Forest Classification
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23 - Classification Model Selection in Python
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24 - Evaluating Classification Models Performance
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25 - Part 4 Clustering
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26 - KMeans Clustering
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27 - Hierarchical Clustering
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28 - Part 5 Association Rule Learning
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29 - Apriori
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3 - Data Preprocessing in Python
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30 - Eclat
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31 - Part 6 Reinforcement Learning
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32 - Upper Confidence Bound UCB
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33 - Thompson Sampling
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34 - Part 7 Natural Language Processing
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35 - Part 8 Deep Learning
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36 - Artificial Neural Networks
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37 - Convolutional Neural Networks
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38 - Part 9 Dimensionality Reduction
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39 - Principal Component Analysis PCA
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4 - Data Preprocessing in R
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40 - Linear Discriminant Analysis LDA
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41 - Kernel PCA
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42 - Part 10 Model Selection Boosting
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43 - Model Selection
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44 - XGBoost
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45 - Exclusive Offer
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46 - Annex Logistic Regression Long Explanation
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5 - Part 2 Regression
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6 - Simple Linear Regression
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7 - Multiple Linear Regression
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8 - Polynomial Regression
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9 - Support Vector Regression SVR
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