Machine_Learning_A-Z_Hands-On_Python_and_R_In_Data_Science

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文件大小:6GB
下载次数:40
最近下载:2019-03-21 02:20:57
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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 227MB
39 XGBoost/attached_files/213 Download all the Codes and Datasets Here/Machine-Learning-A-Z.zip 227MB
32 Convolutional Neural Networks/attached_files/190 CNN in Python - Step 1/Convolutional-Neural-Networks.zip 222MB
12 Logistic Regression/080 Logistic Regression in R - Step 5.mp4 94MB
31 Artificial Neural Networks/177 ANN in Python - Step 2.mp4 85MB
17 Decision Tree Classification/102 Decision Tree Classification in R.mp4 68MB
14 Support Vector Machine SVM/087 SVM in R.mp4 65MB
18 Random Forest Classification/105 Random Forest Classification in R.mp4 64MB
32 Convolutional Neural Networks/198 CNN in Python - Step 9.mp4 62MB
18 Random Forest Classification/104 Random Forest Classification in Python.mp4 62MB
07 Support Vector Regression SVR/056 SVR in Python.mp4 60MB
05 Multiple Linear Regression/038 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK.mp4 59MB
27 Upper Confidence Bound UCB/145 Upper Confidence Bound in R - Step 3.mp4 58MB
24 Apriori/133 Apriori in R - Step 3.mp4 57MB
08 Decision Tree Regression/060 Decision Tree Regression in R.mp4 56MB
13 K-Nearest Neighbors K-NN/084 K-NN in R.mp4 56MB
28 Thompson Sampling/147 Thompson Sampling in Python - Step 1.mp4 56MB
15 Kernel SVM/092 Kernel SVM in Python.mp4 55MB
06 Polynomial Regression/053 Polynomial Regression in R - Step 3.mp4 55MB
05 Multiple Linear Regression/037 Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4 55MB
06 Polynomial Regression/048 Polynomial Regression in Python - Step 3.mp4 55MB
05 Multiple Linear Regression/039 Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4 54MB
29 --------------------- Part 7 Natural Language Processing ---------------------/172 Natural Language Processing in R - Step 10.mp4 54MB
27 Upper Confidence Bound UCB/141 Upper Confidence Bound in Python - Step 3.mp4 54MB
12 Logistic Regression/074 Logistic Regression in Python - Step 5.mp4 53MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/012 Categorical Data.mp4 53MB
24 Apriori/131 Apriori in R - Step 1.mp4 53MB
15 Kernel SVM/093 Kernel SVM in R.mp4 53MB
09 Random Forest Regression/062 Random Forest Regression in Python.mp4 53MB
05 Multiple Linear Regression/034 Multiple Linear Regression in Python - Step 1.mp4 52MB
29 --------------------- Part 7 Natural Language Processing ---------------------/159 Natural Language Processing in Python - Step 8.mp4 52MB
09 Random Forest Regression/063 Random Forest Regression in R.mp4 52MB
29 --------------------- Part 7 Natural Language Processing ---------------------/163 Natural Language Processing in R - Step 1.mp4 51MB
28 Thompson Sampling/149 Thompson Sampling in R - Step 1.mp4 51MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/013 Splitting the Dataset into the Training set and Test set.mp4 51MB
05 Multiple Linear Regression/043 Multiple Linear Regression in R - Backward Elimination - HOMEWORK.mp4 51MB
16 Naive Bayes/094 Bayes Theorem.mp4 50MB
31 Artificial Neural Networks/186 ANN in R - Step 1.mp4 50MB
21 K-Means Clustering/115 K-Means Clustering in Python.mp4 50MB
16 Naive Bayes/099 Naive Bayes in R.mp4 50MB
04 Simple Linear Regression/027 Simple Linear Regression in R - Step 4.mp4 49MB
24 Apriori/134 Apriori in Python - Step 1.mp4 47MB
13 K-Nearest Neighbors K-NN/083 K-NN in Python.mp4 47MB
29 --------------------- Part 7 Natural Language Processing ---------------------/152 Natural Language Processing in Python - Step 1.mp4 46MB
35 Linear Discriminant Analysis LDA/205 LDA in Python.mp4 45MB
05 Multiple Linear Regression/041 Multiple Linear Regression in R - Step 2.mp4 45MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/014 Feature Scaling.mp4 45MB
27 Upper Confidence Bound UCB/140 Upper Confidence Bound in Python - Step 2.mp4 44MB
31 Artificial Neural Networks/189 ANN in R - Step 4 Last step.mp4 44MB
08 Decision Tree Regression/059 Decision Tree Regression in Python.mp4 43MB
14 Support Vector Machine SVM/086 SVM in Python.mp4 42MB
04 Simple Linear Regression/023 Simple Linear Regression in Python - Step 4.mp4 39MB
31 Artificial Neural Networks/180 ANN in Python - Step 5.mp4 39MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/011 Missing Data.mp4 39MB
27 Upper Confidence Bound UCB/139 Upper Confidence Bound in Python - Step 1.mp4 39MB
17 Decision Tree Classification/101 Decision Tree Classification in Python.mp4 39MB
24 Apriori/132 Apriori in R - Step 2.mp4 39MB
38 Model Selection/209 Grid Search in Python - Step 1.mp4 38MB
31 Artificial Neural Networks/188 ANN in R - Step 3.mp4 38MB
29 --------------------- Part 7 Natural Language Processing ---------------------/171 Natural Language Processing in R - Step 9.mp4 38MB
31 Artificial Neural Networks/176 ANN in Python - Step 1 - Installing Theano Tensorflow and Keras.mp4 37MB
24 Apriori/135 Apriori in Python - Step 2.mp4 37MB
21 K-Means Clustering/116 K-Means Clustering in R.mp4 37MB
06 Polynomial Regression/050 Python Regression Template.mp4 37MB
24 Apriori/136 Apriori in Python - Step 3.mp4 35MB
06 Polynomial Regression/047 Polynomial Regression in Python - Step 2.mp4 35MB
15 Kernel SVM/090 The Kernel Trick.mp4 35MB
32 Convolutional Neural Networks/193 CNN in Python - Step 4.mp4 35MB
27 Upper Confidence Bound UCB/144 Upper Confidence Bound in R - Step 2.mp4 34MB
31 Artificial Neural Networks/183 ANN in Python - Step 8.mp4 34MB
27 Upper Confidence Bound UCB/143 Upper Confidence Bound in R - Step 1.mp4 34MB
07 Support Vector Regression SVR/057 SVR in R.mp4 34MB
36 Kernel PCA/206 Kernel PCA in Python.mp4 33MB
29 --------------------- Part 7 Natural Language Processing ---------------------/161 Natural Language Processing in Python - Step 10.mp4 33MB
38 Model Selection/208 k-Fold Cross Validation in Python.mp4 33MB
05 Multiple Linear Regression/033 Multiple Linear Regression Intuition - Step 5.mp4 33MB
06 Polynomial Regression/052 Polynomial Regression in R - Step 2.mp4 32MB
39 XGBoost/212 XGBoost in Python - Step 2.mp4 32MB
34 Principal Component Analysis PCA/202 PCA in Python - Step 1.mp4 32MB
06 Polynomial Regression/046 Polynomial Regression in Python - Step 1.mp4 32MB
06 Polynomial Regression/055 R Regression Template.mp4 31MB
16 Naive Bayes/098 Naive Bayes in Python.mp4 31MB
16 Naive Bayes/095 Naive Bayes Intuition.mp4 31MB
32 Convolutional Neural Networks/190 CNN in Python - Step 1.mp4 31MB
21 K-Means Clustering/112 K-Means Clustering Intuition.mp4 30MB
29 --------------------- Part 7 Natural Language Processing ---------------------/155 Natural Language Processing in Python - Step 4.mp4 30MB
38 Model Selection/210 Grid Search in Python - Step 2.mp4 30MB
31 Artificial Neural Networks/175 Business Problem Description.mp4 29MB
12 Logistic Regression/069 Logistic Regression Intuition.mp4 29MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/009 Importing the Dataset.mp4 29MB
06 Polynomial Regression/054 Polynomial Regression in R - Step 4.mp4 29MB
31 Artificial Neural Networks/184 ANN in Python - Step 9.mp4 28MB
31 Artificial Neural Networks/185 ANN in Python - Step 10.mp4 28MB
10 Evaluating Regression Models Performance/066 Evaluating Regression Models Performance - Homeworks Final Part.mp4 28MB
04 Simple Linear Regression/020 Simple Linear Regression in Python - Step 1.mp4 28MB
32 Convolutional Neural Networks/199 CNN in Python - Step 10.mp4 28MB
12 Logistic Regression/078 Logistic Regression in R - Step 3.mp4 27MB
29 --------------------- Part 7 Natural Language Processing ---------------------/153 Natural Language Processing in Python - Step 2.mp4 27MB
10 Evaluating Regression Models Performance/067 Interpreting Linear Regression Coefficients.mp4 27MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/015 And here is our Data Preprocessing Template.mp4 26MB
21 K-Means Clustering/114 K-Means Selecting The Number Of Clusters.mp4 26MB
18 Random Forest Classification/103 Random Forest Classification Intuition.mp4 26MB
34 Principal Component Analysis PCA/204 PCA in Python - Step 3.mp4 26MB
05 Multiple Linear Regression/036 Multiple Linear Regression in Python - Step 3.mp4 25MB
08 Decision Tree Regression/058 Decision Tree Regression Intuition.mp4 25MB
25 Eclat/137 Eclat in R.mp4 25MB
04 Simple Linear Regression/025 Simple Linear Regression in R - Step 2.mp4 25MB
04 Simple Linear Regression/021 Simple Linear Regression in Python - Step 2.mp4 25MB
01 Welcome to the course/004 Installing Python and Anaconda MAC Windows.mp4 24MB
05 Multiple Linear Regression/040 Multiple Linear Regression in R - Step 1.mp4 23MB
01 Welcome to the course/003 Installing R and R Studio MAC Windows.mp4 23MB
22 Hierarchical Clustering/119 Hierarchical Clustering Using Dendrograms.mp4 23MB
29 --------------------- Part 7 Natural Language Processing ---------------------/158 Natural Language Processing in Python - Step 7.mp4 22MB
34 Principal Component Analysis PCA/203 PCA in Python - Step 2.mp4 22MB
05 Multiple Linear Regression/044 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4 22MB
29 --------------------- Part 7 Natural Language Processing ---------------------/164 Natural Language Processing in R - Step 2.mp4 22MB
17 Decision Tree Classification/100 Decision Tree Classification Intuition.mp4 22MB
10 Evaluating Regression Models Performance/065 Adjusted R-Squared Intuition.mp4 21MB
39 XGBoost/211 XGBoost in Python - Step 1.mp4 21MB
22 Hierarchical Clustering/123 HC in Python - Step 4.mp4 21MB
06 Polynomial Regression/051 Polynomial Regression in R - Step 1.mp4 21MB
04 Simple Linear Regression/022 Simple Linear Regression in Python - Step 3.mp4 21MB
19 Evaluating Classification Models Performance/109 CAP Curve.mp4 20MB
14 Support Vector Machine SVM/085 SVM Intuition.mp4 20MB
16 Naive Bayes/097 Naive Bayes Intuition Extras.mp4 19MB
29 --------------------- Part 7 Natural Language Processing ---------------------/160 Natural Language Processing in Python - Step 9.mp4 19MB
29 --------------------- Part 7 Natural Language Processing ---------------------/156 Natural Language Processing in Python - Step 5.mp4 19MB
31 Artificial Neural Networks/187 ANN in R - Step 2.mp4 18MB
06 Polynomial Regression/049 Polynomial Regression in Python - Step 4.mp4 18MB
12 Logistic Regression/075 Python Classification Template.mp4 18MB
12 Logistic Regression/081 R Classification Template.mp4 18MB
22 Hierarchical Clustering/118 Hierarchical Clustering How Dendrograms Work.mp4 17MB
29 --------------------- Part 7 Natural Language Processing ---------------------/170 Natural Language Processing in R - Step 8.mp4 17MB
29 --------------------- Part 7 Natural Language Processing ---------------------/165 Natural Language Processing in R - Step 3.mp4 17MB
12 Logistic Regression/070 Logistic Regression in Python - Step 1.mp4 17MB
32 Convolutional Neural Networks/196 CNN in Python - Step 7.mp4 17MB
05 Multiple Linear Regression/031 Multiple Linear Regression Intuition - Step 3.mp4 17MB
22 Hierarchical Clustering/117 Hierarchical Clustering Intuition.mp4 17MB
22 Hierarchical Clustering/122 HC in Python - Step 3.mp4 16MB
29 --------------------- Part 7 Natural Language Processing ---------------------/168 Natural Language Processing in R - Step 6.mp4 16MB
12 Logistic Regression/076 Logistic Regression in R - Step 1.mp4 16MB
15 Kernel SVM/091 Types of Kernel Functions.mp4 16MB
09 Random Forest Regression/061 Random Forest Regression Intuition.mp4 16MB
22 Hierarchical Clustering/121 HC in Python - Step 2.mp4 16MB
15 Kernel SVM/089 Mapping to a higher dimension.mp4 15MB
21 K-Means Clustering/113 K-Means Random Initialization Trap.mp4 15MB
19 Evaluating Classification Models Performance/106 False Positives False Negatives.mp4 15MB
31 Artificial Neural Networks/182 ANN in Python - Step 7.mp4 15MB
12 Logistic Regression/077 Logistic Regression in R - Step 2.mp4 15MB
31 Artificial Neural Networks/178 ANN in Python - Step 3.mp4 15MB
01 Welcome to the course/002 Why Machine Learning is the Future.mp4 14MB
12 Logistic Regression/073 Logistic Regression in Python - Step 4.mp4 14MB
22 Hierarchical Clustering/126 HC in R - Step 2.mp4 14MB
05 Multiple Linear Regression/042 Multiple Linear Regression in R - Step 3.mp4 14MB
22 Hierarchical Clustering/120 HC in Python - Step 1.mp4 14MB
22 Hierarchical Clustering/129 HC in R - Step 5.mp4 14MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/008 Importing the Libraries.mp4 14MB
16 Naive Bayes/096 Naive Bayes Intuition Challenge Reveal.mp4 13MB
19 Evaluating Classification Models Performance/110 CAP Curve Analysis.mp4 13MB
05 Multiple Linear Regression/028 Dataset Business Problem Description.mp4 13MB
27 Upper Confidence Bound UCB/142 Upper Confidence Bound in Python - Step 4.mp4 12MB
32 Convolutional Neural Networks/194 CNN in Python - Step 5.mp4 12MB
32 Convolutional Neural Networks/195 CNN in Python - Step 6.mp4 12MB
31 Artificial Neural Networks/181 ANN in Python - Step 6.mp4 12MB
12 Logistic Regression/079 Logistic Regression in R - Step 4.mp4 12MB
04 Simple Linear Regression/024 Simple Linear Regression in R - Step 1.mp4 12MB
04 Simple Linear Regression/026 Simple Linear Regression in R - Step 3.mp4 11MB
28 Thompson Sampling/148 Thompson Sampling in Python - Step 2.mp4 11MB
12 Logistic Regression/071 Logistic Regression in Python - Step 2.mp4 11MB
04 Simple Linear Regression/018 Simple Linear Regression Intuition - Step 1.mp4 11MB
13 K-Nearest Neighbors K-NN/082 K-Nearest Neighbor Intuition.mp4 10MB
22 Hierarchical Clustering/128 HC in R - Step 4.mp4 10MB
22 Hierarchical Clustering/127 HC in R - Step 3.mp4 10MB
22 Hierarchical Clustering/124 HC in Python - Step 5.mp4 10MB
05 Multiple Linear Regression/035 Multiple Linear Regression in Python - Step 2.mp4 10MB
01 Welcome to the course/001 Applications of Machine Learning.mp4 10MB
10 Evaluating Regression Models Performance/064 R-Squared Intuition.mp4 10MB
31 Artificial Neural Networks/179 ANN in Python - Step 4.mp4 10MB
29 --------------------- Part 7 Natural Language Processing ---------------------/169 Natural Language Processing in R - Step 7.mp4 10MB
28 Thompson Sampling/150 Thompson Sampling in R - Step 2.mp4 10MB
27 Upper Confidence Bound UCB/146 Upper Confidence Bound in R - Step 4.mp4 10MB
06 Polynomial Regression/045 Polynomial Regression Intuition.mp4 9MB
32 Convolutional Neural Networks/197 CNN in Python - Step 8.mp4 9MB
19 Evaluating Classification Models Performance/107 Confusion Matrix.mp4 9MB
22 Hierarchical Clustering/125 HC in R - Step 1.mp4 9MB
29 --------------------- Part 7 Natural Language Processing ---------------------/157 Natural Language Processing in Python - Step 6.mp4 8MB
29 --------------------- Part 7 Natural Language Processing ---------------------/166 Natural Language Processing in R - Step 4.mp4 8MB
12 Logistic Regression/072 Logistic Regression in Python - Step 3.mp4 8MB
04 Simple Linear Regression/017 Dataset Business Problem Description.mp4 8MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/007 Get the dataset.mp4 7MB
32 Convolutional Neural Networks/191 CNN in Python - Step 2.mp4 7MB
15 Kernel SVM/088 Kernel SVM Intuition.mp4 6MB
04 Simple Linear Regression/019 Simple Linear Regression Intuition - Step 2.mp4 6MB
29 --------------------- Part 7 Natural Language Processing ---------------------/167 Natural Language Processing in R - Step 5.mp4 6MB
05 Multiple Linear Regression/032 Multiple Linear Regression Intuition - Step 4.mp4 5MB
19 Evaluating Classification Models Performance/108 Accuracy Paradox.mp4 4MB
29 --------------------- Part 7 Natural Language Processing ---------------------/154 Natural Language Processing in Python - Step 3.mp4 4MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/006 Welcome to Part 1 - Data Preprocessing.mp4 4MB
32 Convolutional Neural Networks/192 CNN in Python - Step 3.mp4 3MB
05 Multiple Linear Regression/030 Multiple Linear Regression Intuition - Step 2.mp4 2MB
05 Multiple Linear Regression/029 Multiple Linear Regression Intuition - Step 1.mp4 2MB
31 Artificial Neural Networks/attached_files/176 ANN in Python - Step 1 - Installing Theano Tensorflow and Keras/Artificial-Neural-Networks.zip 1MB
31 Artificial Neural Networks/attached_files/186 ANN in R - Step 1/Artificial-Neural-Networks.zip 1MB
27 Upper Confidence Bound UCB/attached_files/139 Upper Confidence Bound in Python - Step 1/UCB.zip 1MB
27 Upper Confidence Bound UCB/attached_files/143 Upper Confidence Bound in R - Step 1/UCB.zip 1MB
28 Thompson Sampling/attached_files/147 Thompson Sampling in Python - Step 1/Thompson-Sampling.zip 1009KB
28 Thompson Sampling/attached_files/149 Thompson Sampling in R - Step 1/Thompson-Sampling.zip 1009KB
05 Multiple Linear Regression/attached_files/033 Multiple Linear Regression Intuition - Step 5/Step-by-step-Blueprints-For-Building-Models.pdf 769KB
39 XGBoost/attached_files/211 XGBoost in Python - Step 1/XGBoost.zip 259KB
24 Apriori/attached_files/134 Apriori in Python - Step 1/Apriori-Python.zip 53KB
24 Apriori/attached_files/131 Apriori in R - Step 1/Apriori.zip 49KB
25 Eclat/attached_files/137 Eclat in R/Eclat.zip 49KB
16 Naive Bayes/captions/094 Bayes Theorem-EN.srt 31KB
18 Random Forest Classification/captions/105 Random Forest Classification in R-EN.srt 29KB
08 Decision Tree Regression/captions/060 Decision Tree Regression in R-EN.srt 29KB
29 --------------------- Part 7 Natural Language Processing ---------------------/attached_files/152 Natural Language Processing in Python - Step 1/Natural-Language-Processing.zip 28KB
29 --------------------- Part 7 Natural Language Processing ---------------------/attached_files/163 Natural Language Processing in R - Step 1/Natural-Language-Processing.zip 28KB
06 Polynomial Regression/captions/048 Polynomial Regression in Python - Step 3-EN.srt 28KB
24 Apriori/captions/133 Apriori in R - Step 3-EN.srt 28KB
24 Apriori/captions/131 Apriori in R - Step 1-EN.srt 28KB
07 Support Vector Regression SVR/captions/056 SVR in Python-EN.srt 27KB
06 Polynomial Regression/captions/053 Polynomial Regression in R - Step 3-EN.srt 27KB
18 Random Forest Classification/captions/104 Random Forest Classification in Python-EN.srt 27KB
12 Logistic Regression/captions/074 Logistic Regression in Python - Step 5-EN.srt 26KB
12 Logistic Regression/captions/080 Logistic Regression in R - Step 5-EN.srt 26KB
17 Decision Tree Classification/captions/102 Decision Tree Classification in R-EN.srt 26KB
21 K-Means Clustering/captions/115 K-Means Clustering in Python-EN.srt 25KB
09 Random Forest Regression/captions/063 Random Forest Regression in R-EN.srt 25KB
15 Kernel SVM/captions/092 Kernel SVM in Python-EN.srt 25KB
24 Apriori/captions/134 Apriori in Python - Step 1-EN.srt 25KB
05 Multiple Linear Regression/captions/043 Multiple Linear Regression in R - Backward Elimination - HOMEWORK-EN.srt 25KB
09 Random Forest Regression/captions/062 Random Forest Regression in Python-EN.srt 24KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/013 Splitting the Dataset into the Training set and Test set-EN.srt 24KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/012 Categorical Data-EN.srt 24KB
15 Kernel SVM/captions/093 Kernel SVM in R-EN.srt 23KB
05 Multiple Linear Regression/captions/034 Multiple Linear Regression in Python - Step 1-EN.srt 22KB
04 Simple Linear Regression/captions/027 Simple Linear Regression in R - Step 4-EN.srt 21KB
08 Decision Tree Regression/captions/059 Decision Tree Regression in Python-EN.srt 21KB
05 Multiple Linear Regression/captions/033 Multiple Linear Regression Intuition - Step 5-EN.srt 21KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/011 Missing Data-EN.srt 21KB
21 K-Means Clustering/captions/112 K-Means Clustering Intuition-EN.srt 21KB
16 Naive Bayes/captions/095 Naive Bayes Intuition-EN.srt 21KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/014 Feature Scaling-EN.srt 21KB
13 K-Nearest Neighbors K-NN/captions/084 K-NN in R-EN.srt 21KB
24 Apriori/captions/132 Apriori in R - Step 2-EN.srt 21KB
24 Apriori/captions/135 Apriori in Python - Step 2-EN.srt 20KB
04 Simple Linear Regression/captions/023 Simple Linear Regression in Python - Step 4-EN.srt 20KB
16 Naive Bayes/captions/099 Naive Bayes in R-EN.srt 19KB
13 K-Nearest Neighbors K-NN/captions/083 K-NN in Python-EN.srt 19KB
05 Multiple Linear Regression/captions/037 Multiple Linear Regression in Python - Backward Elimination - Preparation-EN.srt 18KB
05 Multiple Linear Regression/captions/038 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK-EN.srt 18KB
24 Apriori/captions/136 Apriori in Python - Step 3-EN.srt 17KB
21 K-Means Clustering/captions/116 K-Means Clustering in R-EN.srt 17KB
17 Decision Tree Classification/captions/101 Decision Tree Classification in Python-EN.srt 17KB
14 Support Vector Machine SVM/captions/086 SVM in Python-EN.srt 17KB
06 Polynomial Regression/captions/055 R Regression Template-EN.srt 17KB
07 Support Vector Regression SVR/captions/057 SVR in R-EN.srt 17KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/009 Importing the Dataset-EN.srt 17KB
21 K-Means Clustering/captions/114 K-Means Selecting The Number Of Clusters-EN.srt 17KB
14 Support Vector Machine SVM/captions/087 SVM in R-EN.srt 16KB
22 Hierarchical Clustering/captions/119 Hierarchical Clustering Using Dendrograms-EN.srt 16KB
06 Polynomial Regression/captions/046 Polynomial Regression in Python - Step 1-EN.srt 16KB
06 Polynomial Regression/captions/047 Polynomial Regression in Python - Step 2-EN.srt 15KB
08 Decision Tree Regression/captions/058 Decision Tree Regression Intuition-EN.srt 15KB
06 Polynomial Regression/captions/050 Python Regression Template-EN.srt 15KB
19 Evaluating Classification Models Performance/captions/109 CAP Curve-EN.srt 15KB
16 Naive Bayes/captions/097 Naive Bayes Intuition Extras-EN.srt 14KB
14 Support Vector Machine SVM/captions/085 SVM Intuition-EN.srt 14KB
25 Eclat/captions/137 Eclat in R-EN.srt 14KB
04 Simple Linear Regression/captions/020 Simple Linear Regression in Python - Step 1-EN.srt 14KB
05 Multiple Linear Regression/captions/041 Multiple Linear Regression in R - Step 2-EN.srt 14KB
06 Polynomial Regression/captions/054 Polynomial Regression in R - Step 4-EN.srt 14KB
06 Polynomial Regression/captions/052 Polynomial Regression in R - Step 2-EN.srt 14KB
22 Hierarchical Clustering/captions/117 Hierarchical Clustering Intuition-EN.srt 13KB
10 Evaluating Regression Models Performance/captions/065 Adjusted R-Squared Intuition-EN.srt 13KB
22 Hierarchical Clustering/captions/118 Hierarchical Clustering How Dendrograms Work-EN.srt 13KB
05 Multiple Linear Regression/captions/039 Multiple Linear Regression in Python - Backward Elimination - Homework Solution-EN.srt 13KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/015 And here is our Data Preprocessing Template-EN.srt 13KB
06 Polynomial Regression/captions/051 Polynomial Regression in R - Step 1-EN.srt 13KB
16 Naive Bayes/captions/098 Naive Bayes in Python-EN.srt 12KB
10 Evaluating Regression Models Performance/captions/067 Interpreting Linear Regression Coefficients-EN.srt 12KB
21 K-Means Clustering/captions/113 K-Means Random Initialization Trap-EN.srt 12KB
10 Evaluating Regression Models Performance/captions/066 Evaluating Regression Models Performance - Homeworks Final Part-EN.srt 12KB
17 Decision Tree Classification/captions/100 Decision Tree Classification Intuition-EN.srt 12KB
04 Simple Linear Regression/captions/021 Simple Linear Regression in Python - Step 2-EN.srt 11KB
01 Welcome to the course/captions/004 Installing Python and Anaconda MAC Windows-EN.srt 11KB
05 Multiple Linear Regression/captions/044 Multiple Linear Regression in R - Backward Elimination - Homework Solution-EN.srt 11KB
05 Multiple Linear Regression/captions/040 Multiple Linear Regression in R - Step 1-EN.srt 10KB
19 Evaluating Classification Models Performance/captions/106 False Positives False Negatives-EN.srt 10KB
05 Multiple Linear Regression/captions/031 Multiple Linear Regression Intuition - Step 3-EN.srt 10KB
09 Random Forest Regression/captions/061 Random Forest Regression Intuition-EN.srt 9KB
04 Simple Linear Regression/captions/022 Simple Linear Regression in Python - Step 3-EN.srt 9KB
18 Random Forest Classification/attached_files/104 Random Forest Classification in Python/Random-Forest-Classification.zip 9KB
18 Random Forest Classification/attached_files/105 Random Forest Classification in R/Random-Forest-Classification.zip 9KB
17 Decision Tree Classification/attached_files/101 Decision Tree Classification in Python/Decision-Tree-Classification.zip 9KB
17 Decision Tree Classification/attached_files/102 Decision Tree Classification in R/Decision-Tree-Classification.zip 9KB
22 Hierarchical Clustering/captions/121 HC in Python - Step 2-EN.srt 9KB
16 Naive Bayes/captions/096 Naive Bayes Intuition Challenge Reveal-EN.srt 9KB
13 K-Nearest Neighbors K-NN/attached_files/083 K-NN in Python/K-Nearest-Neighbors.zip 9KB
13 K-Nearest Neighbors K-NN/attached_files/084 K-NN in R/K-Nearest-Neighbors.zip 9KB
15 Kernel SVM/attached_files/092 Kernel SVM in Python/Kernel-SVM.zip 8KB
15 Kernel SVM/attached_files/093 Kernel SVM in R/Kernel-SVM.zip 8KB
16 Naive Bayes/attached_files/098 Naive Bayes in Python/Naive-Bayes.zip 8KB
16 Naive Bayes/attached_files/099 Naive Bayes in R/Naive-Bayes.zip 8KB
19 Evaluating Classification Models Performance/captions/110 CAP Curve Analysis-EN.srt 8KB
14 Support Vector Machine SVM/attached_files/086 SVM in Python/SVM.zip 8KB
14 Support Vector Machine SVM/attached_files/087 SVM in R/SVM.zip 8KB
01 Welcome to the course/captions/003 Installing R and R Studio MAC Windows-EN.srt 8KB
04 Simple Linear Regression/captions/025 Simple Linear Regression in R - Step 2-EN.srt 8KB
12 Logistic Regression/captions/076 Logistic Regression in R - Step 1-EN.srt 8KB
06 Polynomial Regression/captions/049 Polynomial Regression in Python - Step 4-EN.srt 8KB
12 Logistic Regression/captions/070 Logistic Regression in Python - Step 1-EN.srt 8KB
38 Model Selection/attached_files/208 k-Fold Cross Validation in Python/Model-Selection.zip 8KB
38 Model Selection/attached_files/209 Grid Search in Python - Step 1/Model-Selection.zip 8KB
04 Simple Linear Regression/captions/018 Simple Linear Regression Intuition - Step 1-EN.srt 7KB
05 Multiple Linear Regression/captions/036 Multiple Linear Regression in Python - Step 3-EN.srt 7KB
22 Hierarchical Clustering/captions/126 HC in R - Step 2-EN.srt 7KB
13 K-Nearest Neighbors K-NN/captions/082 K-Nearest Neighbor Intuition-EN.srt 7KB
06 Polynomial Regression/captions/045 Polynomial Regression Intuition-EN.srt 7KB
22 Hierarchical Clustering/captions/122 HC in Python - Step 3-EN.srt 7KB
34 Principal Component Analysis PCA/attached_files/202 PCA in Python - Step 1/PCA.zip 7KB
04 Simple Linear Regression/captions/024 Simple Linear Regression in R - Step 1-EN.srt 7KB
22 Hierarchical Clustering/captions/120 HC in Python - Step 1-EN.srt 7KB
19 Evaluating Classification Models Performance/captions/107 Confusion Matrix-EN.srt 7KB
12 Logistic Regression/captions/078 Logistic Regression in R - Step 3-EN.srt 7KB
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08 Decision Tree Regression/attached_files/059 Decision Tree Regression in Python/Decision-Tree-Regression.zip 5KB
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07 Support Vector Regression SVR/attached_files/057 SVR in R/SVR.zip 5KB
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02 -------------------------- Part 1 Data Preprocessing --------------------------/quizzes/001 Data Preprocessing.html 5KB
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32 Convolutional Neural Networks/200 CNN in R.html 3KB
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02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/006 Welcome to Part 1 - Data Preprocessing-EN.srt 2KB
29 --------------------- Part 7 Natural Language Processing ---------------------/151 Welcome to Part 7 - Natural Language Processing.html 2KB
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02 -------------------------- Part 1 Data Preprocessing --------------------------/010 For Python learners summary of Object-oriented programming classes objects.html 2KB
29 --------------------- Part 7 Natural Language Processing ---------------------/173 Homework Challenge.html 2KB
29 --------------------- Part 7 Natural Language Processing ---------------------/162 Homework Challenge.html 2KB
33 ----------------------- Part 9 Dimensionality Reduction -----------------------/201 Welcome to Part 9 - Dimensionality Reduction.html 2KB
05 Multiple Linear Regression/captions/029 Multiple Linear Regression Intuition - Step 1-EN.srt 1KB
01 Welcome to the course/005 BONUS Meet your instructors.html 1KB
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37 --------------------- Part 10 Model Selection Boosting ---------------------/207 Welcome to Part 10 - Model Selection Boosting.html 1KB
03 ------------------------------ Part 2 Regression ------------------------------/016 Welcome to Part 2 - Regression.html 1KB
26 ------------------------ Part 6 Reinforcement Learning ------------------------/138 Welcome to Part 6 - Reinforcement Learning.html 1KB
11 ---------------------------- Part 3 Classification ----------------------------/068 Welcome to Part 3 - Classification.html 1KB
30 ---------------------------- Part 8 Deep Learning ----------------------------/174 Welcome to Part 8 - Deep Learning.html 1KB
20 ---------------------------- Part 4 Clustering ----------------------------/111 Welcome to Part 4 - Clustering.html 1004B
39 XGBoost/213 Download all the Codes and Datasets Here.html 888B
23 ---------------------- Part 5 Association Rule Learning ----------------------/130 Welcome to Part 5 - Association Rule Learning.html 713B
02 -------------------------- Part 1 Data Preprocessing --------------------------/attached_files/007 Get the dataset/Data.csv 226B