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

Creation Time	July 6, 2024, 8:03 p.m.
Last Access Time	March 26, 2025, 12:25 a.m.
File Size	6.2 GB
Keywords	and On Python Science In - Machine A-Z Learning Hands R Data
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02 -------------------------- Part 1 Data Preprocessing --------------------------/attached_files/006 Welcome to Part 1 - Data Preprocessing/Machine-Learning-A-Z-Template-Folder.zip 227.4 MB
39 XGBoost/attached_files/213 Download all the Codes and Datasets Here/Machine-Learning-A-Z.zip 227.1 MB
32 Convolutional Neural Networks/attached_files/190 CNN in Python - Step 1/Convolutional-Neural-Networks.zip 221.8 MB
12 Logistic Regression/080 Logistic Regression in R - Step 5.mp4 93.8 MB
31 Artificial Neural Networks/177 ANN in Python - Step 2.mp4 84.9 MB
17 Decision Tree Classification/102 Decision Tree Classification in R.mp4 68.2 MB
14 Support Vector Machine SVM/087 SVM in R.mp4 65.3 MB
18 Random Forest Classification/105 Random Forest Classification in R.mp4 64.1 MB
32 Convolutional Neural Networks/198 CNN in Python - Step 9.mp4 62.4 MB
18 Random Forest Classification/104 Random Forest Classification in Python.mp4 62.0 MB
07 Support Vector Regression SVR/056 SVR in Python.mp4 60.2 MB
05 Multiple Linear Regression/038 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK.mp4 59.1 MB
27 Upper Confidence Bound UCB/145 Upper Confidence Bound in R - Step 3.mp4 57.8 MB
24 Apriori/133 Apriori in R - Step 3.mp4 56.5 MB
08 Decision Tree Regression/060 Decision Tree Regression in R.mp4 56.2 MB
13 K-Nearest Neighbors K-NN/084 K-NN in R.mp4 55.8 MB
28 Thompson Sampling/147 Thompson Sampling in Python - Step 1.mp4 55.5 MB
15 Kernel SVM/092 Kernel SVM in Python.mp4 54.9 MB
06 Polynomial Regression/053 Polynomial Regression in R - Step 3.mp4 54.8 MB
05 Multiple Linear Regression/037 Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4 54.5 MB
06 Polynomial Regression/048 Polynomial Regression in Python - Step 3.mp4 54.5 MB
05 Multiple Linear Regression/039 Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4 54.3 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/172 Natural Language Processing in R - Step 10.mp4 54.1 MB
27 Upper Confidence Bound UCB/141 Upper Confidence Bound in Python - Step 3.mp4 53.7 MB
12 Logistic Regression/074 Logistic Regression in Python - Step 5.mp4 53.1 MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/012 Categorical Data.mp4 52.9 MB
24 Apriori/131 Apriori in R - Step 1.mp4 52.8 MB
15 Kernel SVM/093 Kernel SVM in R.mp4 52.8 MB
09 Random Forest Regression/062 Random Forest Regression in Python.mp4 52.7 MB
05 Multiple Linear Regression/034 Multiple Linear Regression in Python - Step 1.mp4 52.2 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/159 Natural Language Processing in Python - Step 8.mp4 52.0 MB
09 Random Forest Regression/063 Random Forest Regression in R.mp4 51.9 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/163 Natural Language Processing in R - Step 1.mp4 51.2 MB
28 Thompson Sampling/149 Thompson Sampling in R - Step 1.mp4 51.0 MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/013 Splitting the Dataset into the Training set and Test set.mp4 50.9 MB
05 Multiple Linear Regression/043 Multiple Linear Regression in R - Backward Elimination - HOMEWORK.mp4 50.8 MB
16 Naive Bayes/094 Bayes Theorem.mp4 50.4 MB
31 Artificial Neural Networks/186 ANN in R - Step 1.mp4 49.9 MB
21 K-Means Clustering/115 K-Means Clustering in Python.mp4 49.8 MB
16 Naive Bayes/099 Naive Bayes in R.mp4 49.8 MB
04 Simple Linear Regression/027 Simple Linear Regression in R - Step 4.mp4 49.2 MB
24 Apriori/134 Apriori in Python - Step 1.mp4 47.4 MB
13 K-Nearest Neighbors K-NN/083 K-NN in Python.mp4 47.0 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/152 Natural Language Processing in Python - Step 1.mp4 46.1 MB
35 Linear Discriminant Analysis LDA/205 LDA in Python.mp4 45.4 MB
05 Multiple Linear Regression/041 Multiple Linear Regression in R - Step 2.mp4 45.2 MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/014 Feature Scaling.mp4 44.6 MB
27 Upper Confidence Bound UCB/140 Upper Confidence Bound in Python - Step 2.mp4 44.5 MB
31 Artificial Neural Networks/189 ANN in R - Step 4 Last step.mp4 43.7 MB
08 Decision Tree Regression/059 Decision Tree Regression in Python.mp4 43.4 MB
14 Support Vector Machine SVM/086 SVM in Python.mp4 41.7 MB
04 Simple Linear Regression/023 Simple Linear Regression in Python - Step 4.mp4 39.4 MB
31 Artificial Neural Networks/180 ANN in Python - Step 5.mp4 39.4 MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/011 Missing Data.mp4 39.3 MB
27 Upper Confidence Bound UCB/139 Upper Confidence Bound in Python - Step 1.mp4 39.0 MB
17 Decision Tree Classification/101 Decision Tree Classification in Python.mp4 38.8 MB
24 Apriori/132 Apriori in R - Step 2.mp4 38.8 MB
38 Model Selection/209 Grid Search in Python - Step 1.mp4 38.2 MB
31 Artificial Neural Networks/188 ANN in R - Step 3.mp4 37.9 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/171 Natural Language Processing in R - Step 9.mp4 37.7 MB
31 Artificial Neural Networks/176 ANN in Python - Step 1 - Installing Theano Tensorflow and Keras.mp4 37.5 MB
24 Apriori/135 Apriori in Python - Step 2.mp4 37.3 MB
21 K-Means Clustering/116 K-Means Clustering in R.mp4 36.9 MB
06 Polynomial Regression/050 Python Regression Template.mp4 36.8 MB
24 Apriori/136 Apriori in Python - Step 3.mp4 35.3 MB
06 Polynomial Regression/047 Polynomial Regression in Python - Step 2.mp4 35.1 MB
15 Kernel SVM/090 The Kernel Trick.mp4 34.7 MB
32 Convolutional Neural Networks/193 CNN in Python - Step 4.mp4 34.6 MB
27 Upper Confidence Bound UCB/144 Upper Confidence Bound in R - Step 2.mp4 34.1 MB
31 Artificial Neural Networks/183 ANN in Python - Step 8.mp4 34.0 MB
27 Upper Confidence Bound UCB/143 Upper Confidence Bound in R - Step 1.mp4 34.0 MB
07 Support Vector Regression SVR/057 SVR in R.mp4 33.7 MB
36 Kernel PCA/206 Kernel PCA in Python.mp4 33.4 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/161 Natural Language Processing in Python - Step 10.mp4 32.9 MB
38 Model Selection/208 k-Fold Cross Validation in Python.mp4 32.8 MB
05 Multiple Linear Regression/033 Multiple Linear Regression Intuition - Step 5.mp4 32.8 MB
06 Polynomial Regression/052 Polynomial Regression in R - Step 2.mp4 32.3 MB
39 XGBoost/212 XGBoost in Python - Step 2.mp4 32.0 MB
34 Principal Component Analysis PCA/202 PCA in Python - Step 1.mp4 31.9 MB
06 Polynomial Regression/046 Polynomial Regression in Python - Step 1.mp4 31.6 MB
06 Polynomial Regression/055 R Regression Template.mp4 31.3 MB
16 Naive Bayes/098 Naive Bayes in Python.mp4 31.1 MB
16 Naive Bayes/095 Naive Bayes Intuition.mp4 31.1 MB
32 Convolutional Neural Networks/190 CNN in Python - Step 1.mp4 30.6 MB
21 K-Means Clustering/112 K-Means Clustering Intuition.mp4 30.0 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/155 Natural Language Processing in Python - Step 4.mp4 29.8 MB
38 Model Selection/210 Grid Search in Python - Step 2.mp4 29.5 MB
31 Artificial Neural Networks/175 Business Problem Description.mp4 29.2 MB
12 Logistic Regression/069 Logistic Regression Intuition.mp4 29.2 MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/009 Importing the Dataset.mp4 28.6 MB
06 Polynomial Regression/054 Polynomial Regression in R - Step 4.mp4 28.5 MB
31 Artificial Neural Networks/184 ANN in Python - Step 9.mp4 28.5 MB
31 Artificial Neural Networks/185 ANN in Python - Step 10.mp4 28.4 MB
10 Evaluating Regression Models Performance/066 Evaluating Regression Models Performance - Homeworks Final Part.mp4 28.3 MB
04 Simple Linear Regression/020 Simple Linear Regression in Python - Step 1.mp4 27.9 MB
32 Convolutional Neural Networks/199 CNN in Python - Step 10.mp4 27.7 MB
12 Logistic Regression/078 Logistic Regression in R - Step 3.mp4 27.4 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/153 Natural Language Processing in Python - Step 2.mp4 27.4 MB
10 Evaluating Regression Models Performance/067 Interpreting Linear Regression Coefficients.mp4 27.4 MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/015 And here is our Data Preprocessing Template.mp4 25.9 MB
21 K-Means Clustering/114 K-Means Selecting The Number Of Clusters.mp4 25.7 MB
18 Random Forest Classification/103 Random Forest Classification Intuition.mp4 25.7 MB
34 Principal Component Analysis PCA/204 PCA in Python - Step 3.mp4 25.5 MB
05 Multiple Linear Regression/036 Multiple Linear Regression in Python - Step 3.mp4 25.5 MB
08 Decision Tree Regression/058 Decision Tree Regression Intuition.mp4 25.3 MB
25 Eclat/137 Eclat in R.mp4 25.3 MB
04 Simple Linear Regression/025 Simple Linear Regression in R - Step 2.mp4 24.9 MB
04 Simple Linear Regression/021 Simple Linear Regression in Python - Step 2.mp4 24.6 MB
01 Welcome to the course/004 Installing Python and Anaconda MAC Windows.mp4 24.0 MB
05 Multiple Linear Regression/040 Multiple Linear Regression in R - Step 1.mp4 23.4 MB
01 Welcome to the course/003 Installing R and R Studio MAC Windows.mp4 23.2 MB
22 Hierarchical Clustering/119 Hierarchical Clustering Using Dendrograms.mp4 22.8 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/158 Natural Language Processing in Python - Step 7.mp4 22.1 MB
34 Principal Component Analysis PCA/203 PCA in Python - Step 2.mp4 22.1 MB
05 Multiple Linear Regression/044 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4 22.0 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/164 Natural Language Processing in R - Step 2.mp4 21.7 MB
17 Decision Tree Classification/100 Decision Tree Classification Intuition.mp4 21.6 MB
10 Evaluating Regression Models Performance/065 Adjusted R-Squared Intuition.mp4 21.4 MB
39 XGBoost/211 XGBoost in Python - Step 1.mp4 21.4 MB
22 Hierarchical Clustering/123 HC in Python - Step 4.mp4 21.3 MB
06 Polynomial Regression/051 Polynomial Regression in R - Step 1.mp4 21.2 MB
04 Simple Linear Regression/022 Simple Linear Regression in Python - Step 3.mp4 20.5 MB
19 Evaluating Classification Models Performance/109 CAP Curve.mp4 20.3 MB
14 Support Vector Machine SVM/085 SVM Intuition.mp4 19.9 MB
16 Naive Bayes/097 Naive Bayes Intuition Extras.mp4 18.9 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/160 Natural Language Processing in Python - Step 9.mp4 18.9 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/156 Natural Language Processing in Python - Step 5.mp4 18.8 MB
31 Artificial Neural Networks/187 ANN in R - Step 2.mp4 18.2 MB
06 Polynomial Regression/049 Polynomial Regression in Python - Step 4.mp4 17.6 MB
12 Logistic Regression/075 Python Classification Template.mp4 17.6 MB
12 Logistic Regression/081 R Classification Template.mp4 17.5 MB
22 Hierarchical Clustering/118 Hierarchical Clustering How Dendrograms Work.mp4 17.5 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/170 Natural Language Processing in R - Step 8.mp4 17.2 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/165 Natural Language Processing in R - Step 3.mp4 16.9 MB
12 Logistic Regression/070 Logistic Regression in Python - Step 1.mp4 16.8 MB
32 Convolutional Neural Networks/196 CNN in Python - Step 7.mp4 16.6 MB
05 Multiple Linear Regression/031 Multiple Linear Regression Intuition - Step 3.mp4 16.6 MB
22 Hierarchical Clustering/117 Hierarchical Clustering Intuition.mp4 16.5 MB
22 Hierarchical Clustering/122 HC in Python - Step 3.mp4 16.2 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/168 Natural Language Processing in R - Step 6.mp4 16.1 MB
12 Logistic Regression/076 Logistic Regression in R - Step 1.mp4 15.7 MB
15 Kernel SVM/091 Types of Kernel Functions.mp4 15.7 MB
09 Random Forest Regression/061 Random Forest Regression Intuition.mp4 15.7 MB
22 Hierarchical Clustering/121 HC in Python - Step 2.mp4 15.5 MB
15 Kernel SVM/089 Mapping to a higher dimension.mp4 15.4 MB
21 K-Means Clustering/113 K-Means Random Initialization Trap.mp4 15.4 MB
19 Evaluating Classification Models Performance/106 False Positives False Negatives.mp4 15.1 MB
31 Artificial Neural Networks/182 ANN in Python - Step 7.mp4 14.9 MB
12 Logistic Regression/077 Logistic Regression in R - Step 2.mp4 14.9 MB
31 Artificial Neural Networks/178 ANN in Python - Step 3.mp4 14.6 MB
01 Welcome to the course/002 Why Machine Learning is the Future.mp4 14.5 MB
12 Logistic Regression/073 Logistic Regression in Python - Step 4.mp4 13.9 MB
22 Hierarchical Clustering/126 HC in R - Step 2.mp4 13.9 MB
05 Multiple Linear Regression/042 Multiple Linear Regression in R - Step 3.mp4 13.9 MB
22 Hierarchical Clustering/120 HC in Python - Step 1.mp4 13.8 MB
22 Hierarchical Clustering/129 HC in R - Step 5.mp4 13.7 MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/008 Importing the Libraries.mp4 13.6 MB
16 Naive Bayes/096 Naive Bayes Intuition Challenge Reveal.mp4 13.3 MB
19 Evaluating Classification Models Performance/110 CAP Curve Analysis.mp4 12.9 MB
05 Multiple Linear Regression/028 Dataset Business Problem Description.mp4 12.6 MB
27 Upper Confidence Bound UCB/142 Upper Confidence Bound in Python - Step 4.mp4 12.4 MB
32 Convolutional Neural Networks/194 CNN in Python - Step 5.mp4 12.4 MB
32 Convolutional Neural Networks/195 CNN in Python - Step 6.mp4 11.9 MB
31 Artificial Neural Networks/181 ANN in Python - Step 6.mp4 11.9 MB
12 Logistic Regression/079 Logistic Regression in R - Step 4.mp4 11.7 MB
04 Simple Linear Regression/024 Simple Linear Regression in R - Step 1.mp4 11.5 MB
04 Simple Linear Regression/026 Simple Linear Regression in R - Step 3.mp4 11.4 MB
28 Thompson Sampling/148 Thompson Sampling in Python - Step 2.mp4 11.2 MB
12 Logistic Regression/071 Logistic Regression in Python - Step 2.mp4 11.1 MB
04 Simple Linear Regression/018 Simple Linear Regression Intuition - Step 1.mp4 10.5 MB
13 K-Nearest Neighbors K-NN/082 K-Nearest Neighbor Intuition.mp4 10.5 MB
22 Hierarchical Clustering/128 HC in R - Step 4.mp4 10.2 MB
22 Hierarchical Clustering/127 HC in R - Step 3.mp4 9.9 MB
22 Hierarchical Clustering/124 HC in Python - Step 5.mp4 9.9 MB
05 Multiple Linear Regression/035 Multiple Linear Regression in Python - Step 2.mp4 9.8 MB
01 Welcome to the course/001 Applications of Machine Learning.mp4 9.8 MB
10 Evaluating Regression Models Performance/064 R-Squared Intuition.mp4 9.8 MB
31 Artificial Neural Networks/179 ANN in Python - Step 4.mp4 9.7 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/169 Natural Language Processing in R - Step 7.mp4 9.6 MB
28 Thompson Sampling/150 Thompson Sampling in R - Step 2.mp4 9.6 MB
27 Upper Confidence Bound UCB/146 Upper Confidence Bound in R - Step 4.mp4 9.5 MB
06 Polynomial Regression/045 Polynomial Regression Intuition.mp4 9.4 MB
32 Convolutional Neural Networks/197 CNN in Python - Step 8.mp4 8.9 MB
19 Evaluating Classification Models Performance/107 Confusion Matrix.mp4 8.9 MB
22 Hierarchical Clustering/125 HC in R - Step 1.mp4 8.6 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/157 Natural Language Processing in Python - Step 6.mp4 8.3 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/166 Natural Language Processing in R - Step 4.mp4 8.2 MB
12 Logistic Regression/072 Logistic Regression in Python - Step 3.mp4 8.0 MB
04 Simple Linear Regression/017 Dataset Business Problem Description.mp4 7.8 MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/007 Get the dataset.mp4 7.2 MB
32 Convolutional Neural Networks/191 CNN in Python - Step 2.mp4 7.2 MB
15 Kernel SVM/088 Kernel SVM Intuition.mp4 6.4 MB
04 Simple Linear Regression/019 Simple Linear Regression Intuition - Step 2.mp4 6.0 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/167 Natural Language Processing in R - Step 5.mp4 5.8 MB
05 Multiple Linear Regression/032 Multiple Linear Regression Intuition - Step 4.mp4 5.3 MB
19 Evaluating Classification Models Performance/108 Accuracy Paradox.mp4 4.2 MB
29 --------------------- Part 7 Natural Language Processing ---------------------/154 Natural Language Processing in Python - Step 3.mp4 4.2 MB
02 -------------------------- Part 1 Data Preprocessing --------------------------/006 Welcome to Part 1 - Data Preprocessing.mp4 3.5 MB
32 Convolutional Neural Networks/192 CNN in Python - Step 3.mp4 2.8 MB
05 Multiple Linear Regression/030 Multiple Linear Regression Intuition - Step 2.mp4 2.0 MB
05 Multiple Linear Regression/029 Multiple Linear Regression Intuition - Step 1.mp4 2.0 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 1.0 MB
27 Upper Confidence Bound UCB/attached_files/143 Upper Confidence Bound in R - Step 1/UCB.zip 1.0 MB
28 Thompson Sampling/attached_files/147 Thompson Sampling in Python - Step 1/Thompson-Sampling.zip 1008.9 KB
28 Thompson Sampling/attached_files/149 Thompson Sampling in R - Step 1/Thompson-Sampling.zip 1008.9 KB
05 Multiple Linear Regression/attached_files/033 Multiple Linear Regression Intuition - Step 5/Step-by-step-Blueprints-For-Building-Models.pdf 768.6 KB
39 XGBoost/attached_files/211 XGBoost in Python - Step 1/XGBoost.zip 259.3 KB
24 Apriori/attached_files/134 Apriori in Python - Step 1/Apriori-Python.zip 53.2 KB
24 Apriori/attached_files/131 Apriori in R - Step 1/Apriori.zip 49.1 KB
25 Eclat/attached_files/137 Eclat in R/Eclat.zip 48.5 KB
16 Naive Bayes/captions/094 Bayes Theorem-EN.srt 30.7 KB
18 Random Forest Classification/captions/105 Random Forest Classification in R-EN.srt 28.8 KB
08 Decision Tree Regression/captions/060 Decision Tree Regression in R-EN.srt 28.5 KB
29 --------------------- Part 7 Natural Language Processing ---------------------/attached_files/152 Natural Language Processing in Python - Step 1/Natural-Language-Processing.zip 27.9 KB
29 --------------------- Part 7 Natural Language Processing ---------------------/attached_files/163 Natural Language Processing in R - Step 1/Natural-Language-Processing.zip 27.9 KB
06 Polynomial Regression/captions/048 Polynomial Regression in Python - Step 3-EN.srt 27.8 KB
24 Apriori/captions/133 Apriori in R - Step 3-EN.srt 27.7 KB
24 Apriori/captions/131 Apriori in R - Step 1-EN.srt 27.7 KB
07 Support Vector Regression SVR/captions/056 SVR in Python-EN.srt 27.4 KB
06 Polynomial Regression/captions/053 Polynomial Regression in R - Step 3-EN.srt 27.4 KB
18 Random Forest Classification/captions/104 Random Forest Classification in Python-EN.srt 27.4 KB
12 Logistic Regression/captions/074 Logistic Regression in Python - Step 5-EN.srt 26.5 KB
12 Logistic Regression/captions/080 Logistic Regression in R - Step 5-EN.srt 26.0 KB
17 Decision Tree Classification/captions/102 Decision Tree Classification in R-EN.srt 25.8 KB
21 K-Means Clustering/captions/115 K-Means Clustering in Python-EN.srt 25.2 KB
09 Random Forest Regression/captions/063 Random Forest Regression in R-EN.srt 25.1 KB
15 Kernel SVM/captions/092 Kernel SVM in Python-EN.srt 25.0 KB
24 Apriori/captions/134 Apriori in Python - Step 1-EN.srt 24.8 KB
05 Multiple Linear Regression/captions/043 Multiple Linear Regression in R - Backward Elimination - HOMEWORK-EN.srt 24.6 KB
09 Random Forest Regression/captions/062 Random Forest Regression in Python-EN.srt 24.4 KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/013 Splitting the Dataset into the Training set and Test set-EN.srt 23.9 KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/012 Categorical Data-EN.srt 23.9 KB
15 Kernel SVM/captions/093 Kernel SVM in R-EN.srt 22.7 KB
05 Multiple Linear Regression/captions/034 Multiple Linear Regression in Python - Step 1-EN.srt 21.5 KB
04 Simple Linear Regression/captions/027 Simple Linear Regression in R - Step 4-EN.srt 21.2 KB
08 Decision Tree Regression/captions/059 Decision Tree Regression in Python-EN.srt 21.1 KB
05 Multiple Linear Regression/captions/033 Multiple Linear Regression Intuition - Step 5-EN.srt 21.1 KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/011 Missing Data-EN.srt 21.0 KB
21 K-Means Clustering/captions/112 K-Means Clustering Intuition-EN.srt 20.9 KB
16 Naive Bayes/captions/095 Naive Bayes Intuition-EN.srt 20.9 KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/014 Feature Scaling-EN.srt 20.8 KB
13 K-Nearest Neighbors K-NN/captions/084 K-NN in R-EN.srt 20.7 KB
24 Apriori/captions/132 Apriori in R - Step 2-EN.srt 20.6 KB
24 Apriori/captions/135 Apriori in Python - Step 2-EN.srt 20.1 KB
04 Simple Linear Regression/captions/023 Simple Linear Regression in Python - Step 4-EN.srt 20.0 KB
16 Naive Bayes/captions/099 Naive Bayes in R-EN.srt 19.4 KB
13 K-Nearest Neighbors K-NN/captions/083 K-NN in Python-EN.srt 18.7 KB
05 Multiple Linear Regression/captions/037 Multiple Linear Regression in Python - Backward Elimination - Preparation-EN.srt 17.7 KB
05 Multiple Linear Regression/captions/038 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK-EN.srt 17.6 KB
24 Apriori/captions/136 Apriori in Python - Step 3-EN.srt 17.4 KB
21 K-Means Clustering/captions/116 K-Means Clustering in R-EN.srt 17.3 KB
17 Decision Tree Classification/captions/101 Decision Tree Classification in Python-EN.srt 17.2 KB
14 Support Vector Machine SVM/captions/086 SVM in Python-EN.srt 16.9 KB
06 Polynomial Regression/captions/055 R Regression Template-EN.srt 16.7 KB
07 Support Vector Regression SVR/captions/057 SVR in R-EN.srt 16.6 KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/009 Importing the Dataset-EN.srt 16.6 KB
21 K-Means Clustering/captions/114 K-Means Selecting The Number Of Clusters-EN.srt 16.5 KB
14 Support Vector Machine SVM/captions/087 SVM in R-EN.srt 16.4 KB
22 Hierarchical Clustering/captions/119 Hierarchical Clustering Using Dendrograms-EN.srt 15.8 KB
06 Polynomial Regression/captions/046 Polynomial Regression in Python - Step 1-EN.srt 15.7 KB
06 Polynomial Regression/captions/047 Polynomial Regression in Python - Step 2-EN.srt 15.3 KB
08 Decision Tree Regression/captions/058 Decision Tree Regression Intuition-EN.srt 15.2 KB
06 Polynomial Regression/captions/050 Python Regression Template-EN.srt 14.7 KB
19 Evaluating Classification Models Performance/captions/109 CAP Curve-EN.srt 14.5 KB
16 Naive Bayes/captions/097 Naive Bayes Intuition Extras-EN.srt 14.3 KB
14 Support Vector Machine SVM/captions/085 SVM Intuition-EN.srt 14.2 KB
25 Eclat/captions/137 Eclat in R-EN.srt 14.1 KB
04 Simple Linear Regression/captions/020 Simple Linear Regression in Python - Step 1-EN.srt 13.9 KB
05 Multiple Linear Regression/captions/041 Multiple Linear Regression in R - Step 2-EN.srt 13.8 KB
06 Polynomial Regression/captions/054 Polynomial Regression in R - Step 4-EN.srt 13.7 KB
06 Polynomial Regression/captions/052 Polynomial Regression in R - Step 2-EN.srt 13.7 KB
22 Hierarchical Clustering/captions/117 Hierarchical Clustering Intuition-EN.srt 13.1 KB
10 Evaluating Regression Models Performance/captions/065 Adjusted R-Squared Intuition-EN.srt 13.0 KB
22 Hierarchical Clustering/captions/118 Hierarchical Clustering How Dendrograms Work-EN.srt 12.8 KB
05 Multiple Linear Regression/captions/039 Multiple Linear Regression in Python - Backward Elimination - Homework Solution-EN.srt 12.7 KB
02 -------------------------- Part 1 Data Preprocessing --------------------------/captions/015 And here is our Data Preprocessing Template-EN.srt 12.7 KB
06 Polynomial Regression/captions/051 Polynomial Regression in R - Step 1-EN.srt 12.6 KB
16 Naive Bayes/captions/098 Naive Bayes in Python-EN.srt 12.2 KB
10 Evaluating Regression Models Performance/captions/067 Interpreting Linear Regression Coefficients-EN.srt 12.0 KB
21 K-Means Clustering/captions/113 K-Means Random Initialization Trap-EN.srt 11.6 KB
10 Evaluating Regression Models Performance/captions/066 Evaluating Regression Models Performance - Homeworks Final Part-EN.srt 11.6 KB
17 Decision Tree Classification/captions/100 Decision Tree Classification Intuition-EN.srt 11.5 KB
04 Simple Linear Regression/captions/021 Simple Linear Regression in Python - Step 2-EN.srt 11.1 KB
01 Welcome to the course/captions/004 Installing Python and Anaconda MAC Windows-EN.srt 11.0 KB
05 Multiple Linear Regression/captions/044 Multiple Linear Regression in R - Backward Elimination - Homework Solution-EN.srt 10.6 KB
05 Multiple Linear Regression/captions/040 Multiple Linear Regression in R - Step 1-EN.srt 10.5 KB
19 Evaluating Classification Models Performance/captions/106 False Positives False Negatives-EN.srt 10.2 KB
05 Multiple Linear Regression/captions/031 Multiple Linear Regression Intuition - Step 3-EN.srt 9.7 KB
09 Random Forest Regression/captions/061 Random Forest Regression Intuition-EN.srt 9.3 KB
04 Simple Linear Regression/captions/022 Simple Linear Regression in Python - Step 3-EN.srt 8.9 KB
18 Random Forest Classification/attached_files/104 Random Forest Classification in Python/Random-Forest-Classification.zip 8.9 KB
18 Random Forest Classification/attached_files/105 Random Forest Classification in R/Random-Forest-Classification.zip 8.9 KB
17 Decision Tree Classification/attached_files/101 Decision Tree Classification in Python/Decision-Tree-Classification.zip 8.9 KB
17 Decision Tree Classification/attached_files/102 Decision Tree Classification in R/Decision-Tree-Classification.zip 8.9 KB
22 Hierarchical Clustering/captions/121 HC in Python - Step 2-EN.srt 8.6 KB
16 Naive Bayes/captions/096 Naive Bayes Intuition Challenge Reveal-EN.srt 8.6 KB
13 K-Nearest Neighbors K-NN/attached_files/083 K-NN in Python/K-Nearest-Neighbors.zip 8.6 KB
13 K-Nearest Neighbors K-NN/attached_files/084 K-NN in R/K-Nearest-Neighbors.zip 8.6 KB
15 Kernel SVM/attached_files/092 Kernel SVM in Python/Kernel-SVM.zip 8.4 KB
15 Kernel SVM/attached_files/093 Kernel SVM in R/Kernel-SVM.zip 8.4 KB
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16 Naive Bayes/attached_files/099 Naive Bayes in R/Naive-Bayes.zip 8.4 KB
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29 --------------------- Part 7 Natural Language Processing ---------------------/151 Welcome to Part 7 - Natural Language Processing.html 2.0 KB
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02 -------------------------- Part 1 Data Preprocessing --------------------------/010 For Python learners summary of Object-oriented programming classes objects.html 1.7 KB
29 --------------------- Part 7 Natural Language Processing ---------------------/173 Homework Challenge.html 1.7 KB
29 --------------------- Part 7 Natural Language Processing ---------------------/162 Homework Challenge.html 1.7 KB
33 ----------------------- Part 9 Dimensionality Reduction -----------------------/201 Welcome to Part 9 - Dimensionality Reduction.html 1.6 KB
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01 Welcome to the course/005 BONUS Meet your instructors.html 1.3 KB
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37 --------------------- Part 10 Model Selection Boosting ---------------------/207 Welcome to Part 10 - Model Selection Boosting.html 1.2 KB
03 ------------------------------ Part 2 Regression ------------------------------/016 Welcome to Part 2 - Regression.html 1.1 KB
26 ------------------------ Part 6 Reinforcement Learning ------------------------/138 Welcome to Part 6 - Reinforcement Learning.html 1.1 KB
11 ---------------------------- Part 3 Classification ----------------------------/068 Welcome to Part 3 - Classification.html 1.1 KB
30 ---------------------------- Part 8 Deep Learning ----------------------------/174 Welcome to Part 8 - Deep Learning.html 1.0 KB
20 ---------------------------- Part 4 Clustering ----------------------------/111 Welcome to Part 4 - Clustering.html 1004 bytes
39 XGBoost/213 Download all the Codes and Datasets Here.html 888 bytes
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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