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| 001 Install Anaconda package_en.vtt |
3.51Кб |
| 001 Install Anaconda package.mp4 |
29.65Мб |
| 001 Introduction to Course_en.vtt |
2.34Кб |
| 001 Introduction to Course.mp4 |
25.44Мб |
| 001 Introduction to Deep Learning_en.vtt |
5.93Кб |
| 001 Introduction to Deep Learning.mp4 |
36.05Мб |
| 001 Introduction to Supervised Learning Algorithms_en.vtt |
1.19Кб |
| 001 Introduction to Supervised Learning Algorithms.mp4 |
6.26Мб |
| 001 Review Unsupervised Learning Algorithms_en.vtt |
1.62Кб |
| 001 Review Unsupervised Learning Algorithms.mp4 |
8.52Мб |
| 001 What is Statistics_en.vtt |
1.41Кб |
| 001 What is Statistics.mp4 |
6.05Мб |
| 002 Course Contents_en.vtt |
1.51Кб |
| 002 Course Contents.mp4 |
9.05Мб |
| 002 Hierarchical Clustering Algorithm_en.vtt |
2.82Кб |
| 002 Hierarchical Clustering Algorithm.mp4 |
8.93Мб |
| 002 Introduction to Jupyter_en.vtt |
4.69Кб |
| 002 Introduction to Jupyter.mp4 |
29.70Мб |
| 002 Sample And Population_en.vtt |
1.16Кб |
| 002 Sample And Population.mp4 |
6.63Мб |
| 002 Types of Variables_en.vtt |
2.40Кб |
| 002 Types of Variables.mp4 |
9.57Мб |
| 002 Use Deep Learning in Classification_en.vtt |
2.30Кб |
| 002 Use Deep Learning in Classification.mp4 |
13.25Мб |
| 003 1-Create-Lists-Tuples-and-Dictionaries.ipynb |
3.63Кб |
| 003 Control a pace of a video_en.vtt |
712б |
| 003 Control a pace of a video.mp4 |
3.80Мб |
| 003 Dendrogram Diagram Method_en.vtt |
4.58Кб |
| 003 Dendrogram Diagram Method.mp4 |
20.85Мб |
| 003 Descriptive and Inferential Statistics_en.vtt |
1.59Кб |
| 003 Descriptive and Inferential Statistics.mp4 |
8.18Мб |
| 003 How Does Deep Learning Work_en.vtt |
5.96Кб |
| 003 How Does Deep Learning Work.mp4 |
33.03Мб |
| 003 Introduction to Python Part-1(Create Lists)_en.vtt |
5.88Кб |
| 003 Introduction to Python Part-1(Create Lists).mp4 |
35.61Мб |
| 003 Introduction to Regression Analysis_en.vtt |
4.33Кб |
| 003 Introduction to Regression Analysis.mp4 |
21.26Мб |
| 004 Activation Functions_en.vtt |
6.25Кб |
| 004 Activation Functions.mp4 |
43.14Мб |
| 004 Data types_en.vtt |
3.61Кб |
| 004 Data types.mp4 |
22.52Мб |
| 004 Introduction to Data Mining_en.vtt |
1.99Кб |
| 004 Introduction to Data Mining.mp4 |
9.27Мб |
| 004 Introduction to Python Part-2 (Create Tuples & Dictionaries)_en.vtt |
3.18Кб |
| 004 Introduction to Python Part-2 (Create Tuples & Dictionaries).mp4 |
21.53Мб |
| 004 Movies.csv |
1.66Кб |
| 004 Overview on the business problem data_en.vtt |
716б |
| 004 Overview on the business problem data.mp4 |
4.18Мб |
| 004 Regression Model Slope_en.vtt |
6.23Кб |
| 004 Regression Model Slope.mp4 |
29.56Мб |
| 005 2-Loops-in-Python.ipynb |
2.43Кб |
| 005 Business Applications of Data Mining_en.vtt |
4.41Кб |
| 005 Business Applications of Data Mining.mp4 |
15.87Мб |
| 005 Create Hierarchical Clustering Algorithm in Python-1_en.vtt |
8.28Кб |
| 005 Create Hierarchical Clustering Algorithm in Python-1.mp4 |
60.73Мб |
| 005 HC-Clustering.ipynb |
2.82Кб |
| 005 Introduction to Python Part-3 (Loops & Functions)_en.vtt |
7.18Кб |
| 005 Introduction to Python Part-3 (Loops & Functions).mp4 |
38.56Мб |
| 005 The Intercept Value_en.vtt |
636б |
| 005 The Intercept Value.mp4 |
2.91Мб |
| 005 Visualize Data_en.vtt |
2.04Кб |
| 005 Visualize Data.mp4 |
13.40Мб |
| 005 Walmart-Stores.xlsx |
14.92Кб |
| 005 What is Tensorflow_en.vtt |
2.39Кб |
| 005 What is Tensorflow.mp4 |
10.76Мб |
| 006 3-Import-Libraries.ipynb |
4.13Кб |
| 006 Create Hierarchical Clustering Algorithm in Python-2_en.vtt |
7.93Кб |
| 006 Create Hierarchical Clustering Algorithm in Python-2.mp4 |
56.11Мб |
| 006 Data Mining Process Pyramid_en.vtt |
1.98Кб |
| 006 Data Mining Process Pyramid.mp4 |
12.57Мб |
| 006 Histogram_en.vtt |
4.58Кб |
| 006 Histogram.mp4 |
36.88Мб |
| 006 Histogram.xlsx |
15.72Кб |
| 006 Introduction to Pandas Library_en.vtt |
8.80Кб |
| 006 Introduction to Pandas Library.mp4 |
66.12Мб |
| 006 Introduction to the Deep Learning Problem and Dataset_en.vtt |
1016б |
| 006 Introduction to the Deep Learning Problem and Dataset.mp4 |
8.95Мб |
| 006 R-Squared Value_en.vtt |
7.10Кб |
| 006 R-Squared Value.mp4 |
28.56Мб |
| 006 Sales-data.csv |
83.95Кб |
| 007 Central Tendency Measures_en.vtt |
3.06Кб |
| 007 Central Tendency Measures.mp4 |
15.10Мб |
| 007 Create Artificial Neural Network Model in Python Part-1_en.vtt |
4.97Кб |
| 007 Create Artificial Neural Network Model in Python Part-1.mp4 |
43.02Мб |
| 007 Deep-learning-model.ipynb |
3.76Кб |
| 007 Introduction to Machine Learning_en.vtt |
1.99Кб |
| 007 Introduction to Machine Learning.mp4 |
10.64Мб |
| 007 Introduction to NumPy & Matplotlib Libraries_en.vtt |
3.71Кб |
| 007 Introduction to NumPy & Matplotlib Libraries.mp4 |
25.26Мб |
| 007 K-means Clustering Algorithm_en.vtt |
3.55Кб |
| 007 K-means Clustering Algorithm.mp4 |
16.17Мб |
| 007 Medical-data.csv |
23.45Кб |
| 007 P-Value_en.vtt |
3.71Кб |
| 007 P-Value.mp4 |
17.43Мб |
| 008 Create Artificial Neural Network Model in Python Part-2_en.vtt |
7.87Кб |
| 008 Create Artificial Neural Network Model in Python Part-2.mp4 |
60.23Мб |
| 008 How Does Machine Learning Work_en.vtt |
3.78Кб |
| 008 How Does Machine Learning Work.mp4 |
18.73Мб |
| 008 Introduction to Scikit-learn Library_en.vtt |
818б |
| 008 Introduction to Scikit-learn Library.mp4 |
5.71Мб |
| 008 Simple Linear Regression_en.vtt |
870б |
| 008 Simple Linear Regression.mp4 |
3.75Мб |
| 008 Using Elbow Method to Determine Optimal Number of Clusters_en.vtt |
9.76Кб |
| 008 Using Elbow Method to Determine Optimal Number of Clusters.mp4 |
48.80Мб |
| 008 Variability Measures_en.vtt |
3.24Кб |
| 008 Variability Measures.mp4 |
13.43Мб |
| 009 Calculate Central and Variability Measures (Practical)_en.vtt |
3.18Кб |
| 009 Calculate Central and Variability Measures (Practical).mp4 |
23.03Мб |
| 009 Concepts used in Machine Learning (Important).html |
228б |
| 009 Create Artificial Neural Network Model in Python Part-3_en.vtt |
4.89Кб |
| 009 Create Artificial Neural Network Model in Python Part-3.mp4 |
42.73Мб |
| 009 Create K-means Clustering Algorithm Model in Python - 1_en.vtt |
6.94Кб |
| 009 Create K-means Clustering Algorithm Model in Python - 1.mp4 |
55.00Мб |
| 009 K-means-clustering-model.ipynb |
2.79Кб |
| 009 Link-to-the-Keras-documentation-website..url |
41б |
| 009 Machine Learning Algorithms Types_en.vtt |
3.71Кб |
| 009 Machine Learning Algorithms Types.mp4 |
16.62Мб |
| 009 Variance-and-SD.xlsx |
10.89Кб |
| 010 Course Rating.html |
493б |
| 010 Create K-means Clustering Algorithm Model in Python - 2_en.vtt |
3.04Кб |
| 010 Create K-means Clustering Algorithm Model in Python - 2.mp4 |
21.01Мб |
| 010 Overview on the dataset_en.vtt |
797б |
| 010 Overview on the dataset.mp4 |
5.05Мб |
| 010 Reinforcement Learning overview_en.vtt |
1.96Кб |
| 010 Reinforcement Learning overview.mp4 |
12.93Мб |
| 010 Study-Hours.csv |
287б |
| 010 Symmetry and skewness in data_en.vtt |
1.67Кб |
| 010 Symmetry and skewness in data.mp4 |
9.70Мб |
| 011 Association Rules (Market Basket Analysis)_en.vtt |
9.96Кб |
| 011 Association Rules (Market Basket Analysis).mp4 |
52.22Мб |
| 011 Correlation and Covariance_en.vtt |
4.52Кб |
| 011 Correlation and Covariance.mp4 |
23.78Мб |
| 011 Course Rating.html |
493б |
| 011 Create Simple Linear Regression Model in Python-Part 1_en.vtt |
6.25Кб |
| 011 Create Simple Linear Regression Model in Python-Part 1.mp4 |
38.52Мб |
| 011 Simple-Linear-Regression.ipynb |
3.43Кб |
| 012 Create Simple Linear Regression Model in Python-Part 2_en.vtt |
5.53Кб |
| 012 Create Simple Linear Regression Model in Python-Part 2.mp4 |
34.61Мб |
| 012 GroceryStoreDataSet.csv |
1.85Кб |
| 012 Introduction to Inferential Statistics_en.vtt |
2.10Кб |
| 012 Introduction to Inferential Statistics.mp4 |
13.84Мб |
| 012 Overview on the business problem data_en.vtt |
729б |
| 012 Overview on the business problem data.mp4 |
4.13Мб |
| 013 apriori-model.ipynb |
11.62Кб |
| 013 Create Association Rules (Market Basket Analysis) Model in Python - 1_en.vtt |
6.01Кб |
| 013 Create Association Rules (Market Basket Analysis) Model in Python - 1.mp4 |
41.23Мб |
| 013 Create Simple Linear Regression Model in Python-Part 3_en.vtt |
3.77Кб |
| 013 Create Simple Linear Regression Model in Python-Part 3.mp4 |
25.97Мб |
| 013 Discrete Probability Distributions_en.vtt |
3.05Кб |
| 013 Discrete Probability Distributions.mp4 |
15.51Мб |
| 014 Create Association Rules (Market Basket Analysis) Model in Python - 2_en.vtt |
4.70Кб |
| 014 Create Association Rules (Market Basket Analysis) Model in Python - 2.mp4 |
37.72Мб |
| 014 Create Simple Linear Regression Model in Python-Part 4_en.vtt |
4.50Кб |
| 014 Create Simple Linear Regression Model in Python-Part 4.mp4 |
27.41Мб |
| 014 Normal Distribution_en.vtt |
5.33Кб |
| 014 Normal Distribution.mp4 |
23.97Мб |
| 015 Create Association Rules (Market Basket Analysis) Model in Python - 3_en.vtt |
3.13Кб |
| 015 Create Association Rules (Market Basket Analysis) Model in Python - 3.mp4 |
34.70Мб |
| 015 Create Simple Linear Regression Model in Python-Part 5_en.vtt |
8.17Кб |
| 015 Create Simple Linear Regression Model in Python-Part 5.mp4 |
56.93Мб |
| 015 Variable standardization_en.vtt |
2.47Кб |
| 015 Variable standardization.mp4 |
11.24Мб |
| 016 Multiple Linear Regression_en.vtt |
2.57Кб |
| 016 Multiple Linear Regression.mp4 |
14.19Мб |
| 016 Variable standardization Demo_en.vtt |
940б |
| 016 Variable standardization Demo.mp4 |
8.90Мб |
| 017 Dummy Variables_en.vtt |
4.96Кб |
| 017 Dummy Variables.mp4 |
36.36Мб |
| 017 Introduction to Central Limit Theorem_en.vtt |
3.29Кб |
| 017 Introduction to Central Limit Theorem.mp4 |
23.50Мб |
| 018 Dummy Variables Trap.html |
612б |
| 018 Estimators_en.vtt |
1.40Кб |
| 018 Estimators.mp4 |
7.40Мб |
| 019 Introduction to Confidence Interval_en.vtt |
4.77Кб |
| 019 Introduction to Confidence Interval.mp4 |
23.20Мб |
| 019 Stepwise Approach_en.vtt |
6.13Кб |
| 019 Stepwise Approach.mp4 |
28.78Мб |
| 020 Assumptions of Multiple Linear Regression_en.vtt |
8.24Кб |
| 020 Assumptions of Multiple Linear Regression.mp4 |
31.31Мб |
| 020 Calculate Confidence Interval for one Sample with a Known Population Variance_en.vtt |
5.33Кб |
| 020 Calculate Confidence Interval for one Sample with a Known Population Variance.mp4 |
22.79Мб |
| 021 Companies-spends-and-profits.csv |
3.24Кб |
| 021 Introduction to the Business Problem_en.vtt |
2.24Кб |
| 021 Introduction to the Business Problem.mp4 |
11.36Мб |
| 021 Overview on the business problem data_en.vtt |
1.09Кб |
| 021 Overview on the business problem data.mp4 |
7.64Мб |
| 022 1-Confidence-intervals-variance-known.xlsx |
45.15Кб |
| 022 Calculate Confidence Interval in Excel_en.vtt |
7.60Кб |
| 022 Calculate Confidence Interval in Excel.mp4 |
78.71Мб |
| 022 Create Multiple Linear Regression Model in Python-Part 1_en.vtt |
4.33Кб |
| 022 Create Multiple Linear Regression Model in Python-Part 1.mp4 |
33.62Мб |
| 022 Multiple-Linear-Regression.ipynb |
3.61Кб |
| 023 Create Multiple Linear Regression Model in Python-Part 2_en.vtt |
5.85Кб |
| 023 Create Multiple Linear Regression Model in Python-Part 2.mp4 |
51.01Мб |
| 023 t - Distribution_en.vtt |
3.75Кб |
| 023 t - Distribution.mp4 |
21.70Мб |
| 024 2-Confidence-intervals-variance-unknown.xlsx |
37.92Кб |
| 024 Calculate Confidence Interval for one Sample with a Unknown Population Variance_en.vtt |
3.54Кб |
| 024 Calculate Confidence Interval for one Sample with a Unknown Population Variance.mp4 |
32.06Мб |
| 024 Create Multiple Linear Regression Model in Python-Part 3_en.vtt |
9.14Кб |
| 024 Create Multiple Linear Regression Model in Python-Part 3.mp4 |
92.09Мб |
| 025 Create Multiple Linear Regression Model in Python-Part 4_en.vtt |
9.38Кб |
| 025 Create Multiple Linear Regression Model in Python-Part 4.mp4 |
61.71Мб |
| 025 Reduce Margin of Error_en.vtt |
2.38Кб |
| 025 Reduce Margin of Error.mp4 |
9.51Мб |
| 026 Confidence Interval for two Dependent Samples_en.vtt |
1.26Кб |
| 026 Confidence Interval for two Dependent Samples.mp4 |
5.58Мб |
| 026 Polynomial Regression_en.vtt |
2.40Кб |
| 026 Polynomial Regression.mp4 |
10.86Мб |
| 027 Calculate Confidence Interval for two Dependent Samples in Excel_en.vtt |
3.98Кб |
| 027 Calculate Confidence Interval for two Dependent Samples in Excel.mp4 |
38.33Мб |
| 027 Overview on the business problem data_en.vtt |
1.13Кб |
| 027 Overview on the business problem data.mp4 |
7.17Мб |
| 027 Reward-system.csv |
213б |
| 028 3-Confidence-intervals-dependent-samples.xlsx |
37.96Кб |
| 028 Confidence Interval for two Independent Samples with a Known Population Variance_en.vtt |
2.73Кб |
| 028 Confidence Interval for two Independent Samples with a Known Population Variance.mp4 |
18.24Мб |
| 028 Create Polynomial Regression Model in Python-Part 1_en.vtt |
7.35Кб |
| 028 Create Polynomial Regression Model in Python-Part 1.mp4 |
48.80Мб |
| 028 Polynomial-Regression-Model.ipynb |
4.16Кб |
| 029 Calculate Confidence Interval for two Independent Samples Known Var in Excel_en.vtt |
4.39Кб |
| 029 Calculate Confidence Interval for two Independent Samples Known Var in Excel.mp4 |
37.62Мб |
| 029 Create Polynomial Regression Model in Python-Part 2_en.vtt |
8.14Кб |
| 029 Create Polynomial Regression Model in Python-Part 2.mp4 |
57.60Мб |
| 030 5-Confidence-intervals-independent-samples-variance-unknown-and-equal.xlsx |
70.08Кб |
| 030 Confidence Interval for two Independent Samples Unknown Population Variance_en.vtt |
4.75Кб |
| 030 Confidence Interval for two Independent Samples Unknown Population Variance.mp4 |
40.03Мб |
| 030 Create Polynomial Regression Model in Python-Part 3_en.vtt |
3.53Кб |
| 030 Create Polynomial Regression Model in Python-Part 3.mp4 |
23.12Мб |
| 031 Course Rating.html |
493б |
| 031 What is a Statistical Hypothesis_en.vtt |
2.32Кб |
| 031 What is a Statistical Hypothesis.mp4 |
13.95Мб |
| 032 Introduction to Classification_en.vtt |
4.10Кб |
| 032 Introduction to Classification.mp4 |
19.88Мб |
| 032 Types of Hypotheses_en.vtt |
3.58Кб |
| 032 Types of Hypotheses.mp4 |
20.54Мб |
| 033 Introduction to Logistic Regression_en.vtt |
7.80Кб |
| 033 Introduction to Logistic Regression.mp4 |
29.10Мб |
| 033 P-Value_en.vtt |
2.16Кб |
| 033 P-Value.mp4 |
10.46Мб |
| 034 Confusion Matrix_en.vtt |
3.98Кб |
| 034 Confusion Matrix.mp4 |
15.56Мб |
| 034 Link to z-value Calculator.html |
105б |
| 035 Standard Scaler_en.vtt |
2.96Кб |
| 035 Standard Scaler.mp4 |
12.16Мб |
| 035 Testing a Hypothesis for one Sample, Variance is Known_en.vtt |
1.55Кб |
| 035 Testing a Hypothesis for one Sample, Variance is Known.mp4 |
7.43Мб |
| 036 6-Test-Hypothises-population-variance-known.xlsx |
69.05Кб |
| 036 Bank-Data.csv |
17.25Кб |
| 036 Overview on the business problem data_en.vtt |
1.57Кб |
| 036 Overview on the business problem data.mp4 |
10.28Мб |
| 036 Testing the Hypothesis in Excel_en.vtt |
3.62Кб |
| 036 Testing the Hypothesis in Excel.mp4 |
36.22Мб |
| 037 7-Test-hypothises-population-variance-unknown.xlsx |
69.67Кб |
| 037 Create Logistic Regression Model in Python-Part 1_en.vtt |
8.34Кб |
| 037 Create Logistic Regression Model in Python-Part 1.mp4 |
63.07Мб |
| 037 Logistic-Regression-Model.ipynb |
3.61Кб |
| 037 Testing a Hypothesis for one Sample, Variance is Unknown_en.vtt |
2.83Кб |
| 037 Testing a Hypothesis for one Sample, Variance is Unknown.mp4 |
23.74Мб |
| 038 8-Test-hypothises-dependent-samples.xlsx |
49.24Кб |
| 038 Create Logistic Regression Model in Python-Part 2_en.vtt |
5.58Кб |
| 038 Create Logistic Regression Model in Python-Part 2.mp4 |
44.71Мб |
| 038 Testing a Hypothesis for two Dependent Samples_en.vtt |
4.42Кб |
| 038 Testing a Hypothesis for two Dependent Samples.mp4 |
35.54Мб |
| 039 KNN Classification Algorithm_en.vtt |
3.57Кб |
| 039 KNN Classification Algorithm.mp4 |
17.76Мб |
| 039 Link to t-value Calculator.html |
99б |
| 040 9-Test-hypothises-two-independent-samples-variance-known.xlsx |
68.71Кб |
| 040 Bank-Data.csv |
17.25Кб |
| 040 Create KNN Model in Python_en.vtt |
6.83Кб |
| 040 Create KNN Model in Python.mp4 |
51.93Мб |
| 040 KNN-Model.ipynb |
3.58Кб |
| 040 Testing a Hypothesis for two Independent Samples, Variance is Known_en.vtt |
3.76Кб |
| 040 Testing a Hypothesis for two Independent Samples, Variance is Known.mp4 |
25.03Мб |
| 041 10-Test-hypothises-two-independent-samples-variance-unknown.xlsx |
91.15Кб |
| 041 Support Vector Machine (SVM) Classification Algorithm_en.vtt |
3.84Кб |
| 041 Support Vector Machine (SVM) Classification Algorithm.mp4 |
18.90Мб |
| 041 Testing a Hypothesis for two Independent Samples, Variance is Unknown_en.vtt |
3.09Кб |
| 041 Testing a Hypothesis for two Independent Samples, Variance is Unknown.mp4 |
23.20Мб |
| 042 Create Support Vector Machine in Python_en.vtt |
6.15Кб |
| 042 Create Support Vector Machine in Python.mp4 |
45.85Мб |
| 042 Support-Vector-Machine.ipynb |
2.10Кб |
| 043 Naive Bayes Algorithm Part 1_en.vtt |
4.55Кб |
| 043 Naive Bayes Algorithm Part 1.mp4 |
19.82Мб |
| 044 Naive Bayes Algorithm Part 2_en.vtt |
6.10Кб |
| 044 Naive Bayes Algorithm Part 2.mp4 |
27.92Мб |
| 045 Create Naive Bayes Model in Python_en.vtt |
2.47Кб |
| 045 Create Naive Bayes Model in Python.mp4 |
21.58Мб |
| 045 Naive-Bayes-Model.ipynb |
2.49Кб |
| 046 Decision Tree Algorithm_en.vtt |
6.89Кб |
| 046 Decision Tree Algorithm.mp4 |
34.46Мб |
| 047 Bank-Data.csv |
17.25Кб |
| 047 Create Decision Tree Model in Python_en.vtt |
2.21Кб |
| 047 Create Decision Tree Model in Python.mp4 |
18.81Мб |
| 047 Decision-Tree-Model.ipynb |
2.56Кб |
| 048 Random Forest Algorithm_en.vtt |
1.26Кб |
| 048 Random Forest Algorithm.mp4 |
6.07Мб |
| 049 Create Random Forest Model in Python_en.vtt |
4.32Кб |
| 049 Create Random Forest Model in Python.mp4 |
36.01Мб |
| 049 Random-Forest-Model.ipynb |
3.84Кб |
| 050 Course Rating.html |
493б |
| Bonus Resources.txt |
386б |
| external-links.txt |
67б |
| Get Bonus Downloads Here.url |
182б |