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| [CourseClub.NET].url |
123б |
| [FCS Forum].url |
133б |
| [FreeCourseSite.com].url |
127б |
| 1.1 AdvanceReg.zip.zip |
1.11Мб |
| 1.1 Boosting.zip.zip |
1.26Мб |
| 1.1 code-LR-Teclov.zip.zip |
76.83Кб |
| 1.1 CrossValidation_Linear Regression.zip.zip |
342.22Кб |
| 1.1 Datavisual.zip.zip |
1.20Мб |
| 1.1 DT_forudemy.zip.zip |
4.03Мб |
| 1.1 Gradient+Descent+Updated.zip.zip |
161.15Кб |
| 1.1 Hotstarcode-for-udemy.zip.zip |
254.59Кб |
| 1.1 KNN.zip.zip |
1.34Мб |
| 1.1 LogisticReg.zip.zip |
983.68Кб |
| 1.1 Multplr_LR_Code_for Udemy.zip.zip |
521.01Кб |
| 1.1 NaiveBayes.zip.zip |
266.04Кб |
| 1.1 Pandas.zip.zip |
15.46Кб |
| 1.1 PCA code for udemy.zip.zip |
9.06Мб |
| 1.1 SVM.zip.zip |
15.41Мб |
| 1.1 Teclov-numpy.ipynb.zip.zip |
5.16Кб |
| 1.1 training.zip.zip |
59.99Мб |
| 1.1 Unsupervised.zip.zip |
7.38Мб |
| 1.1 z-table.pdf.pdf |
58.97Кб |
| 1.2 RF_forudemy.zip.zip |
1.05Мб |
| 1.2 Teclov Project - Medical treatment.ipynb.zip.zip |
1.28Мб |
| 1.2 t-table.pdf.pdf |
147.30Кб |
| 1. Expectations.mp4 |
9.36Мб |
| 1. Expectations.vtt |
2.80Кб |
| 1. Inferential Statistics.mp4 |
10.31Мб |
| 1. Inferential Statistics.vtt |
3.05Кб |
| 1. Introduction.mp4 |
16.46Мб |
| 1. Introduction.mp4 |
26.60Мб |
| 1. Introduction.mp4 |
58.71Мб |
| 1. Introduction.mp4 |
29.78Мб |
| 1. Introduction.mp4 |
24.74Мб |
| 1. Introduction.mp4 |
156.68Мб |
| 1. Introduction.mp4 |
30.94Мб |
| 1. Introduction.mp4 |
39.10Мб |
| 1. Introduction.mp4 |
31.09Мб |
| 1. Introduction.mp4 |
3.79Мб |
| 1. Introduction.vtt |
3.63Кб |
| 1. Introduction.vtt |
8.18Кб |
| 1. Introduction.vtt |
13.72Кб |
| 1. Introduction.vtt |
8.97Кб |
| 1. Introduction.vtt |
6.27Кб |
| 1. Introduction.vtt |
32.17Кб |
| 1. Introduction.vtt |
7.18Кб |
| 1. Introduction.vtt |
7.87Кб |
| 1. Introduction.vtt |
9.20Кб |
| 1. Introduction.vtt |
897б |
| 1. Introduction to Classification.mp4 |
54.11Мб |
| 1. Introduction to Classification.vtt |
15.53Кб |
| 1. Introduction to Clustering.mp4 |
59.13Мб |
| 1. Introduction to Clustering.vtt |
12.68Кб |
| 1. Introduction to Ensembles.mp4 |
39.28Мб |
| 1. Introduction to Ensembles.vtt |
11.08Кб |
| 1. Introduction to Machine Learning.mp4 |
11.16Мб |
| 1. Introduction to Machine Learning.vtt |
2.19Кб |
| 1. Introduction to Naive Bayes.mp4 |
73.37Мб |
| 1. Introduction to Naive Bayes.vtt |
17.80Кб |
| 1. Introduction to the course.mp4 |
93.85Мб |
| 1. Introduction to the course.vtt |
16.32Кб |
| 1. Introduction to the Problem Statement.mp4 |
40.85Мб |
| 1. Introduction to the Problem Statement.mp4 |
93.36Мб |
| 1. Introduction to the Problem Statement.vtt |
6.24Кб |
| 1. Introduction to the Problem Statement.vtt |
9.64Кб |
| 1. Linear Algebra Vectors.mp4 |
162.41Мб |
| 1. Linear Algebra Vectors.vtt |
49.93Кб |
| 1. Matplotlib.mp4 |
172.76Мб |
| 1. Matplotlib.vtt |
26.33Кб |
| 1. Model Creation Case1.mp4 |
52.09Мб |
| 1. Model Creation Case1.vtt |
12.42Кб |
| 1. Model Selection Part1.mp4 |
104.30Мб |
| 1. Model Selection Part1.vtt |
23.20Кб |
| 1. Performance Metrics Part1.mp4 |
113.83Мб |
| 1. Performance Metrics Part1.vtt |
27.14Кб |
| 1. Pre-Req For Gradient Descent Part1.mp4 |
61.24Мб |
| 1. Pre-Req For Gradient Descent Part1.vtt |
17.58Кб |
| 10. Adaboost Part2.mp4 |
38.46Мб |
| 10. Adaboost Part2.vtt |
7.93Кб |
| 10. Adjusted R Square.mp4 |
20.13Мб |
| 10. Adjusted R Square.vtt |
4.09Кб |
| 10. Case Study.mp4 |
70.71Мб |
| 10. Case Study.vtt |
10.80Кб |
| 10. Case Study 2 Part1.mp4 |
74.57Мб |
| 10. Case Study 2 Part1.vtt |
8.91Кб |
| 10. Case Study Part2.mp4 |
61.33Мб |
| 10. Case Study Part2.vtt |
9.04Кб |
| 10. Case Study Part5.mp4 |
45.73Мб |
| 10. Case Study Part5.vtt |
6.10Кб |
| 10. DT Case Study Part2.mp4 |
95.71Мб |
| 10. DT Case Study Part2.vtt |
10.91Кб |
| 10. Functions.mp4 |
85.62Мб |
| 10. Functions.vtt |
14.50Кб |
| 10. groupby.mp4 |
46.92Мб |
| 10. groupby.vtt |
7.06Кб |
| 10. Kernel Part2.mp4 |
71.13Мб |
| 10. Kernel Part2.vtt |
12.68Кб |
| 10. Normal Distribution.mp4 |
19.02Мб |
| 10. Normal Distribution.vtt |
5.29Кб |
| 10. Residual Square Error (RSE).mp4 |
4.55Мб |
| 10. Residual Square Error (RSE).vtt |
1.02Кб |
| 10. Response encoding and one hot encoder.mp4 |
54.68Мб |
| 10. Response encoding and one hot encoder.vtt |
6.58Кб |
| 10. Types of Error.mp4 |
15.30Мб |
| 10. Types of Error.vtt |
3.41Кб |
| 10. Univariate Analysis Part1.mp4 |
82.78Мб |
| 10. Univariate Analysis Part1.vtt |
25.79Кб |
| 11. Adaboost Case Study.mp4 |
53.65Мб |
| 11. Adaboost Case Study.vtt |
6.01Кб |
| 11. Case Study 2.mp4 |
90.00Мб |
| 11. Case Study 2.vtt |
8.36Кб |
| 11. Case Study 2 Part2.mp4 |
25.35Мб |
| 11. Case Study 2 Part2.vtt |
2.97Кб |
| 11. Case Study Part6 (RFE).mp4 |
64.15Мб |
| 11. Case Study Part6 (RFE).vtt |
8.24Кб |
| 11. Classification Case1.mp4 |
84.22Мб |
| 11. Classification Case1.vtt |
25.01Кб |
| 11. Laplace Smoothing and Calibrated classifier.mp4 |
48.25Мб |
| 11. Laplace Smoothing and Calibrated classifier.vtt |
14.41Кб |
| 11. Merging Part2.mp4 |
33.90Мб |
| 11. Merging Part2.vtt |
5.73Кб |
| 11. More on Segmentation.mp4 |
18.06Мб |
| 11. More on Segmentation.vtt |
5.50Кб |
| 11. String Part1.mp4 |
106.01Мб |
| 11. String Part1.vtt |
15.53Кб |
| 11. t- distribution Part1.mp4 |
21.31Мб |
| 11. t- distribution Part1.vtt |
4.15Кб |
| 11. Univariate Analysis Part2.mp4 |
60.85Мб |
| 11. Univariate Analysis Part2.vtt |
19.57Кб |
| 11. z Score.mp4 |
23.80Мб |
| 11. z Score.vtt |
5.35Кб |
| 12. Case Study 3 Part1.mp4 |
56.01Мб |
| 12. Case Study 3 Part1.vtt |
9.92Кб |
| 12. Classification Case2.mp4 |
52.23Мб |
| 12. Classification Case2.vtt |
16.93Кб |
| 12. Hierarchial Clustering.mp4 |
38.02Мб |
| 12. Hierarchial Clustering.vtt |
9.03Кб |
| 12. Pivot Table.mp4 |
27.70Мб |
| 12. Pivot Table.vtt |
4.50Кб |
| 12. Sampling.mp4 |
38.73Мб |
| 12. Sampling.vtt |
9.88Кб |
| 12. Segmented Analysis.mp4 |
24.47Мб |
| 12. Segmented Analysis.vtt |
7.78Кб |
| 12. Significance of first categorical column.mp4 |
71.74Мб |
| 12. Significance of first categorical column.vtt |
8.91Кб |
| 12. String Part2.mp4 |
27.38Мб |
| 12. String Part2.vtt |
3.45Кб |
| 12. t- distribution Part2.mp4 |
29.32Мб |
| 12. t- distribution Part2.vtt |
3.06Кб |
| 12. XGBoost.mp4 |
23.11Мб |
| 12. XGBoost.vtt |
4.74Кб |
| 13. Bivariate Analysis.mp4 |
60.60Мб |
| 13. Bivariate Analysis.vtt |
16.44Кб |
| 13. Boosting Part1.mp4 |
13.69Мб |
| 13. Boosting Part1.vtt |
3.70Кб |
| 13. Case Study.mp4 |
34.40Мб |
| 13. Case Study.vtt |
6.54Кб |
| 13. Case Study 3 Part2.mp4 |
61.28Мб |
| 13. Case Study 3 Part2.vtt |
6.24Кб |
| 13. Classification Case3.mp4 |
52.97Мб |
| 13. Classification Case3.vtt |
15.21Кб |
| 13. List Part1.mp4 |
10.04Мб |
| 13. List Part1.vtt |
2.91Кб |
| 13. Sampling Distribution.mp4 |
25.51Мб |
| 13. Sampling Distribution.vtt |
6.87Кб |
| 13. Second Categorical column.mp4 |
45.70Мб |
| 13. Second Categorical column.vtt |
5.27Кб |
| 14. Boosting Part2.mp4 |
35.51Мб |
| 14. Boosting Part2.vtt |
7.82Кб |
| 14. Case Study 4.mp4 |
164.41Мб |
| 14. Case Study 4.vtt |
20.37Кб |
| 14. Central Limit Theorem.mp4 |
13.10Мб |
| 14. Central Limit Theorem.vtt |
2.97Кб |
| 14. Classification Case4.mp4 |
41.10Мб |
| 14. Classification Case4.vtt |
13.79Кб |
| 14. Derived Columns.mp4 |
41.89Мб |
| 14. Derived Columns.vtt |
14.40Кб |
| 14. List Part2.mp4 |
87.32Мб |
| 14. List Part2.vtt |
13.17Кб |
| 14. Third Categorical column.mp4 |
66.72Мб |
| 14. Third Categorical column.vtt |
8.57Кб |
| 15. Confidence Interval Part1.mp4 |
34.55Мб |
| 15. Confidence Interval Part1.vtt |
7.26Кб |
| 15. Data pre-processing before building machine learning model.mp4 |
50.59Мб |
| 15. Data pre-processing before building machine learning model.vtt |
5.64Кб |
| 15. List Part3.mp4 |
73.56Мб |
| 15. List Part3.vtt |
10.47Кб |
| 15. XGboost Algorithm.mp4 |
38.76Мб |
| 15. XGboost Algorithm.vtt |
8.79Кб |
| 16. Building Machine Learning model part1.mp4 |
124.01Мб |
| 16. Building Machine Learning model part1.vtt |
17.30Кб |
| 16. Case Study Part1.mp4 |
141.54Мб |
| 16. Case Study Part1.vtt |
11.77Кб |
| 16. Confidence Interval Part2.mp4 |
13.39Мб |
| 16. Confidence Interval Part2.vtt |
3.19Кб |
| 16. List Part4.mp4 |
63.85Мб |
| 16. List Part4.vtt |
10.43Кб |
| 17. Building Machine Learning model part2.mp4 |
135.18Мб |
| 17. Building Machine Learning model part2.vtt |
15.30Кб |
| 17. Case Study Part2.mp4 |
136.70Мб |
| 17. Case Study Part2.vtt |
13.37Кб |
| 17. Tuples.mp4 |
67.33Мб |
| 17. Tuples.vtt |
10.18Кб |
| 18. Building Machine Learning model part3.mp4 |
38.41Мб |
| 18. Building Machine Learning model part3.vtt |
4.16Кб |
| 18. Case Study Part3.mp4 |
75.43Мб |
| 18. Case Study Part3.vtt |
6.88Кб |
| 18. Sets.mp4 |
58.16Мб |
| 18. Sets.vtt |
7.81Кб |
| 19. Building Machine Learning model part4.mp4 |
33.07Мб |
| 19. Building Machine Learning model part4.vtt |
3.91Кб |
| 19. Dictionaries.mp4 |
61.60Мб |
| 19. Dictionaries.vtt |
8.32Кб |
| 2. Bagging.mp4 |
71.21Мб |
| 2. Bagging.vtt |
15.44Кб |
| 2. Bayes Theorem.mp4 |
63.05Мб |
| 2. Bayes Theorem.vtt |
12.74Кб |
| 2. Case Study part1.mp4 |
83.04Мб |
| 2. Case Study part1.vtt |
8.51Кб |
| 2. Data Sourcing and Cleaning part1.mp4 |
15.56Мб |
| 2. Data Sourcing and Cleaning part1.vtt |
4.05Кб |
| 2. Defining Classification Mathematically.mp4 |
39.99Мб |
| 2. Defining Classification Mathematically.vtt |
9.02Кб |
| 2. Example of DT.mp4 |
40.59Мб |
| 2. Example of DT.vtt |
9.17Кб |
| 2. Example Part1.mp4 |
27.48Мб |
| 2. Example Part1.vtt |
6.03Кб |
| 2. Hyperplane Part1.mp4 |
27.07Мб |
| 2. Hyperplane Part1.vtt |
6.11Кб |
| 2. Introduction.mp4 |
48.76Мб |
| 2. Introduction.vtt |
10.57Кб |
| 2. Introduction to Kaggle.mp4 |
90.07Мб |
| 2. Introduction to Kaggle.vtt |
11.15Кб |
| 2. Linear Algebra Matrix Part1.mp4 |
95.26Мб |
| 2. Linear Algebra Matrix Part1.vtt |
16.85Кб |
| 2. Model Creation Case2.mp4 |
34.67Мб |
| 2. Model Creation Case2.vtt |
8.78Кб |
| 2. Model Selection Part2.mp4 |
41.33Мб |
| 2. Model Selection Part2.vtt |
14.54Кб |
| 2. NULL And Alternate Hypothesis.mp4 |
28.79Мб |
| 2. NULL And Alternate Hypothesis.vtt |
7.52Кб |
| 2. Numpy Operations Part1.mp4 |
128.75Мб |
| 2. Numpy Operations Part1.vtt |
23.83Кб |
| 2. PCA.mp4 |
98.39Мб |
| 2. PCA.vtt |
26.45Кб |
| 2. Performance Metrics Part2.mp4 |
90.48Мб |
| 2. Performance Metrics Part2.vtt |
19.15Кб |
| 2. Playing With Data.mp4 |
81.36Мб |
| 2. Playing With Data.vtt |
11.90Кб |
| 2. Playing With The Data.mp4 |
137.05Мб |
| 2. Playing With The Data.vtt |
17.90Кб |
| 2. Pre-Req For Gradient Descent Part2.mp4 |
32.90Мб |
| 2. Pre-Req For Gradient Descent Part2.vtt |
8.96Кб |
| 2. Probability Theory.mp4 |
54.79Мб |
| 2. Probability Theory.vtt |
13.87Кб |
| 2. Seaborn.mp4 |
184.74Мб |
| 2. Seaborn.vtt |
26.01Кб |
| 2. Segmentation.mp4 |
28.65Мб |
| 2. Segmentation.vtt |
8.70Кб |
| 2. Series.mp4 |
61.49Мб |
| 2. Series.vtt |
9.58Кб |
| 2. Sigmoid Function.mp4 |
44.31Мб |
| 2. Sigmoid Function.vtt |
11.63Кб |
| 2. Types of Machine Learning.mp4 |
35.38Мб |
| 2. Types of Machine Learning.vtt |
9.00Кб |
| 20. Building Machine Learning model part5.mp4 |
41.94Мб |
| 20. Building Machine Learning model part5.vtt |
5.09Кб |
| 20. Comprehentions.mp4 |
70.54Мб |
| 20. Comprehentions.vtt |
8.08Кб |
| 21. Building Machine Learning model part6.mp4 |
50.82Мб |
| 21. Building Machine Learning model part6.vtt |
9.10Кб |
| 3.1 Python-code-udemy.zip.zip |
16.42Кб |
| 3.2 Installing-Python.Teclov.pdf.pdf |
1.37Мб |
| 3. Advantages.mp4 |
14.87Мб |
| 3. Advantages.vtt |
5.07Кб |
| 3. Building Model Part1.mp4 |
55.07Мб |
| 3. Building Model Part1.vtt |
5.84Кб |
| 3. Case Study.mp4 |
113.20Мб |
| 3. Case Study.vtt |
12.91Кб |
| 3. Case Study part2.mp4 |
98.41Мб |
| 3. Case Study part2.vtt |
12.18Кб |
| 3. Cost Functions.mp4 |
13.16Мб |
| 3. Cost Functions.vtt |
2.83Кб |
| 3. DataFrame.mp4 |
66.19Мб |
| 3. DataFrame.vtt |
9.32Кб |
| 3. Data Sourcing and Cleaning part2.mp4 |
15.62Мб |
| 3. Data Sourcing and Cleaning part2.vtt |
2.53Кб |
| 3. Example Part2.mp4 |
45.11Мб |
| 3. Example Part2.vtt |
10.74Кб |
| 3. Examples.mp4 |
27.75Мб |
| 3. Examples.vtt |
6.68Кб |
| 3. Gridsearch Case study Part1.mp4 |
124.24Мб |
| 3. Gridsearch Case study Part1.vtt |
13.48Кб |
| 3. History.mp4 |
61.86Мб |
| 3. History.vtt |
17.97Кб |
| 3. Homogenity.mp4 |
20.61Мб |
| 3. Homogenity.vtt |
5.84Кб |
| 3. Hyperplane Part2.mp4 |
65.32Мб |
| 3. Hyperplane Part2.vtt |
16.77Кб |
| 3. Installation of Python and Anaconda.mp4 |
82.29Мб |
| 3. Installation of Python and Anaconda.vtt |
11.12Кб |
| 3. Introduction to KNN.mp4 |
47.13Мб |
| 3. Introduction to KNN.vtt |
13.69Кб |
| 3. Introduction to Linear Regression (LR).mp4 |
17.88Мб |
| 3. Introduction to Linear Regression (LR).vtt |
2.97Кб |
| 3. Kmeans.mp4 |
57.71Мб |
| 3. Kmeans.vtt |
10.13Кб |
| 3. Linear Algebra Matrix Part2.mp4 |
77.99Мб |
| 3. Linear Algebra Matrix Part2.vtt |
19.40Кб |
| 3. Log Odds.mp4 |
41.83Мб |
| 3. Log Odds.vtt |
10.91Кб |
| 3. Maths Behind PCA.mp4 |
96.82Мб |
| 3. Maths Behind PCA.vtt |
25.52Кб |
| 3. Model Selection Part3.mp4 |
35.66Мб |
| 3. Numpy Operations Part2.mp4 |
169.97Мб |
| 3. Numpy Operations Part2.vtt |
29.79Кб |
| 3. Performance Metrics Part3.mp4 |
24.02Мб |
| 3. Performance Metrics Part3.vtt |
6.24Кб |
| 3. Practical Example from NB with One Column.mp4 |
80.59Мб |
| 3. Practical Example from NB with One Column.vtt |
10.68Кб |
| 3. Probability Distribution.mp4 |
24.24Мб |
| 3. Probability Distribution.vtt |
5.47Кб |
| 3. Translating the Problem In Machine Learning World.mp4 |
113.02Мб |
| 3. Translating the Problem In Machine Learning World.vtt |
11.88Кб |
| 4.1 Python-code-udemy.zip.zip |
16.42Кб |
| 4. Accuracy of KNN.mp4 |
57.16Мб |
| 4. Accuracy of KNN.vtt |
14.85Кб |
| 4. Building Model Part2.mp4 |
87.80Мб |
| 4. Building Model Part2.vtt |
9.31Кб |
| 4. Case Study.mp4 |
198.20Мб |
| 4. Case Study.vtt |
20.41Кб |
| 4. Case Study Part1.mp4 |
45.47Мб |
| 4. Case Study Part1.vtt |
6.08Кб |
| 4. Case Study part3.mp4 |
68.67Мб |
| 4. Case Study part3.vtt |
7.75Кб |
| 4. Data Sourcing and Cleaning part3.mp4 |
10.03Мб |
| 4. Data Sourcing and Cleaning part3.vtt |
3.37Кб |
| 4. Dealing with Text Data.mp4 |
98.05Мб |
| 4. Dealing with Text Data.vtt |
9.90Кб |
| 4. Defining Cost Functions More Formally.mp4 |
36.51Мб |
| 4. Defining Cost Functions More Formally.vtt |
8.59Кб |
| 4. Expected Values Part1.mp4 |
24.25Мб |
| 4. Expected Values Part1.vtt |
5.52Кб |
| 4. Gini Index.mp4 |
44.19Мб |
| 4. Gini Index.vtt |
8.88Кб |
| 4. Gridsearch Case study Part2.mp4 |
178.88Мб |
| 4. Gridsearch Case study Part2.vtt |
18.44Кб |
| 4. How LR Works.mp4 |
58.68Мб |
| 4. How LR Works.vtt |
9.93Кб |
| 4. Linear Algebra Going From 2D to nD Part1.mp4 |
27.71Мб |
| 4. Linear Algebra Going From 2D to nD Part1.vtt |
9.94Кб |
| 4. Maths Behind Kmeans.mp4 |
53.75Мб |
| 4. Maths Behind Kmeans.vtt |
13.18Кб |
| 4. Maths Behind SVM.mp4 |
24.04Мб |
| 4. Maths Behind SVM.vtt |
8.15Кб |
| 4. OneTwo Tailed Tests.mp4 |
38.00Мб |
| 4. OneTwo Tailed Tests.vtt |
10.14Кб |
| 4. Operations Part1.mp4 |
12.02Мб |
| 4. Operations Part1.vtt |
1.44Кб |
| 4. Optimal Solution.mp4 |
65.23Мб |
| 4. Optimal Solution.vtt |
16.71Кб |
| 4. Perceptron.mp4 |
29.78Мб |
| 4. Perceptron.vtt |
8.24Кб |
| 4. Practical Example from NB with Multiple Columns.mp4 |
59.83Мб |
| 4. Practical Example from NB with Multiple Columns.vtt |
13.16Кб |
| 4. Python Introduction.mp4 |
10.25Мб |
| 4. Python Introduction.vtt |
3.54Кб |
| 4. Runtime.mp4 |
16.38Мб |
| 4. Runtime.vtt |
4.66Кб |
| 4. Seaborn On Time Series Data.mp4 |
54.06Мб |
| 4. Seaborn On Time Series Data.vtt |
5.60Кб |
| 5. Adjusted R Square.mp4 |
8.08Мб |
| 5. Adjusted R Square.vtt |
855б |
| 5. Building Model Part3.mp4 |
48.52Мб |
| 5. Building Model Part3.vtt |
4.65Кб |
| 5. Case study.mp4 |
73.09Мб |
| 5. Case study.mp4 |
39.97Мб |
| 5. Case study.vtt |
6.89Кб |
| 5. Case study.vtt |
4.21Кб |
| 5. Case Study Part2.mp4 |
123.06Мб |
| 5. Case Study Part2.vtt |
18.98Кб |
| 5. Critical Value Method.mp4 |
24.71Мб |
| 5. Critical Value Method.vtt |
4.55Кб |
| 5. Data Sourcing and Cleaning part4.mp4 |
10.37Мб |
| 5. Data Sourcing and Cleaning part4.vtt |
3.85Кб |
| 5. Effectiveness of KNN.mp4 |
48.23Мб |
| 5. Effectiveness of KNN.vtt |
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| 5. Expected Values Part2.mp4 |
14.49Мб |
| 5. Expected Values Part2.vtt |
3.87Кб |
| 5. Gradient Descent.mp4 |
37.66Мб |
| 5. Gradient Descent.vtt |
12.51Кб |
| 5. Information Gain Part1.mp4 |
29.29Мб |
| 5. Information Gain Part1.vtt |
6.68Кб |
| 5. Linear Algebra 2D to nD Part2.mp4 |
25.78Мб |
| 5. Linear Algebra 2D to nD Part2.vtt |
8.16Кб |
| 5. More Maths.mp4 |
9.43Мб |
| 5. More Maths.vtt |
2.91Кб |
| 5. Multi Layered Perceptron.mp4 |
63.83Мб |
| 5. Multi Layered Perceptron.vtt |
14.50Кб |
| 5. Naive Bayes On Text Data Part1.mp4 |
54.74Мб |
| 5. Naive Bayes On Text Data Part1.vtt |
9.99Кб |
| 5. Operations Part2.mp4 |
44.10Мб |
| 5. Operations Part2.vtt |
6.10Кб |
| 5. Some Fun With Maths Behind LR.mp4 |
52.75Мб |
| 5. Some Fun With Maths Behind LR.vtt |
10.98Кб |
| 5. Support Vectors.mp4 |
11.04Мб |
| 5. Support Vectors.vtt |
3.95Кб |
| 5. Train, Test And Cross Validation Split.mp4 |
116.21Мб |
| 5. Train, Test And Cross Validation Split.vtt |
12.27Кб |
| 5. Variables in Python.mp4 |
110.46Мб |
| 5. Variables in Python.vtt |
20.73Кб |
| 6. Case Study Part1.mp4 |
68.55Мб |
| 6. Case Study Part1.vtt |
8.83Кб |
| 6. Data Sourcing and Cleaning part5.mp4 |
12.41Мб |
| 6. Data Sourcing and Cleaning part5.vtt |
3.73Кб |
| 6. Distance Metrics.mp4 |
47.90Мб |
| 6. Distance Metrics.vtt |
14.65Кб |
| 6. Indexes.mp4 |
50.11Мб |
| 6. Indexes.vtt |
7.44Кб |
| 6. Information Gain Part2.mp4 |
27.37Мб |
| 6. Information Gain Part2.vtt |
5.65Кб |
| 6. Introduction to Boosting.mp4 |
33.05Мб |
| 6. Introduction to Boosting.vtt |
6.47Кб |
| 6. Kmeans plus.mp4 |
51.78Мб |
| 6. Kmeans plus.vtt |
11.43Кб |
| 6. Naive Bayes On Text Data Part2.mp4 |
46.06Мб |
| 6. Naive Bayes On Text Data Part2.vtt |
6.58Кб |
| 6. Neural Network Playground.mp4 |
103.70Мб |
| 6. Neural Network Playground.vtt |
13.60Кб |
| 6. Numeric Operations in Python.mp4 |
36.92Мб |
| 6. Numeric Operations in Python.vtt |
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| 6. Optimisation.mp4 |
21.68Мб |
| 6. Optimisation.vtt |
5.06Кб |
| 6. Regularization.mp4 |
48.60Мб |
| 6. Regularization.vtt |
10.32Кб |
| 6. R Square.mp4 |
52.47Мб |
| 6. R Square.vtt |
12.33Кб |
| 6. Slack Variable.mp4 |
33.27Мб |
| 6. Slack Variable.vtt |
10.22Кб |
| 6. Understanding Evaluation Matrix Log Loss.mp4 |
85.50Мб |
| 6. Understanding Evaluation Matrix Log Loss.vtt |
19.98Кб |
| 6. Verification of Model.mp4 |
39.49Мб |
| 6. Verification of Model.vtt |
4.74Кб |
| 6. Without Experiment.mp4 |
28.68Мб |
| 6. Without Experiment.vtt |
7.20Кб |
| 6. z Table.mp4 |
58.63Мб |
| 6. z Table.vtt |
8.80Кб |
| 7. Advantages and Disadvantages of DT.mp4 |
15.45Мб |
| 7. Advantages and Disadvantages of DT.vtt |
4.43Кб |
| 7. Binomial Distribution.mp4 |
17.58Мб |
| 7. Binomial Distribution.vtt |
4.21Кб |
| 7. Building A Worst Model.mp4 |
68.49Мб |
| 7. Building A Worst Model.vtt |
10.66Кб |
| 7. Case Study Part2.mp4 |
72.90Мб |
| 7. Case Study Part2.vtt |
12.31Кб |
| 7. Closed Form Vs Gradient Descent.mp4 |
26.61Мб |
| 7. Closed Form Vs Gradient Descent.vtt |
5.77Кб |
| 7. Data Sourcing and Cleaning part6.mp4 |
53.70Мб |
| 7. Data Sourcing and Cleaning part6.vtt |
4.36Кб |
| 7. Distance Metrics Part2.mp4 |
28.83Мб |
| 7. Distance Metrics Part2.vtt |
9.26Кб |
| 7. Examples.mp4 |
26.42Мб |
| 7. Examples.vtt |
3.55Кб |
| 7. Laplace Smoothing.mp4 |
55.26Мб |
| 7. Laplace Smoothing.vtt |
4.94Кб |
| 7. loc and iloc.mp4 |
59.37Мб |
| 7. loc and iloc.vtt |
9.34Кб |
| 7. Logical Operations.mp4 |
17.32Мб |
| 7. Logical Operations.vtt |
3.22Кб |
| 7. LR Case Study Part1.mp4 |
137.50Мб |
| 7. LR Case Study Part1.vtt |
17.46Кб |
| 7. Ridge and Lasso.mp4 |
39.95Мб |
| 7. Ridge and Lasso.vtt |
7.70Кб |
| 7. SVM Case Study Part1.mp4 |
74.15Мб |
| 7. SVM Case Study Part1.vtt |
6.49Кб |
| 7. Value of K.mp4 |
35.82Мб |
| 7. Value of K.vtt |
7.62Кб |
| 7. Weak Learners.mp4 |
17.90Мб |
| 7. Weak Learners.vtt |
3.11Кб |
| 8. Bernoulli Naive Bayes.mp4 |
27.11Мб |
| 8. Bernoulli Naive Bayes.vtt |
2.04Кб |
| 8. Case Study.mp4 |
106.22Мб |
| 8. Case Study.vtt |
10.68Кб |
| 8. Case Study Part3.mp4 |
66.56Мб |
| 8. Case Study Part3.vtt |
7.65Кб |
| 8. Commulative Distribution.mp4 |
8.37Мб |
| 8. Commulative Distribution.vtt |
2.72Кб |
| 8. Data Cleaning part1.mp4 |
76.24Мб |
| 8. Data Cleaning part1.vtt |
16.71Кб |
| 8. Evaluating Worst ML Model.mp4 |
58.87Мб |
| 8. Evaluating Worst ML Model.vtt |
7.07Кб |
| 8. Finding k.mp4 |
33.32Мб |
| 8. Finding k.vtt |
11.49Кб |
| 8. Gradient Descent case study.mp4 |
71.66Мб |
| 8. Gradient Descent case study.vtt |
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| 8. Hopkins test.mp4 |
12.27Мб |
| 8. Hopkins test.vtt |
3.02Кб |
| 8. If else Loop.mp4 |
64.01Мб |
| 8. If else Loop.vtt |
10.03Кб |
| 8. LR Case Study Part2.mp4 |
53.38Мб |
| 8. LR Case Study Part2.vtt |
5.44Кб |
| 8. More Examples.mp4 |
16.47Мб |
| 8. More Examples.vtt |
3.38Кб |
| 8. Preventing Overfitting Issues in DT.mp4 |
40.29Мб |
| 8. Preventing Overfitting Issues in DT.vtt |
11.77Кб |
| 8. Reading CSV.mp4 |
42.47Мб |
| 8. Reading CSV.vtt |
6.93Кб |
| 8. Shallow Decision Tree.mp4 |
14.96Мб |
| 8. Shallow Decision Tree.vtt |
2.73Кб |
| 8. SVM Case Study Part2.mp4 |
66.16Мб |
| 8. SVM Case Study Part2.vtt |
8.41Кб |
| 9. Adaboost Part1.mp4 |
41.53Мб |
| 9. Adaboost Part1.vtt |
8.25Кб |
| 9. Case Study 1.mp4 |
95.46Мб |
| 9. Case Study 1.vtt |
10.81Кб |
| 9. Case Study Part1.mp4 |
95.82Мб |
| 9. Case Study Part1.vtt |
13.18Кб |
| 9. Case Study Part4.mp4 |
132.20Мб |
| 9. Case Study Part4.vtt |
17.82Кб |
| 9. Data Cleaning part2.mp4 |
29.70Мб |
| 9. Data Cleaning part2.vtt |
11.04Кб |
| 9. DT Case Study Part1.mp4 |
125.45Мб |
| 9. DT Case Study Part1.vtt |
12.92Кб |
| 9. First Categorical column analysis.mp4 |
71.13Мб |
| 9. First Categorical column analysis.vtt |
14.66Кб |
| 9. for while Loop.mp4 |
77.78Мб |
| 9. for while Loop.vtt |
12.99Кб |
| 9. Kernel Part1.mp4 |
49.24Мб |
| 9. Kernel Part1.vtt |
9.36Кб |
| 9. KNN on Regression.mp4 |
9.28Мб |
| 9. KNN on Regression.vtt |
2.92Кб |
| 9. LR Case Study Part3.mp4 |
46.44Мб |
| 9. LR Case Study Part3.vtt |
5.54Кб |
| 9. Merging Part1.mp4 |
30.01Мб |
| 9. Merging Part1.vtt |
4.34Кб |
| 9. Model Selection.mp4 |
31.30Мб |
| 9. Model Selection.vtt |
6.52Кб |
| 9. PDF.mp4 |
21.00Мб |
| 9. PDF.vtt |
5.42Кб |
| 9. p Value.mp4 |
33.48Мб |
| 9. p Value.vtt |
6.47Кб |