人工智能国外教程

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教程目录:
├─01 Welcome to the course!
│ 001 Applications of Machine Learning-subtitle-en.srt
│ 001 Applications of Machine Learning.mp4
│ 002 Why Machine Learning is the Future-subtitle-en.srt
│ 002 Why Machine Learning is the Future.mp4
│ 003 Installing R and R Studio (MAC & Windows)-subtitle-en.srt
│ 003 Installing R and R Studio (MAC & Windows).mp4
│ 004 Update_ Recommended Anaconda Version.html
│ 005 Installing Python and Anaconda (MAC & Windows)-subtitle-en.srt
│ 005 Installing Python and Anaconda (MAC & Windows).mp4
│ 006 BONUS_ Meet your instructors.html

├─02 ——————– Part 1_ Data Preprocessing ——————–
│ 007 Welcome to Part 1 – Data Preprocessing-subtitle-en.srt
│ 007 Welcome to Part 1 – Data Preprocessing.mp4
│ 008 Get the dataset-subtitle-en.srt
│ 008 Get the dataset.mp4
│ 009 Importing the Libraries-subtitle-en.srt
│ 009 Importing the Libraries.mp4
│ 010 Importing the Dataset-subtitle-en.srt
│ 010 Importing the Dataset.mp4
│ 011 For Python learners_ summary of Object-oriented programming_ classes & objects.html
│ 012 Missing Data-subtitle-en.srt
│ 012 Missing Data.mp4
│ 013 Categorical Data-subtitle-en.srt
│ 013 Categorical Data.mp4
│ 014 Splitting the Dataset into the Training set and Test set-subtitle-en.srt
│ 014 Splitting the Dataset into the Training set and Test set.mp4
│ 015 Feature Scaling-subtitle-en.srt
│ 015 Feature Scaling.mp4
│ 016 And here is our Data Preprocessing Template!-subtitle-en.srt
│ 016 And here is our Data Preprocessing Template!.mp4

├─03 ——————– Part 2_ Regression ——————–
│ 017 Welcome to Part 2 – Regression.html

├─04 Simple Linear Regression
│ 018 How to get the dataset-subtitle-en.srt
│ 018 How to get the dataset.mp4
│ 019 Dataset + Business Problem Description-subtitle-en.srt
│ 019 Dataset + Business Problem Description.mp4
│ 020 Simple Linear Regression Intuition – Step 1-subtitle-en.srt
│ 020 Simple Linear Regression Intuition – Step 1.mp4
│ 021 Simple Linear Regression Intuition – Step 2-subtitle-en.srt
│ 021 Simple Linear Regression Intuition – Step 2.mp4
│ 022 Simple Linear Regression in Python – Step 1-subtitle-en.srt
│ 022 Simple Linear Regression in Python – Step 1.mp4
│ 023 Simple Linear Regression in Python – Step 2-subtitle-en.srt
│ 023 Simple Linear Regression in Python – Step 2.mp4
│ 024 Simple Linear Regression in Python – Step 3-subtitle-en.srt
│ 024 Simple Linear Regression in Python – Step 3.mp4
│ 025 Simple Linear Regression in Python – Step 4-subtitle-en.srt
│ 025 Simple Linear Regression in Python – Step 4.mp4
│ 026 Simple Linear Regression in R – Step 1-subtitle-en.srt
│ 026 Simple Linear Regression in R – Step 1.mp4
│ 027 Simple Linear Regression in R – Step 2-subtitle-en.srt
│ 027 Simple Linear Regression in R – Step 2.mp4
│ 028 Simple Linear Regression in R – Step 3-subtitle-en.srt
│ 028 Simple Linear Regression in R – Step 3.mp4
│ 029 Simple Linear Regression in R – Step 4-subtitle-en.srt
│ 029 Simple Linear Regression in R – Step 4.mp4

├─05 Multiple Linear Regression
│ 030 How to get the dataset-subtitle-en.srt
│ 030 How to get the dataset.mp4
│ 031 Dataset + Business Problem Description-subtitle-en.srt
│ 031 Dataset + Business Problem Description.mp4
│ 032 Multiple Linear Regression Intuition – Step 1-subtitle-en.srt
│ 032 Multiple Linear Regression Intuition – Step 1.mp4
│ 033 Multiple Linear Regression Intuition – Step 2-subtitle-en.srt
│ 033 Multiple Linear Regression Intuition – Step 2.mp4
│ 034 Multiple Linear Regression Intuition – Step 3-subtitle-en.srt
│ 034 Multiple Linear Regression Intuition – Step 3.mp4
│ 035 Multiple Linear Regression Intuition – Step 4-subtitle-en.srt
│ 035 Multiple Linear Regression Intuition – Step 4.mp4
│ 036 Multiple Linear Regression Intuition – Step 5-subtitle-en.srt
│ 036 Multiple Linear Regression Intuition – Step 5.mp4
│ 037 Multiple Linear Regression in Python – Step 1-subtitle-en.srt
│ 037 Multiple Linear Regression in Python – Step 1.mp4
│ 038 Multiple Linear Regression in Python – Step 2-subtitle-en.srt
│ 038 Multiple Linear Regression in Python – Step 2.mp4
│ 039 Multiple Linear Regression in Python – Step 3-subtitle-en.srt
│ 039 Multiple Linear Regression in Python – Step 3.mp4
│ 040 Multiple Linear Regression in Python – Backward Elimination – Preparation-subtitle-en.srt
│ 040 Multiple Linear Regression in Python – Backward Elimination – Preparation.mp4
│ 041 Multiple Linear Regression in Python – Backward Elimination – HOMEWORK !-subtitle-en.srt
│ 041 Multiple Linear Regression in Python – Backward Elimination – HOMEWORK !.mp4
│ 042 Multiple Linear Regression in Python – Backward Elimination – Homework Solution-subtitle-en.srt
│ 042 Multiple Linear Regression in Python – Backward Elimination – Homework Solution.mp4
│ 043 Multiple Linear Regression in R – Step 1-subtitle-en.srt
│ 043 Multiple Linear Regression in R – Step 1.mp4
│ 044 Multiple Linear Regression in R – Step 2-subtitle-en.srt
│ 044 Multiple Linear Regression in R – Step 2.mp4
│ 045 Multiple Linear Regression in R – Step 3-subtitle-en.srt
│ 045 Multiple Linear Regression in R – Step 3.mp4
│ 046 Multiple Linear Regression in R – Backward Elimination – HOMEWORK !-subtitle-en.srt
│ 046 Multiple Linear Regression in R – Backward Elimination – HOMEWORK !.mp4
│ 047 Multiple Linear Regression in R – Backward Elimination – Homework Solution-subtitle-en.srt
│ 047 Multiple Linear Regression in R – Backward Elimination – Homework Solution.mp4

├─06 Polynomial Regression
│ 048 Polynomial Regression Intuition-subtitle-en.srt
│ 048 Polynomial Regression Intuition.mp4
│ 049 How to get the dataset-subtitle-en.srt
│ 049 How to get the dataset.mp4
│ 050 Polynomial Regression in Python – Step 1-subtitle-en.srt
│ 050 Polynomial Regression in Python – Step 1.mp4
│ 051 Polynomial Regression in Python – Step 2-subtitle-en.srt
│ 051 Polynomial Regression in Python – Step 2.mp4
│ 052 Polynomial Regression in Python – Step 3-subtitle-en.srt
│ 052 Polynomial Regression in Python – Step 3.mp4
│ 053 Polynomial Regression in Python – Step 4-subtitle-en.srt
│ 053 Polynomial Regression in Python – Step 4.mp4
│ 054 Python Regression Template-subtitle-en.srt
│ 054 Python Regression Template.mp4
│ 055 Polynomial Regression in R – Step 1-subtitle-en.srt
│ 055 Polynomial Regression in R – Step 1.mp4
│ 056 Polynomial Regression in R – Step 2-subtitle-en.srt
│ 056 Polynomial Regression in R – Step 2.mp4
│ 057 Polynomial Regression in R – Step 3-subtitle-en.srt
│ 057 Polynomial Regression in R – Step 3.mp4
│ 058 Polynomial Regression in R – Step 4-subtitle-en.srt
│ 058 Polynomial Regression in R – Step 4.mp4
│ 059 R Regression Template-subtitle-en.srt
│ 059 R Regression Template.mp4

├─07 Support Vector Regression (SVR)
│ 060 How to get the dataset-subtitle-en.srt
│ 060 How to get the dataset.mp4
│ 061 SVR in Python-subtitle-en.srt
│ 061 SVR in Python.mp4
│ 062 SVR in R-subtitle-en.srt
│ 062 SVR in R.mp4

├─08 Decision Tree Regression
│ 063 Decision Tree Regression Intuition-subtitle-en.srt
│ 063 Decision Tree Regression Intuition.mp4
│ 064 How to get the dataset-subtitle-en.srt
│ 064 How to get the dataset.mp4
│ 065 Decision Tree Regression in Python-subtitle-en.srt
│ 065 Decision Tree Regression in Python.mp4
│ 066 Decision Tree Regression in R-subtitle-en.srt
│ 066 Decision Tree Regression in R.mp4

├─09 Random Forest Regression
│ 067 Random Forest Regression Intuition-subtitle-en.srt
│ 067 Random Forest Regression Intuition.mp4
│ 068 How to get the dataset-subtitle-en.srt
│ 068 How to get the dataset.mp4
│ 069 Random Forest Regression in Python-subtitle-en.srt
│ 069 Random Forest Regression in Python.mp4
│ 070 Random Forest Regression in R-subtitle-en.srt
│ 070 Random Forest Regression in R.mp4

├─10 Evaluating Regression Models Performance
│ 071 R-Squared Intuition-subtitle-en.srt
│ 071 R-Squared Intuition.mp4
│ 072 Adjusted R-Squared Intuition-subtitle-en.srt
│ 072 Adjusted R-Squared Intuition.mp4
│ 073 Evaluating Regression Models Performance – Homework’s Final Part-subtitle-en.srt
│ 073 Evaluating Regression Models Performance – Homework’s Final Part.mp4
│ 074 Interpreting Linear Regression Coefficients-subtitle-en.srt
│ 074 Interpreting Linear Regression Coefficients.mp4
│ 075 Conclusion of Part 2 – Regression.html

├─11 ——————– Part 3_ Classification ——————–
│ 076 Welcome to Part 3 – Classification.html

├─12 Logistic Regression
│ 077 Logistic Regression Intuition-subtitle-en.srt
│ 077 Logistic Regression Intuition.mp4
│ 078 How to get the dataset-subtitle-en.srt
│ 078 How to get the dataset.mp4
│ 079 Logistic Regression in Python – Step 1-subtitle-en.srt
│ 079 Logistic Regression in Python – Step 1.mp4
│ 080 Logistic Regression in Python – Step 2-subtitle-en.srt
│ 080 Logistic Regression in Python – Step 2.mp4
│ 081 Logistic Regression in Python – Step 3-subtitle-en.srt
│ 081 Logistic Regression in Python – Step 3.mp4
│ 082 Logistic Regression in Python – Step 4-subtitle-en.srt
│ 082 Logistic Regression in Python – Step 4.mp4
│ 083 Logistic Regression in Python – Step 5-subtitle-en.srt
│ 083 Logistic Regression in Python – Step 5.mp4
│ 084 Python Classification Template(1).mp4
│ 084 Python Classification Template-subtitle-en.srt
│ 084 Python Classification Template.mp4
│ 085 Logistic Regression in R – Step 1-subtitle-en.srt
│ 085 Logistic Regression in R – Step 1.mp4
│ 086 Logistic Regression in R – Step 2-subtitle-en.srt
│ 086 Logistic Regression in R – Step 2.mp4
│ 087 Logistic Regression in R – Step 3-subtitle-en.srt
│ 087 Logistic Regression in R – Step 3.mp4
│ 088 Logistic Regression in R – Step 4-subtitle-en.srt
│ 088 Logistic Regression in R – Step 4.mp4
│ 089 Logistic Regression in R – Step 5-subtitle-en.srt
│ 089 Logistic Regression in R – Step 5.mp4
│ 090 R Classification Template-subtitle-en.srt
│ 090 R Classification Template.mp4

├─13 K-Nearest Neighbors (K-NN)
│ 091 K-Nearest Neighbor Intuition-subtitle-en.srt
│ 091 K-Nearest Neighbor Intuition.mp4
│ 092 How to get the dataset-subtitle-en.srt
│ 092 How to get the dataset.mp4
│ 093 K-NN in Python-subtitle-en.srt
│ 093 K-NN in Python.mp4
│ 094 K-NN in R-subtitle-en.srt
│ 094 K-NN in R.mp4

├─14 Support Vector Machine (SVM)
│ 095 SVM Intuition-subtitle-en.srt
│ 095 SVM Intuition.mp4
│ 096 How to get the dataset-subtitle-en.srt
│ 096 How to get the dataset.mp4
│ 097 SVM in Python-subtitle-en.srt
│ 097 SVM in Python.mp4
│ 098 SVM in R-subtitle-en.srt
│ 098 SVM in R.mp4
│ 098 SVM.zip

├─15 Kernel SVM
│ 099 Kernel SVM Intuition-subtitle-en.srt
│ 099 Kernel SVM Intuition.mp4
│ 100 Mapping to a higher dimension-subtitle-en.srt
│ 100 Mapping to a higher dimension.mp4
│ 101 The Kernel Trick-subtitle-en.srt
│ 101 The Kernel Trick.mp4
│ 102 Types of Kernel Functions-subtitle-en.srt
│ 102 Types of Kernel Functions.mp4
│ 103 How to get the dataset-subtitle-en.srt
│ 103 How to get the dataset.mp4
│ 104 Kernel SVM in Python-subtitle-en.srt
│ 104 Kernel SVM in Python.mp4
│ 105 Kernel SVM in R-subtitle-en.srt
│ 105 Kernel SVM in R.mp4

├─16 Naive Bayes
│ 106 Bayes Theorem-subtitle-en.srt
│ 106 Bayes Theorem.mp4
│ 107 Naive Bayes Intuition-subtitle-en.srt
│ 107 Naive Bayes Intuition.mp4
│ 108 Naive Bayes Intuition (Challenge Reveal)-subtitle-en.srt
│ 108 Naive Bayes Intuition (Challenge Reveal).mp4
│ 109 Naive Bayes Intuition (Extras)-subtitle-en.srt
│ 109 Naive Bayes Intuition (Extras).mp4
│ 110 How to get the dataset-subtitle-en.srt
│ 110 How to get the dataset.mp4
│ 111 Naive Bayes in Python-subtitle-en.srt
│ 111 Naive Bayes in Python.mp4
│ 112 Naive Bayes in R-subtitle-en.srt
│ 112 Naive Bayes in R.mp4

├─17 Decision Tree Classification
│ 113 Decision Tree Classification Intuition-subtitle-en.srt
│ 113 Decision Tree Classification Intuition.mp4
│ 114 How to get the dataset-subtitle-en.srt
│ 114 How to get the dataset.mp4
│ 115 Decision Tree Classification in Python-subtitle-en.srt
│ 115 Decision Tree Classification in Python.mp4
│ 116 Decision Tree Classification in R-subtitle-en.srt
│ 116 Decision Tree Classification in R.mp4

├─18 Random Forest Classification
│ 117 Random Forest Classification Intuition-subtitle-en.srt
│ 117 Random Forest Classification Intuition.mp4
│ 118 How to get the dataset-subtitle-en.srt
│ 118 How to get the dataset.mp4
│ 119 Random Forest Classification in Python-subtitle-en.srt
│ 119 Random Forest Classification in Python.mp4
│ 120 Random Forest Classification in R-subtitle-en.srt
│ 120 Random Forest Classification in R.mp4

├─19 Evaluating Classification Models Performance
│ 121 False Positives & False Negatives-subtitle-en.srt
│ 121 False Positives & False Negatives.mp4
│ 122 Confusion Matrix-subtitle-en.srt
│ 122 Confusion Matrix.mp4
│ 123 Accuracy Paradox-subtitle-en.srt
│ 123 Accuracy Paradox.mp4
│ 124 CAP Curve-subtitle-en.srt
│ 124 CAP Curve.mp4
│ 125 CAP Curve Analysis-subtitle-en.srt
│ 125 CAP Curve Analysis.mp4
│ 126 Conclusion of Part 3 – Classification.html

├─20 ——————– Part 4_ Clustering ——————–
│ 127 Welcome to Part 4 – Clustering.html

├─21 K-Means Clustering
│ 128 K-Means Clustering Intuition-subtitle-en.srt
│ 128 K-Means Clustering Intuition.mp4
│ 129 K-Means Random Initialization Trap-subtitle-en.srt
│ 129 K-Means Random Initialization Trap.mp4
│ 130 K-Means Selecting The Number Of Clusters-subtitle-en.srt
│ 130 K-Means Selecting The Number Of Clusters.mp4
│ 131 How to get the dataset-subtitle-en.srt
│ 131 How to get the dataset.mp4
│ 132 K-Means Clustering in Python-subtitle-en.srt
│ 132 K-Means Clustering in Python.mp4
│ 133 K-Means Clustering in R-subtitle-en.srt
│ 133 K-Means Clustering in R.mp4

├─22 Hierarchical Clustering
│ 134 Hierarchical Clustering Intuition-subtitle-en.srt
│ 134 Hierarchical Clustering Intuition.mp4
│ 135 Hierarchical Clustering How Dendrograms Work-subtitle-en.srt
│ 135 Hierarchical Clustering How Dendrograms Work.mp4
│ 136 Hierarchical Clustering Using Dendrograms-subtitle-en.srt
│ 136 Hierarchical Clustering Using Dendrograms.mp4
│ 137 How to get the dataset-subtitle-en.srt
│ 137 How to get the dataset.mp4
│ 138 HC in Python – Step 1-subtitle-en.srt
│ 138 HC in Python – Step 1.mp4
│ 139 HC in Python – Step 2-subtitle-en.srt
│ 139 HC in Python – Step 2.mp4
│ 140 HC in Python – Step 3-subtitle-en.srt
│ 140 HC in Python – Step 3.mp4
│ 141 HC in Python – Step 4-subtitle-en.srt
│ 141 HC in Python – Step 4.mp4
│ 142 HC in Python – Step 5-subtitle-en.srt
│ 142 HC in Python – Step 5.mp4
│ 143 HC in R – Step 1-subtitle-en.srt
│ 143 HC in R – Step 1.mp4
│ 144 HC in R – Step 2-subtitle-en.srt
│ 144 HC in R – Step 2.mp4
│ 145 HC in R – Step 3-subtitle-en.srt
│ 145 HC in R – Step 3.mp4
│ 146 HC in R – Step 4-subtitle-en.srt
│ 146 HC in R – Step 4.mp4
│ 147 HC in R – Step 5-subtitle-en.srt
│ 147 HC in R – Step 5.mp4
│ 148 Conclusion of Part 4 – Clustering.html

├─23 ——————– Part 5_ Association Rule Learning ——————–
│ 149 Welcome to Part 5 – Association Rule Learning.html

├─24 Apriori
│ 150 Apriori Intuition-subtitle-en.srt
│ 150 Apriori Intuition.mp4
│ 151 How to get the dataset-subtitle-en.srt
│ 151 How to get the dataset.mp4
│ 152 Apriori in R – Step 1-subtitle-en.srt
│ 152 Apriori in R – Step 1.mp4
│ 153 Apriori in R – Step 2-subtitle-en.srt
│ 153 Apriori in R – Step 2.mp4
│ 154 Apriori in R – Step 3-subtitle-en.srt
│ 154 Apriori in R – Step 3.mp4
│ 155 Apriori in Python – Step 1-subtitle-en.srt
│ 155 Apriori in Python – Step 1.mp4
│ 156 Apriori in Python – Step 2-subtitle-en.srt
│ 156 Apriori in Python – Step 2.mp4
│ 157 Apriori in Python – Step 3-subtitle-en.srt
│ 157 Apriori in Python – Step 3.mp4

├─25 Eclat
│ 158 Eclat Intuition-subtitle-en.srt
│ 158 Eclat Intuition.mp4
│ 159 How to get the dataset-subtitle-en.srt
│ 159 How to get the dataset.mp4
│ 160 Eclat in R-subtitle-en.srt
│ 160 Eclat in R.mp4
│ 160 Eclat.zip

├─26 ——————– Part 6_ Reinforcement Learning ——————–
│ 161 Welcome to Part 6 – Reinforcement Learning.html

├─27 Upper Confidence Bound (UCB)
│ 162 The Multi-Armed Bandit Problem-subtitle-en.srt
│ 162 The Multi-Armed Bandit Problem.mp4
│ 163 Upper Confidence Bound (UCB) Intuition-subtitle-en.srt
│ 163 Upper Confidence Bound (UCB) Intuition.mp4
│ 164 How to get the dataset-subtitle-en.srt
│ 164 How to get the dataset.mp4
│ 165 Upper Confidence Bound in Python – Step 1-subtitle-en.srt
│ 165 Upper Confidence Bound in Python – Step 1.mp4
│ 166 Upper Confidence Bound in Python – Step 2-subtitle-en.srt
│ 166 Upper Confidence Bound in Python – Step 2.mp4
│ 167 Upper Confidence Bound in Python – Step 3-subtitle-en.srt
│ 167 Upper Confidence Bound in Python – Step 3.mp4
│ 168 Upper Confidence Bound in Python – Step 4-subtitle-en.srt
│ 168 Upper Confidence Bound in Python – Step 4.mp4
│ 169 Upper Confidence Bound in R – Step 1-subtitle-en.srt
│ 169 Upper Confidence Bound in R – Step 1.mp4
│ 170 Upper Confidence Bound in R – Step 2-subtitle-en.srt
│ 170 Upper Confidence Bound in R – Step 2.mp4
│ 171 Upper Confidence Bound in R – Step 3-subtitle-en.srt
│ 171 Upper Confidence Bound in R – Step 3.mp4
│ 172 Upper Confidence Bound in R – Step 4-subtitle-en.srt
│ 172 Upper Confidence Bound in R – Step 4.mp4

├─28 Thompson Sampling
│ 173 Thompson Sampling Intuition-subtitle-en.srt
│ 173 Thompson Sampling Intuition.mp4
│ 174 Algorithm Comparison_ UCB vs Thompson Sampling-subtitle-en.srt
│ 174 Algorithm Comparison_ UCB vs Thompson Sampling.mp4
│ 175 How to get the dataset-subtitle-en.srt
│ 175 How to get the dataset.mp4
│ 176 Thompson Sampling in Python – Step 1-subtitle-en.srt
│ 176 Thompson Sampling in Python – Step 1.mp4
│ 177 Thompson Sampling in Python – Step 2-subtitle-en.srt
│ 177 Thompson Sampling in Python – Step 2.mp4
│ 178 Thompson Sampling in R – Step 1-subtitle-en.srt
│ 178 Thompson Sampling in R – Step 1.mp4
│ 179 Thompson Sampling in R – Step 2-subtitle-en.srt
│ 179 Thompson Sampling in R – Step 2.mp4

├─29 ——————– Part 7_ Natural Language Processing ——————–
│ 180 Welcome to Part 7 – Natural Language Processing.html
│ 181 How to get the dataset-subtitle-en.srt
│ 181 How to get the dataset.mp4
│ 182 Natural Language Processing in Python – Step 1-subtitle-en.srt
│ 182 Natural Language Processing in Python – Step 1.mp4
│ 183 Natural Language Processing in Python – Step 2-subtitle-en.srt
│ 183 Natural Language Processing in Python – Step 2.mp4
│ 184 Natural Language Processing in Python – Step 3-subtitle-en.srt
│ 184 Natural Language Processing in Python – Step 3.mp4
│ 185 Natural Language Processing in Python – Step 4-subtitle-en.srt
│ 185 Natural Language Processing in Python – Step 4.mp4
│ 186 Natural Language Processing in Python – Step 5-subtitle-en.srt
│ 186 Natural Language Processing in Python – Step 5.mp4
│ 187 Natural Language Processing in Python – Step 6-subtitle-en.srt
│ 187 Natural Language Processing in Python – Step 6.mp4
│ 188 Natural Language Processing in Python – Step 7-subtitle-en.srt
│ 188 Natural Language Processing in Python – Step 7.mp4
│ 189 Natural Language Processing in Python – Step 8-subtitle-en.srt
│ 189 Natural Language Processing in Python – Step 8.mp4
│ 190 Natural Language Processing in Python – Step 9-subtitle-en.srt
│ 190 Natural Language Processing in Python – Step 9.mp4
│ 191 Natural Language Processing in Python – Step 10-subtitle-en.srt
│ 191 Natural Language Processing in Python – Step 10.mp4
│ 192 Homework Challenge.html
│ 193 Natural Language Processing in R – Step 1-subtitle-en.srt
│ 193 Natural Language Processing in R – Step 1.mp4
│ 194 Natural Language Processing in R – Step 2-subtitle-en.srt
│ 194 Natural Language Processing in R – Step 2.mp4
│ 195 Natural Language Processing in R – Step 3-subtitle-en.srt
│ 195 Natural Language Processing in R – Step 3.mp4
│ 196 Natural Language Processing in R – Step 4-subtitle-en.srt
│ 196 Natural Language Processing in R – Step 4.mp4
│ 197 Natural Language Processing in R – Step 5-subtitle-en.srt
│ 197 Natural Language Processing in R – Step 5.mp4
│ 198 Natural Language Processing in R – Step 6-subtitle-en.srt
│ 198 Natural Language Processing in R – Step 6.mp4
│ 199 Natural Language Processing in R – Step 7-subtitle-en.srt
│ 199 Natural Language Processing in R – Step 7.mp4
│ 200 Natural Language Processing in R – Step 8-subtitle-en.srt
│ 200 Natural Language Processing in R – Step 8.mp4
│ 201 Natural Language Processing in R – Step 9-subtitle-en.srt
│ 201 Natural Language Processing in R – Step 9.mp4
│ 202 Natural Language Processing in R – Step 10-subtitle-en.srt
│ 202 Natural Language Processing in R – Step 10.mp4
│ 203 Homework Challenge.html

├─30 ——————– Part 8_ Deep Learning ——————–
│ 204 Welcome to Part 8 – Deep Learning.html
│ 205 What is Deep Learning_-subtitle-en.srt
│ 205 What is Deep Learning_.mp4

├─31 Artificial Neural Networks
│ 206 Plan of attack-subtitle-en.srt
│ 206 Plan of attack.mp4
│ 207 The Neuron-subtitle-en.srt
│ 207 The Neuron.mp4
│ 208 The Activation Function-subtitle-en.srt
│ 208 The Activation Function.mp4
│ 209 How do Neural Networks work_-subtitle-en.srt
│ 209 How do Neural Networks work_.mp4
│ 210 How do Neural Networks learn_-subtitle-en.srt
│ 210 How do Neural Networks learn_.mp4
│ 211 Gradient Descent-subtitle-en.srt
│ 211 Gradient Descent.mp4
│ 212 Stochastic Gradient Descent-subtitle-en.srt
│ 212 Stochastic Gradient Descent.mp4
│ 213 Backpropagation-subtitle-en.srt
│ 213 Backpropagation.mp4
│ 214 How to get the dataset-subtitle-en.srt
│ 214 How to get the dataset.mp4
│ 215 Business Problem Description-subtitle-en.srt
│ 215 Business Problem Description.mp4
│ 216 ANN in Python – Step 1 – Installing Theano_ Tensorflow and Keras-subtitle-en.srt
│ 216 ANN in Python – Step 1 – Installing Theano_ Tensorflow and Keras.mp4
│ 217 ANN in Python – Step 2-subtitle-en.srt
│ 217 ANN in Python – Step 2.mp4
│ 218 ANN in Python – Step 3-subtitle-en.srt
│ 218 ANN in Python – Step 3.mp4
│ 219 ANN in Python – Step 4-subtitle-en.srt
│ 219 ANN in Python – Step 4.mp4
│ 220 ANN in Python – Step 5-subtitle-en.srt
│ 220 ANN in Python – Step 5.mp4
│ 221 ANN in Python – Step 6-subtitle-en.srt
│ 221 ANN in Python – Step 6.mp4
│ 222 ANN in Python – Step 7-subtitle-en.srt
│ 222 ANN in Python – Step 7.mp4
│ 223 ANN in Python – Step 8-subtitle-en.srt
│ 223 ANN in Python – Step 8.mp4
│ 224 ANN in Python – Step 9-subtitle-en.srt
│ 224 ANN in Python – Step 9.mp4
│ 225 ANN in Python – Step 10-subtitle-en.srt
│ 225 ANN in Python – Step 10.mp4
│ 226 ANN in R – Step 1-subtitle-en.srt
│ 226 ANN in R – Step 1.mp4
│ 227 ANN in R – Step 2-subtitle-en.srt
│ 227 ANN in R – Step 2.mp4
│ 228 ANN in R – Step 3-subtitle-en.srt
│ 228 ANN in R – Step 3.mp4
│ 229 ANN in R – Step 4 (Last step)-subtitle-en.srt
│ 229 ANN in R – Step 4 (Last step).mp4

├─32 Convolutional Neural Networks
│ 230 Plan of attack-subtitle-en.srt
│ 230 Plan of attack.mp4
│ 231 What are convolutional neural networks_-subtitle-en.srt
│ 231 What are convolutional neural networks_.mp4
│ 232 Step 1 – Convolution Operation-subtitle-en.srt
│ 232 Step 1 – Convolution Operation.mp4
│ 233 Step 1(b) – ReLU Layer-subtitle-en.srt
│ 233 Step 1(b) – ReLU Layer.mp4
│ 234 Step 2 – Pooling-subtitle-en.srt
│ 234 Step 2 – Pooling.mp4
│ 235 Step 3 – Flattening-subtitle-en.srt
│ 235 Step 3 – Flattening.mp4
│ 236 Step 4 – Full Connection-subtitle-en.srt
│ 236 Step 4 – Full Connection.mp4
│ 237 Summary-subtitle-en.srt
│ 237 Summary.mp4
│ 238 Softmax & Cross-Entropy-subtitle-en.srt
│ 238 Softmax & Cross-Entropy.mp4
│ 239 How to get the dataset-subtitle-en.srt
│ 239 How to get the dataset.mp4
│ 240 CNN in Python – Step 1-subtitle-en.srt
│ 240 CNN in Python – Step 1.mp4
│ 241 CNN in Python – Step 2-subtitle-en.srt
│ 241 CNN in Python – Step 2.mp4
│ 242 CNN in Python – Step 3-subtitle-en.srt
│ 242 CNN in Python – Step 3.mp4
│ 243 CNN in Python – Step 4-subtitle-en.srt
│ 243 CNN in Python – Step 4.mp4
│ 244 CNN in Python – Step 5-subtitle-en.srt
│ 244 CNN in Python – Step 5.mp4
│ 245 CNN in Python – Step 6-subtitle-en.srt
│ 245 CNN in Python – Step 6.mp4
│ 246 CNN in Python – Step 7-subtitle-en.srt
│ 246 CNN in Python – Step 7.mp4
│ 247 CNN in Python – Step 8-subtitle-en.srt
│ 247 CNN in Python – Step 8.mp4
│ 248 CNN in Python – Step 9-subtitle-en.srt
│ 248 CNN in Python – Step 9.mp4
│ 249 CNN in Python – Step 10-subtitle-en.srt
│ 249 CNN in Python – Step 10.mp4
│ 250 CNN in R.html

├─33 ——————– Part 9_ Dimensionality Reduction ——————–
│ 251 Welcome to Part 9 – Dimensionality Reduction.html

├─34 Principal Component Analysis (PCA)
│ 252 How to get the dataset-subtitle-en.srt
│ 252 How to get the dataset.mp4
│ 253 PCA in Python – Step 1-subtitle-en.srt
│ 253 PCA in Python – Step 1.mp4
│ 254 PCA in Python – Step 2-subtitle-en.srt
│ 254 PCA in Python – Step 2.mp4
│ 255 PCA in Python – Step 3-subtitle-en.srt
│ 255 PCA in Python – Step 3.mp4
│ 256 PCA in R – Step 1-subtitle-en.srt
│ 256 PCA in R – Step 1.mp4
│ 257 PCA in R – Step 2-subtitle-en.srt
│ 257 PCA in R – Step 2.mp4
│ 258 PCA in R – Step 3-subtitle-en.srt
│ 258 PCA in R – Step 3.mp4

├─35 Linear Discriminant Analysis (LDA)
│ 259 How to get the dataset-subtitle-en.srt
│ 259 How to get the dataset.mp4
│ 260 LDA in Python-subtitle-en.srt
│ 260 LDA in Python.mp4
│ 261 LDA in R-subtitle-en.srt
│ 261 LDA in R.mp4

├─36 Kernel PCA
│ 262 How to get the dataset-subtitle-en.srt
│ 262 How to get the dataset.mp4
│ 263 Kernel PCA in Python-subtitle-en.srt
│ 263 Kernel PCA in Python.mp4
│ 264 Kernel PCA in R-subtitle-en.srt
│ 264 Kernel PCA in R.mp4

├─37 ——————– Part 10_ Model Selection & Boosting ——————–
│ 265 Welcome to Part 10 – Model Selection & Boosting.html

├─38 Model Selection
│ 266 How to get the dataset-subtitle-en.srt
│ 266 How to get the dataset.mp4
│ 267 k-Fold Cross Validation in Python-subtitle-en.srt
│ 267 k-Fold Cross Validation in Python.mp4
│ 268 k-Fold Cross Validation in R-subtitle-en.srt
│ 268 k-Fold Cross Validation in R.mp4
│ 269 Grid Search in Python – Step 1-subtitle-en.srt
│ 269 Grid Search in Python – Step 1.mp4
│ 270 Grid Search in Python – Step 2-subtitle-en.srt
│ 270 Grid Search in Python – Step 2.mp4
│ 271 Grid Search in R-subtitle-en.srt
│ 271 Grid Search in R.mp4

├─39 XGBoost
│ 272 How to get the dataset-subtitle-en.srt
│ 272 How to get the dataset.mp4
│ 273 XGBoost in Python – Step 1-subtitle-en.srt
│ 273 XGBoost in Python – Step 1.mp4
│ 274 XGBoost in Python – Step 2-subtitle-en.srt
│ 274 XGBoost in Python – Step 2.mp4
│ 275 XGBoost in R-subtitle-en.srt
│ 275 XGBoost in R.mp4

└─40 Bonus Lectures
276 ___YOUR SPECIAL BONUS___.html

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