Machine Learning A-Z - Hands On Python and R In Data Science

磁力链接/BT种子名称

Machine Learning A-Z - Hands On Python and R In Data Science

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收录时间：2020-03-20
最近下载：2025-10-15

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文件列表

  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/attached_files/006 Welcome to Part 1 - Data Preprocessing/Machine-Learning-A-Z-Template-Folder.zip 238.4 MB
  • 39 XGBoost/attached_files/213 Download all the Codes and Datasets Here/Machine-Learning-A-Z.zip 238.2 MB
  • 32 Convolutional Neural Networks/attached_files/190 CNN in Python - Step 1/Convolutional-Neural-Networks.zip 232.6 MB
  • 12 Logistic Regression/080 Logistic Regression in R - Step 5.mp4 98.3 MB
  • 31 Artificial Neural Networks/177 ANN in Python - Step 2.mp4 89.0 MB
  • 17 Decision Tree Classification/102 Decision Tree Classification in R.mp4 71.5 MB
  • 14 Support Vector Machine SVM/087 SVM in R.mp4 68.5 MB
  • 18 Random Forest Classification/105 Random Forest Classification in R.mp4 67.2 MB
  • 32 Convolutional Neural Networks/198 CNN in Python - Step 9.mp4 65.4 MB
  • 18 Random Forest Classification/104 Random Forest Classification in Python.mp4 65.1 MB
  • 07 Support Vector Regression SVR/056 SVR in Python.mp4 63.1 MB
  • 05 Multiple Linear Regression/038 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK.mp4 62.0 MB
  • 27 Upper Confidence Bound UCB/145 Upper Confidence Bound in R - Step 3.mp4 60.6 MB
  • 24 Apriori/133 Apriori in R - Step 3.mp4 59.3 MB
  • 08 Decision Tree Regression/060 Decision Tree Regression in R.mp4 59.0 MB
  • 13 K-Nearest Neighbors K-NN/084 K-NN in R.mp4 58.5 MB
  • 28 Thompson Sampling/147 Thompson Sampling in Python - Step 1.mp4 58.2 MB
  • 15 Kernel SVM/092 Kernel SVM in Python.mp4 57.5 MB
  • 06 Polynomial Regression/053 Polynomial Regression in R - Step 3.mp4 57.5 MB
  • 05 Multiple Linear Regression/037 Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4 57.2 MB
  • 06 Polynomial Regression/048 Polynomial Regression in Python - Step 3.mp4 57.1 MB
  • 05 Multiple Linear Regression/039 Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4 56.9 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/172 Natural Language Processing in R - Step 10.mp4 56.8 MB
  • 27 Upper Confidence Bound UCB/141 Upper Confidence Bound in Python - Step 3.mp4 56.3 MB
  • 12 Logistic Regression/074 Logistic Regression in Python - Step 5.mp4 55.7 MB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/012 Categorical Data.mp4 55.4 MB
  • 24 Apriori/131 Apriori in R - Step 1.mp4 55.4 MB
  • 15 Kernel SVM/093 Kernel SVM in R.mp4 55.4 MB
  • 09 Random Forest Regression/062 Random Forest Regression in Python.mp4 55.3 MB
  • 05 Multiple Linear Regression/034 Multiple Linear Regression in Python - Step 1.mp4 54.7 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/159 Natural Language Processing in Python - Step 8.mp4 54.5 MB
  • 09 Random Forest Regression/063 Random Forest Regression in R.mp4 54.4 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/163 Natural Language Processing in R - Step 1.mp4 53.7 MB
  • 28 Thompson Sampling/149 Thompson Sampling in R - Step 1.mp4 53.5 MB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/013 Splitting the Dataset into the Training set and Test set.mp4 53.4 MB
  • 05 Multiple Linear Regression/043 Multiple Linear Regression in R - Backward Elimination - HOMEWORK.mp4 53.3 MB
  • 16 Naive Bayes/094 Bayes Theorem.mp4 52.9 MB
  • 31 Artificial Neural Networks/186 ANN in R - Step 1.mp4 52.3 MB
  • 21 K-Means Clustering/115 K-Means Clustering in Python.mp4 52.2 MB
  • 16 Naive Bayes/099 Naive Bayes in R.mp4 52.2 MB
  • 04 Simple Linear Regression/027 Simple Linear Regression in R - Step 4.mp4 51.5 MB
  • 24 Apriori/134 Apriori in Python - Step 1.mp4 49.7 MB
  • 13 K-Nearest Neighbors K-NN/083 K-NN in Python.mp4 49.3 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/152 Natural Language Processing in Python - Step 1.mp4 48.3 MB
  • 35 Linear Discriminant Analysis LDA/205 LDA in Python.mp4 47.6 MB
  • 05 Multiple Linear Regression/041 Multiple Linear Regression in R - Step 2.mp4 47.4 MB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/014 Feature Scaling.mp4 46.8 MB
  • 27 Upper Confidence Bound UCB/140 Upper Confidence Bound in Python - Step 2.mp4 46.7 MB
  • 31 Artificial Neural Networks/189 ANN in R - Step 4 Last step.mp4 45.9 MB
  • 08 Decision Tree Regression/059 Decision Tree Regression in Python.mp4 45.5 MB
  • 14 Support Vector Machine SVM/086 SVM in Python.mp4 43.7 MB
  • 04 Simple Linear Regression/023 Simple Linear Regression in Python - Step 4.mp4 41.3 MB
  • 31 Artificial Neural Networks/180 ANN in Python - Step 5.mp4 41.3 MB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/011 Missing Data.mp4 41.2 MB
  • 27 Upper Confidence Bound UCB/139 Upper Confidence Bound in Python - Step 1.mp4 40.9 MB
  • 17 Decision Tree Classification/101 Decision Tree Classification in Python.mp4 40.7 MB
  • 24 Apriori/132 Apriori in R - Step 2.mp4 40.7 MB
  • 38 Model Selection/209 Grid Search in Python - Step 1.mp4 40.1 MB
  • 31 Artificial Neural Networks/188 ANN in R - Step 3.mp4 39.7 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/171 Natural Language Processing in R - Step 9.mp4 39.5 MB
  • 31 Artificial Neural Networks/176 ANN in Python - Step 1 - Installing Theano Tensorflow and Keras.mp4 39.3 MB
  • 24 Apriori/135 Apriori in Python - Step 2.mp4 39.1 MB
  • 21 K-Means Clustering/116 K-Means Clustering in R.mp4 38.7 MB
  • 06 Polynomial Regression/050 Python Regression Template.mp4 38.6 MB
  • 24 Apriori/136 Apriori in Python - Step 3.mp4 37.0 MB
  • 06 Polynomial Regression/047 Polynomial Regression in Python - Step 2.mp4 36.8 MB
  • 15 Kernel SVM/090 The Kernel Trick.mp4 36.4 MB
  • 32 Convolutional Neural Networks/193 CNN in Python - Step 4.mp4 36.3 MB
  • 27 Upper Confidence Bound UCB/144 Upper Confidence Bound in R - Step 2.mp4 35.8 MB
  • 31 Artificial Neural Networks/183 ANN in Python - Step 8.mp4 35.7 MB
  • 27 Upper Confidence Bound UCB/143 Upper Confidence Bound in R - Step 1.mp4 35.7 MB
  • 07 Support Vector Regression SVR/057 SVR in R.mp4 35.4 MB
  • 36 Kernel PCA/206 Kernel PCA in Python.mp4 35.0 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/161 Natural Language Processing in Python - Step 10.mp4 34.5 MB
  • 38 Model Selection/208 k-Fold Cross Validation in Python.mp4 34.4 MB
  • 05 Multiple Linear Regression/033 Multiple Linear Regression Intuition - Step 5.mp4 34.4 MB
  • 06 Polynomial Regression/052 Polynomial Regression in R - Step 2.mp4 33.9 MB
  • 39 XGBoost/212 XGBoost in Python - Step 2.mp4 33.5 MB
  • 34 Principal Component Analysis PCA/202 PCA in Python - Step 1.mp4 33.5 MB
  • 06 Polynomial Regression/046 Polynomial Regression in Python - Step 1.mp4 33.2 MB
  • 06 Polynomial Regression/055 R Regression Template.mp4 32.9 MB
  • 16 Naive Bayes/098 Naive Bayes in Python.mp4 32.7 MB
  • 16 Naive Bayes/095 Naive Bayes Intuition.mp4 32.6 MB
  • 32 Convolutional Neural Networks/190 CNN in Python - Step 1.mp4 32.1 MB
  • 21 K-Means Clustering/112 K-Means Clustering Intuition.mp4 31.4 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/155 Natural Language Processing in Python - Step 4.mp4 31.2 MB
  • 38 Model Selection/210 Grid Search in Python - Step 2.mp4 30.9 MB
  • 31 Artificial Neural Networks/175 Business Problem Description.mp4 30.7 MB
  • 12 Logistic Regression/069 Logistic Regression Intuition.mp4 30.6 MB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/009 Importing the Dataset.mp4 30.0 MB
  • 06 Polynomial Regression/054 Polynomial Regression in R - Step 4.mp4 29.9 MB
  • 31 Artificial Neural Networks/184 ANN in Python - Step 9.mp4 29.9 MB
  • 31 Artificial Neural Networks/185 ANN in Python - Step 10.mp4 29.8 MB
  • 10 Evaluating Regression Models Performance/066 Evaluating Regression Models Performance - Homeworks Final Part.mp4 29.7 MB
  • 04 Simple Linear Regression/020 Simple Linear Regression in Python - Step 1.mp4 29.3 MB
  • 32 Convolutional Neural Networks/199 CNN in Python - Step 10.mp4 29.1 MB
  • 12 Logistic Regression/078 Logistic Regression in R - Step 3.mp4 28.8 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/153 Natural Language Processing in Python - Step 2.mp4 28.8 MB
  • 10 Evaluating Regression Models Performance/067 Interpreting Linear Regression Coefficients.mp4 28.7 MB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/015 And here is our Data Preprocessing Template.mp4 27.1 MB
  • 21 K-Means Clustering/114 K-Means Selecting The Number Of Clusters.mp4 26.9 MB
  • 18 Random Forest Classification/103 Random Forest Classification Intuition.mp4 26.9 MB
  • 34 Principal Component Analysis PCA/204 PCA in Python - Step 3.mp4 26.7 MB
  • 05 Multiple Linear Regression/036 Multiple Linear Regression in Python - Step 3.mp4 26.7 MB
  • 08 Decision Tree Regression/058 Decision Tree Regression Intuition.mp4 26.6 MB
  • 25 Eclat/137 Eclat in R.mp4 26.5 MB
  • 04 Simple Linear Regression/025 Simple Linear Regression in R - Step 2.mp4 26.1 MB
  • 04 Simple Linear Regression/021 Simple Linear Regression in Python - Step 2.mp4 25.8 MB
  • 01 Welcome to the course/004 Installing Python and Anaconda MAC Windows.mp4 25.1 MB
  • 05 Multiple Linear Regression/040 Multiple Linear Regression in R - Step 1.mp4 24.6 MB
  • 01 Welcome to the course/003 Installing R and R Studio MAC Windows.mp4 24.3 MB
  • 22 Hierarchical Clustering/119 Hierarchical Clustering Using Dendrograms.mp4 23.9 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/158 Natural Language Processing in Python - Step 7.mp4 23.2 MB
  • 34 Principal Component Analysis PCA/203 PCA in Python - Step 2.mp4 23.1 MB
  • 05 Multiple Linear Regression/044 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4 23.0 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/164 Natural Language Processing in R - Step 2.mp4 22.7 MB
  • 17 Decision Tree Classification/100 Decision Tree Classification Intuition.mp4 22.7 MB
  • 10 Evaluating Regression Models Performance/065 Adjusted R-Squared Intuition.mp4 22.5 MB
  • 39 XGBoost/211 XGBoost in Python - Step 1.mp4 22.4 MB
  • 22 Hierarchical Clustering/123 HC in Python - Step 4.mp4 22.4 MB
  • 06 Polynomial Regression/051 Polynomial Regression in R - Step 1.mp4 22.2 MB
  • 04 Simple Linear Regression/022 Simple Linear Regression in Python - Step 3.mp4 21.5 MB
  • 19 Evaluating Classification Models Performance/109 CAP Curve.mp4 21.3 MB
  • 14 Support Vector Machine SVM/085 SVM Intuition.mp4 20.9 MB
  • 16 Naive Bayes/097 Naive Bayes Intuition Extras.mp4 19.9 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/160 Natural Language Processing in Python - Step 9.mp4 19.8 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/156 Natural Language Processing in Python - Step 5.mp4 19.7 MB
  • 31 Artificial Neural Networks/187 ANN in R - Step 2.mp4 19.1 MB
  • 06 Polynomial Regression/049 Polynomial Regression in Python - Step 4.mp4 18.5 MB
  • 12 Logistic Regression/075 Python Classification Template.mp4 18.4 MB
  • 12 Logistic Regression/081 R Classification Template.mp4 18.4 MB
  • 22 Hierarchical Clustering/118 Hierarchical Clustering How Dendrograms Work.mp4 18.3 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/170 Natural Language Processing in R - Step 8.mp4 18.1 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/165 Natural Language Processing in R - Step 3.mp4 17.7 MB
  • 12 Logistic Regression/070 Logistic Regression in Python - Step 1.mp4 17.7 MB
  • 32 Convolutional Neural Networks/196 CNN in Python - Step 7.mp4 17.5 MB
  • 05 Multiple Linear Regression/031 Multiple Linear Regression Intuition - Step 3.mp4 17.4 MB
  • 22 Hierarchical Clustering/117 Hierarchical Clustering Intuition.mp4 17.3 MB
  • 22 Hierarchical Clustering/122 HC in Python - Step 3.mp4 17.0 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/168 Natural Language Processing in R - Step 6.mp4 16.9 MB
  • 12 Logistic Regression/076 Logistic Regression in R - Step 1.mp4 16.5 MB
  • 15 Kernel SVM/091 Types of Kernel Functions.mp4 16.5 MB
  • 09 Random Forest Regression/061 Random Forest Regression Intuition.mp4 16.4 MB
  • 22 Hierarchical Clustering/121 HC in Python - Step 2.mp4 16.3 MB
  • 15 Kernel SVM/089 Mapping to a higher dimension.mp4 16.1 MB
  • 21 K-Means Clustering/113 K-Means Random Initialization Trap.mp4 16.1 MB
  • 19 Evaluating Classification Models Performance/106 False Positives False Negatives.mp4 15.9 MB
  • 31 Artificial Neural Networks/182 ANN in Python - Step 7.mp4 15.6 MB
  • 12 Logistic Regression/077 Logistic Regression in R - Step 2.mp4 15.6 MB
  • 31 Artificial Neural Networks/178 ANN in Python - Step 3.mp4 15.3 MB
  • 01 Welcome to the course/002 Why Machine Learning is the Future.mp4 15.2 MB
  • 12 Logistic Regression/073 Logistic Regression in Python - Step 4.mp4 14.5 MB
  • 22 Hierarchical Clustering/126 HC in R - Step 2.mp4 14.5 MB
  • 05 Multiple Linear Regression/042 Multiple Linear Regression in R - Step 3.mp4 14.5 MB
  • 22 Hierarchical Clustering/120 HC in Python - Step 1.mp4 14.4 MB
  • 22 Hierarchical Clustering/129 HC in R - Step 5.mp4 14.3 MB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/008 Importing the Libraries.mp4 14.2 MB
  • 16 Naive Bayes/096 Naive Bayes Intuition Challenge Reveal.mp4 13.9 MB
  • 19 Evaluating Classification Models Performance/110 CAP Curve Analysis.mp4 13.6 MB
  • 05 Multiple Linear Regression/028 Dataset Business Problem Description.mp4 13.2 MB
  • 27 Upper Confidence Bound UCB/142 Upper Confidence Bound in Python - Step 4.mp4 13.0 MB
  • 32 Convolutional Neural Networks/194 CNN in Python - Step 5.mp4 13.0 MB
  • 32 Convolutional Neural Networks/195 CNN in Python - Step 6.mp4 12.5 MB
  • 31 Artificial Neural Networks/181 ANN in Python - Step 6.mp4 12.5 MB
  • 12 Logistic Regression/079 Logistic Regression in R - Step 4.mp4 12.3 MB
  • 04 Simple Linear Regression/024 Simple Linear Regression in R - Step 1.mp4 12.1 MB
  • 04 Simple Linear Regression/026 Simple Linear Regression in R - Step 3.mp4 12.0 MB
  • 28 Thompson Sampling/148 Thompson Sampling in Python - Step 2.mp4 11.8 MB
  • 12 Logistic Regression/071 Logistic Regression in Python - Step 2.mp4 11.6 MB
  • 04 Simple Linear Regression/018 Simple Linear Regression Intuition - Step 1.mp4 11.0 MB
  • 13 K-Nearest Neighbors K-NN/082 K-Nearest Neighbor Intuition.mp4 11.0 MB
  • 22 Hierarchical Clustering/128 HC in R - Step 4.mp4 10.7 MB
  • 22 Hierarchical Clustering/127 HC in R - Step 3.mp4 10.4 MB
  • 22 Hierarchical Clustering/124 HC in Python - Step 5.mp4 10.4 MB
  • 05 Multiple Linear Regression/035 Multiple Linear Regression in Python - Step 2.mp4 10.3 MB
  • 01 Welcome to the course/001 Applications of Machine Learning.mp4 10.3 MB
  • 10 Evaluating Regression Models Performance/064 R-Squared Intuition.mp4 10.3 MB
  • 31 Artificial Neural Networks/179 ANN in Python - Step 4.mp4 10.2 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/169 Natural Language Processing in R - Step 7.mp4 10.1 MB
  • 28 Thompson Sampling/150 Thompson Sampling in R - Step 2.mp4 10.0 MB
  • 27 Upper Confidence Bound UCB/146 Upper Confidence Bound in R - Step 4.mp4 10.0 MB
  • 06 Polynomial Regression/045 Polynomial Regression Intuition.mp4 9.9 MB
  • 32 Convolutional Neural Networks/197 CNN in Python - Step 8.mp4 9.4 MB
  • 19 Evaluating Classification Models Performance/107 Confusion Matrix.mp4 9.3 MB
  • 22 Hierarchical Clustering/125 HC in R - Step 1.mp4 9.0 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/157 Natural Language Processing in Python - Step 6.mp4 8.7 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/166 Natural Language Processing in R - Step 4.mp4 8.6 MB
  • 12 Logistic Regression/072 Logistic Regression in Python - Step 3.mp4 8.4 MB
  • 04 Simple Linear Regression/017 Dataset Business Problem Description.mp4 8.1 MB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/007 Get the dataset.mp4 7.6 MB
  • 32 Convolutional Neural Networks/191 CNN in Python - Step 2.mp4 7.6 MB
  • 15 Kernel SVM/088 Kernel SVM Intuition.mp4 6.7 MB
  • 04 Simple Linear Regression/019 Simple Linear Regression Intuition - Step 2.mp4 6.3 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/167 Natural Language Processing in R - Step 5.mp4 6.1 MB
  • 05 Multiple Linear Regression/032 Multiple Linear Regression Intuition - Step 4.mp4 5.6 MB
  • 19 Evaluating Classification Models Performance/108 Accuracy Paradox.mp4 4.4 MB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/154 Natural Language Processing in Python - Step 3.mp4 4.4 MB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/006 Welcome to Part 1 - Data Preprocessing.mp4 3.7 MB
  • 32 Convolutional Neural Networks/192 CNN in Python - Step 3.mp4 2.9 MB
  • 05 Multiple Linear Regression/030 Multiple Linear Regression Intuition - Step 2.mp4 2.1 MB
  • 05 Multiple Linear Regression/029 Multiple Linear Regression Intuition - Step 1.mp4 2.1 MB
  • 31 Artificial Neural Networks/attached_files/176 ANN in Python - Step 1 - Installing Theano Tensorflow and Keras/Artificial-Neural-Networks.zip 1.5 MB
  • 31 Artificial Neural Networks/attached_files/186 ANN in R - Step 1/Artificial-Neural-Networks.zip 1.5 MB
  • 27 Upper Confidence Bound UCB/attached_files/139 Upper Confidence Bound in Python - Step 1/UCB.zip 1.1 MB
  • 27 Upper Confidence Bound UCB/attached_files/143 Upper Confidence Bound in R - Step 1/UCB.zip 1.1 MB
  • 28 Thompson Sampling/attached_files/147 Thompson Sampling in Python - Step 1/Thompson-Sampling.zip 1.0 MB
  • 28 Thompson Sampling/attached_files/149 Thompson Sampling in R - Step 1/Thompson-Sampling.zip 1.0 MB
  • 05 Multiple Linear Regression/attached_files/033 Multiple Linear Regression Intuition - Step 5/Step-by-step-Blueprints-For-Building-Models.pdf 787.1 kB
  • 39 XGBoost/attached_files/211 XGBoost in Python - Step 1/XGBoost.zip 265.6 kB
  • 24 Apriori/attached_files/134 Apriori in Python - Step 1/Apriori-Python.zip 54.5 kB
  • 24 Apriori/attached_files/131 Apriori in R - Step 1/Apriori.zip 50.3 kB
  • 25 Eclat/attached_files/137 Eclat in R/Eclat.zip 49.7 kB
  • 16 Naive Bayes/captions/094 Bayes Theorem-EN.srt 31.4 kB
  • 18 Random Forest Classification/captions/105 Random Forest Classification in R-EN.srt 29.5 kB
  • 08 Decision Tree Regression/captions/060 Decision Tree Regression in R-EN.srt 29.2 kB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/attached_files/152 Natural Language Processing in Python - Step 1/Natural-Language-Processing.zip 28.6 kB
  • 29 --------------------- Part 7 Natural Language Processing ---------------------/attached_files/163 Natural Language Processing in R - Step 1/Natural-Language-Processing.zip 28.6 kB
  • 06 Polynomial Regression/captions/048 Polynomial Regression in Python - Step 3-EN.srt 28.5 kB
  • 24 Apriori/captions/133 Apriori in R - Step 3-EN.srt 28.4 kB
  • 24 Apriori/captions/131 Apriori in R - Step 1-EN.srt 28.3 kB
  • 07 Support Vector Regression SVR/captions/056 SVR in Python-EN.srt 28.1 kB
  • 06 Polynomial Regression/captions/053 Polynomial Regression in R - Step 3-EN.srt 28.1 kB
  • 18 Random Forest Classification/captions/104 Random Forest Classification in Python-EN.srt 28.1 kB
  • 12 Logistic Regression/captions/074 Logistic Regression in Python - Step 5-EN.srt 27.1 kB
  • 12 Logistic Regression/captions/080 Logistic Regression in R - Step 5-EN.srt 26.6 kB
  • 17 Decision Tree Classification/captions/102 Decision Tree Classification in R-EN.srt 26.5 kB
  • 21 K-Means Clustering/captions/115 K-Means Clustering in Python-EN.srt 25.8 kB
  • 09 Random Forest Regression/captions/063 Random Forest Regression in R-EN.srt 25.7 kB
  • 15 Kernel SVM/captions/092 Kernel SVM in Python-EN.srt 25.6 kB
  • 24 Apriori/captions/134 Apriori in Python - Step 1-EN.srt 25.4 kB
  • 05 Multiple Linear Regression/captions/043 Multiple Linear Regression in R - Backward Elimination - HOMEWORK-EN.srt 25.2 kB
  • 09 Random Forest Regression/captions/062 Random Forest Regression in Python-EN.srt 25.0 kB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/013 Splitting the Dataset into the Training set and Test set-EN.srt 24.5 kB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/012 Categorical Data-EN.srt 24.4 kB
  • 15 Kernel SVM/captions/093 Kernel SVM in R-EN.srt 23.2 kB
  • 05 Multiple Linear Regression/captions/034 Multiple Linear Regression in Python - Step 1-EN.srt 22.0 kB
  • 04 Simple Linear Regression/captions/027 Simple Linear Regression in R - Step 4-EN.srt 21.7 kB
  • 08 Decision Tree Regression/captions/059 Decision Tree Regression in Python-EN.srt 21.6 kB
  • 05 Multiple Linear Regression/captions/033 Multiple Linear Regression Intuition - Step 5-EN.srt 21.6 kB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/011 Missing Data-EN.srt 21.5 kB
  • 21 K-Means Clustering/captions/112 K-Means Clustering Intuition-EN.srt 21.4 kB
  • 16 Naive Bayes/captions/095 Naive Bayes Intuition-EN.srt 21.4 kB
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/014 Feature Scaling-EN.srt 21.3 kB
  • 13 K-Nearest Neighbors K-NN/captions/084 K-NN in R-EN.srt 21.2 kB
  • 24 Apriori/captions/132 Apriori in R - Step 2-EN.srt 21.1 kB
  • 24 Apriori/captions/135 Apriori in Python - Step 2-EN.srt 20.6 kB
  • 04 Simple Linear Regression/captions/023 Simple Linear Regression in Python - Step 4-EN.srt 20.5 kB
  • 16 Naive Bayes/captions/099 Naive Bayes in R-EN.srt 19.9 kB
  • 13 K-Nearest Neighbors K-NN/captions/083 K-NN in Python-EN.srt 19.2 kB
  • 05 Multiple Linear Regression/captions/037 Multiple Linear Regression in Python - Backward Elimination - Preparation-EN.srt 18.1 kB
  • 05 Multiple Linear Regression/captions/038 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK-EN.srt 18.0 kB
  • 24 Apriori/captions/136 Apriori in Python - Step 3-EN.srt 17.8 kB
  • 21 K-Means Clustering/captions/116 K-Means Clustering in R-EN.srt 17.8 kB
  • 17 Decision Tree Classification/captions/101 Decision Tree Classification in Python-EN.srt 17.6 kB
  • 14 Support Vector Machine SVM/captions/086 SVM in Python-EN.srt 17.3 kB
  • 06 Polynomial Regression/captions/055 R Regression Template-EN.srt 17.1 kB
  • 07 Support Vector Regression SVR/captions/057 SVR in R-EN.srt 17.0 kB
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  • 26 ------------------------ Part 6 Reinforcement Learning ------------------------/138 Welcome to Part 6 - Reinforcement Learning.html 1.1 kB
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  • 30 ---------------------------- Part 8 Deep Learning ----------------------------/174 Welcome to Part 8 - Deep Learning.html 1.1 kB
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  • 23 ---------------------- Part 5 Association Rule Learning ----------------------/130 Welcome to Part 5 - Association Rule Learning.html 713 Bytes
  • 02 -------------------------- Part 1 Data Preprocessing --------------------------/attached_files/007 Get the dataset/Data.csv 226 Bytes

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