|
Please note that this page does not hosts or makes available any of the listed filenames. You
cannot download any of those files from here.
|
| [CourseClub.NET].url |
123B |
| [FCS Forum].url |
133B |
| [FreeCourseSite.com].url |
127B |
| 1.1 AdvanceReg.zip.zip |
1.11MB |
| 1.1 Boosting.zip.zip |
1.26MB |
| 1.1 code-LR-Teclov.zip.zip |
76.83KB |
| 1.1 CrossValidation_Linear Regression.zip.zip |
342.22KB |
| 1.1 Datavisual.zip.zip |
1.20MB |
| 1.1 DT_forudemy.zip.zip |
4.03MB |
| 1.1 Gradient+Descent+Updated.zip.zip |
161.15KB |
| 1.1 Hotstarcode-for-udemy.zip.zip |
254.59KB |
| 1.1 KNN.zip.zip |
1.34MB |
| 1.1 LogisticReg.zip.zip |
983.68KB |
| 1.1 Multplr_LR_Code_for Udemy.zip.zip |
521.01KB |
| 1.1 NaiveBayes.zip.zip |
266.04KB |
| 1.1 Pandas.zip.zip |
15.46KB |
| 1.1 PCA code for udemy.zip.zip |
9.06MB |
| 1.1 SVM.zip.zip |
15.41MB |
| 1.1 Teclov-numpy.ipynb.zip.zip |
5.16KB |
| 1.1 training.zip.zip |
59.99MB |
| 1.1 Unsupervised.zip.zip |
7.38MB |
| 1.1 z-table.pdf.pdf |
58.97KB |
| 1.2 RF_forudemy.zip.zip |
1.05MB |
| 1.2 Teclov Project - Medical treatment.ipynb.zip.zip |
1.28MB |
| 1.2 t-table.pdf.pdf |
147.30KB |
| 1. Expectations.mp4 |
9.36MB |
| 1. Expectations.vtt |
2.80KB |
| 1. Inferential Statistics.mp4 |
10.31MB |
| 1. Inferential Statistics.vtt |
3.05KB |
| 1. Introduction.mp4 |
16.46MB |
| 1. Introduction.mp4 |
26.60MB |
| 1. Introduction.mp4 |
58.71MB |
| 1. Introduction.mp4 |
29.78MB |
| 1. Introduction.mp4 |
24.74MB |
| 1. Introduction.mp4 |
156.68MB |
| 1. Introduction.mp4 |
30.94MB |
| 1. Introduction.mp4 |
39.10MB |
| 1. Introduction.mp4 |
31.09MB |
| 1. Introduction.mp4 |
3.79MB |
| 1. Introduction.vtt |
3.63KB |
| 1. Introduction.vtt |
8.18KB |
| 1. Introduction.vtt |
13.72KB |
| 1. Introduction.vtt |
8.97KB |
| 1. Introduction.vtt |
6.27KB |
| 1. Introduction.vtt |
32.17KB |
| 1. Introduction.vtt |
7.18KB |
| 1. Introduction.vtt |
7.87KB |
| 1. Introduction.vtt |
9.20KB |
| 1. Introduction.vtt |
897B |
| 1. Introduction to Classification.mp4 |
54.11MB |
| 1. Introduction to Classification.vtt |
15.53KB |
| 1. Introduction to Clustering.mp4 |
59.13MB |
| 1. Introduction to Clustering.vtt |
12.68KB |
| 1. Introduction to Ensembles.mp4 |
39.28MB |
| 1. Introduction to Ensembles.vtt |
11.08KB |
| 1. Introduction to Machine Learning.mp4 |
11.16MB |
| 1. Introduction to Machine Learning.vtt |
2.19KB |
| 1. Introduction to Naive Bayes.mp4 |
73.37MB |
| 1. Introduction to Naive Bayes.vtt |
17.80KB |
| 1. Introduction to the course.mp4 |
93.85MB |
| 1. Introduction to the course.vtt |
16.32KB |
| 1. Introduction to the Problem Statement.mp4 |
40.85MB |
| 1. Introduction to the Problem Statement.mp4 |
93.36MB |
| 1. Introduction to the Problem Statement.vtt |
6.24KB |
| 1. Introduction to the Problem Statement.vtt |
9.64KB |
| 1. Linear Algebra Vectors.mp4 |
162.41MB |
| 1. Linear Algebra Vectors.vtt |
49.93KB |
| 1. Matplotlib.mp4 |
172.76MB |
| 1. Matplotlib.vtt |
26.33KB |
| 1. Model Creation Case1.mp4 |
52.09MB |
| 1. Model Creation Case1.vtt |
12.42KB |
| 1. Model Selection Part1.mp4 |
104.30MB |
| 1. Model Selection Part1.vtt |
23.20KB |
| 1. Performance Metrics Part1.mp4 |
113.83MB |
| 1. Performance Metrics Part1.vtt |
27.14KB |
| 1. Pre-Req For Gradient Descent Part1.mp4 |
61.24MB |
| 1. Pre-Req For Gradient Descent Part1.vtt |
17.58KB |
| 10. Adaboost Part2.mp4 |
38.46MB |
| 10. Adaboost Part2.vtt |
7.93KB |
| 10. Adjusted R Square.mp4 |
20.13MB |
| 10. Adjusted R Square.vtt |
4.09KB |
| 10. Case Study.mp4 |
70.71MB |
| 10. Case Study.vtt |
10.80KB |
| 10. Case Study 2 Part1.mp4 |
74.57MB |
| 10. Case Study 2 Part1.vtt |
8.91KB |
| 10. Case Study Part2.mp4 |
61.33MB |
| 10. Case Study Part2.vtt |
9.04KB |
| 10. Case Study Part5.mp4 |
45.73MB |
| 10. Case Study Part5.vtt |
6.10KB |
| 10. DT Case Study Part2.mp4 |
95.71MB |
| 10. DT Case Study Part2.vtt |
10.91KB |
| 10. Functions.mp4 |
85.62MB |
| 10. Functions.vtt |
14.50KB |
| 10. groupby.mp4 |
46.92MB |
| 10. groupby.vtt |
7.06KB |
| 10. Kernel Part2.mp4 |
71.13MB |
| 10. Kernel Part2.vtt |
12.68KB |
| 10. Normal Distribution.mp4 |
19.02MB |
| 10. Normal Distribution.vtt |
5.29KB |
| 10. Residual Square Error (RSE).mp4 |
4.55MB |
| 10. Residual Square Error (RSE).vtt |
1.02KB |
| 10. Response encoding and one hot encoder.mp4 |
54.68MB |
| 10. Response encoding and one hot encoder.vtt |
6.58KB |
| 10. Types of Error.mp4 |
15.30MB |
| 10. Types of Error.vtt |
3.41KB |
| 10. Univariate Analysis Part1.mp4 |
82.78MB |
| 10. Univariate Analysis Part1.vtt |
25.79KB |
| 11. Adaboost Case Study.mp4 |
53.65MB |
| 11. Adaboost Case Study.vtt |
6.01KB |
| 11. Case Study 2.mp4 |
90.00MB |
| 11. Case Study 2.vtt |
8.36KB |
| 11. Case Study 2 Part2.mp4 |
25.35MB |
| 11. Case Study 2 Part2.vtt |
2.97KB |
| 11. Case Study Part6 (RFE).mp4 |
64.15MB |
| 11. Case Study Part6 (RFE).vtt |
8.24KB |
| 11. Classification Case1.mp4 |
84.22MB |
| 11. Classification Case1.vtt |
25.01KB |
| 11. Laplace Smoothing and Calibrated classifier.mp4 |
48.25MB |
| 11. Laplace Smoothing and Calibrated classifier.vtt |
14.41KB |
| 11. Merging Part2.mp4 |
33.90MB |
| 11. Merging Part2.vtt |
5.73KB |
| 11. More on Segmentation.mp4 |
18.06MB |
| 11. More on Segmentation.vtt |
5.50KB |
| 11. String Part1.mp4 |
106.01MB |
| 11. String Part1.vtt |
15.53KB |
| 11. t- distribution Part1.mp4 |
21.31MB |
| 11. t- distribution Part1.vtt |
4.15KB |
| 11. Univariate Analysis Part2.mp4 |
60.85MB |
| 11. Univariate Analysis Part2.vtt |
19.57KB |
| 11. z Score.mp4 |
23.80MB |
| 11. z Score.vtt |
5.35KB |
| 12. Case Study 3 Part1.mp4 |
56.01MB |
| 12. Case Study 3 Part1.vtt |
9.92KB |
| 12. Classification Case2.mp4 |
52.23MB |
| 12. Classification Case2.vtt |
16.93KB |
| 12. Hierarchial Clustering.mp4 |
38.02MB |
| 12. Hierarchial Clustering.vtt |
9.03KB |
| 12. Pivot Table.mp4 |
27.70MB |
| 12. Pivot Table.vtt |
4.50KB |
| 12. Sampling.mp4 |
38.73MB |
| 12. Sampling.vtt |
9.88KB |
| 12. Segmented Analysis.mp4 |
24.47MB |
| 12. Segmented Analysis.vtt |
7.78KB |
| 12. Significance of first categorical column.mp4 |
71.74MB |
| 12. Significance of first categorical column.vtt |
8.91KB |
| 12. String Part2.mp4 |
27.38MB |
| 12. String Part2.vtt |
3.45KB |
| 12. t- distribution Part2.mp4 |
29.32MB |
| 12. t- distribution Part2.vtt |
3.06KB |
| 12. XGBoost.mp4 |
23.11MB |
| 12. XGBoost.vtt |
4.74KB |
| 13. Bivariate Analysis.mp4 |
60.60MB |
| 13. Bivariate Analysis.vtt |
16.44KB |
| 13. Boosting Part1.mp4 |
13.69MB |
| 13. Boosting Part1.vtt |
3.70KB |
| 13. Case Study.mp4 |
34.40MB |
| 13. Case Study.vtt |
6.54KB |
| 13. Case Study 3 Part2.mp4 |
61.28MB |
| 13. Case Study 3 Part2.vtt |
6.24KB |
| 13. Classification Case3.mp4 |
52.97MB |
| 13. Classification Case3.vtt |
15.21KB |
| 13. List Part1.mp4 |
10.04MB |
| 13. List Part1.vtt |
2.91KB |
| 13. Sampling Distribution.mp4 |
25.51MB |
| 13. Sampling Distribution.vtt |
6.87KB |
| 13. Second Categorical column.mp4 |
45.70MB |
| 13. Second Categorical column.vtt |
5.27KB |
| 14. Boosting Part2.mp4 |
35.51MB |
| 14. Boosting Part2.vtt |
7.82KB |
| 14. Case Study 4.mp4 |
164.41MB |
| 14. Case Study 4.vtt |
20.37KB |
| 14. Central Limit Theorem.mp4 |
13.10MB |
| 14. Central Limit Theorem.vtt |
2.97KB |
| 14. Classification Case4.mp4 |
41.10MB |
| 14. Classification Case4.vtt |
13.79KB |
| 14. Derived Columns.mp4 |
41.89MB |
| 14. Derived Columns.vtt |
14.40KB |
| 14. List Part2.mp4 |
87.32MB |
| 14. List Part2.vtt |
13.17KB |
| 14. Third Categorical column.mp4 |
66.72MB |
| 14. Third Categorical column.vtt |
8.57KB |
| 15. Confidence Interval Part1.mp4 |
34.55MB |
| 15. Confidence Interval Part1.vtt |
7.26KB |
| 15. Data pre-processing before building machine learning model.mp4 |
50.59MB |
| 15. Data pre-processing before building machine learning model.vtt |
5.64KB |
| 15. List Part3.mp4 |
73.56MB |
| 15. List Part3.vtt |
10.47KB |
| 15. XGboost Algorithm.mp4 |
38.76MB |
| 15. XGboost Algorithm.vtt |
8.79KB |
| 16. Building Machine Learning model part1.mp4 |
124.01MB |
| 16. Building Machine Learning model part1.vtt |
17.30KB |
| 16. Case Study Part1.mp4 |
141.54MB |
| 16. Case Study Part1.vtt |
11.77KB |
| 16. Confidence Interval Part2.mp4 |
13.39MB |
| 16. Confidence Interval Part2.vtt |
3.19KB |
| 16. List Part4.mp4 |
63.85MB |
| 16. List Part4.vtt |
10.43KB |
| 17. Building Machine Learning model part2.mp4 |
135.18MB |
| 17. Building Machine Learning model part2.vtt |
15.30KB |
| 17. Case Study Part2.mp4 |
136.70MB |
| 17. Case Study Part2.vtt |
13.37KB |
| 17. Tuples.mp4 |
67.33MB |
| 17. Tuples.vtt |
10.18KB |
| 18. Building Machine Learning model part3.mp4 |
38.41MB |
| 18. Building Machine Learning model part3.vtt |
4.16KB |
| 18. Case Study Part3.mp4 |
75.43MB |
| 18. Case Study Part3.vtt |
6.88KB |
| 18. Sets.mp4 |
58.16MB |
| 18. Sets.vtt |
7.81KB |
| 19. Building Machine Learning model part4.mp4 |
33.07MB |
| 19. Building Machine Learning model part4.vtt |
3.91KB |
| 19. Dictionaries.mp4 |
61.60MB |
| 19. Dictionaries.vtt |
8.32KB |
| 2. Bagging.mp4 |
71.21MB |
| 2. Bagging.vtt |
15.44KB |
| 2. Bayes Theorem.mp4 |
63.05MB |
| 2. Bayes Theorem.vtt |
12.74KB |
| 2. Case Study part1.mp4 |
83.04MB |
| 2. Case Study part1.vtt |
8.51KB |
| 2. Data Sourcing and Cleaning part1.mp4 |
15.56MB |
| 2. Data Sourcing and Cleaning part1.vtt |
4.05KB |
| 2. Defining Classification Mathematically.mp4 |
39.99MB |
| 2. Defining Classification Mathematically.vtt |
9.02KB |
| 2. Example of DT.mp4 |
40.59MB |
| 2. Example of DT.vtt |
9.17KB |
| 2. Example Part1.mp4 |
27.48MB |
| 2. Example Part1.vtt |
6.03KB |
| 2. Hyperplane Part1.mp4 |
27.07MB |
| 2. Hyperplane Part1.vtt |
6.11KB |
| 2. Introduction.mp4 |
48.76MB |
| 2. Introduction.vtt |
10.57KB |
| 2. Introduction to Kaggle.mp4 |
90.07MB |
| 2. Introduction to Kaggle.vtt |
11.15KB |
| 2. Linear Algebra Matrix Part1.mp4 |
95.26MB |
| 2. Linear Algebra Matrix Part1.vtt |
16.85KB |
| 2. Model Creation Case2.mp4 |
34.67MB |
| 2. Model Creation Case2.vtt |
8.78KB |
| 2. Model Selection Part2.mp4 |
41.33MB |
| 2. Model Selection Part2.vtt |
14.54KB |
| 2. NULL And Alternate Hypothesis.mp4 |
28.79MB |
| 2. NULL And Alternate Hypothesis.vtt |
7.52KB |
| 2. Numpy Operations Part1.mp4 |
128.75MB |
| 2. Numpy Operations Part1.vtt |
23.83KB |
| 2. PCA.mp4 |
98.39MB |
| 2. PCA.vtt |
26.45KB |
| 2. Performance Metrics Part2.mp4 |
90.48MB |
| 2. Performance Metrics Part2.vtt |
19.15KB |
| 2. Playing With Data.mp4 |
81.36MB |
| 2. Playing With Data.vtt |
11.90KB |
| 2. Playing With The Data.mp4 |
137.05MB |
| 2. Playing With The Data.vtt |
17.90KB |
| 2. Pre-Req For Gradient Descent Part2.mp4 |
32.90MB |
| 2. Pre-Req For Gradient Descent Part2.vtt |
8.96KB |
| 2. Probability Theory.mp4 |
54.79MB |
| 2. Probability Theory.vtt |
13.87KB |
| 2. Seaborn.mp4 |
184.74MB |
| 2. Seaborn.vtt |
26.01KB |
| 2. Segmentation.mp4 |
28.65MB |
| 2. Segmentation.vtt |
8.70KB |
| 2. Series.mp4 |
61.49MB |
| 2. Series.vtt |
9.58KB |
| 2. Sigmoid Function.mp4 |
44.31MB |
| 2. Sigmoid Function.vtt |
11.63KB |
| 2. Types of Machine Learning.mp4 |
35.38MB |
| 2. Types of Machine Learning.vtt |
9.00KB |
| 20. Building Machine Learning model part5.mp4 |
41.94MB |
| 20. Building Machine Learning model part5.vtt |
5.09KB |
| 20. Comprehentions.mp4 |
70.54MB |
| 20. Comprehentions.vtt |
8.08KB |
| 21. Building Machine Learning model part6.mp4 |
50.82MB |
| 21. Building Machine Learning model part6.vtt |
9.10KB |
| 3.1 Python-code-udemy.zip.zip |
16.42KB |
| 3.2 Installing-Python.Teclov.pdf.pdf |
1.37MB |
| 3. Advantages.mp4 |
14.87MB |
| 3. Advantages.vtt |
5.07KB |
| 3. Building Model Part1.mp4 |
55.07MB |
| 3. Building Model Part1.vtt |
5.84KB |
| 3. Case Study.mp4 |
113.20MB |
| 3. Case Study.vtt |
12.91KB |
| 3. Case Study part2.mp4 |
98.41MB |
| 3. Case Study part2.vtt |
12.18KB |
| 3. Cost Functions.mp4 |
13.16MB |
| 3. Cost Functions.vtt |
2.83KB |
| 3. DataFrame.mp4 |
66.19MB |
| 3. DataFrame.vtt |
9.32KB |
| 3. Data Sourcing and Cleaning part2.mp4 |
15.62MB |
| 3. Data Sourcing and Cleaning part2.vtt |
2.53KB |
| 3. Example Part2.mp4 |
45.11MB |
| 3. Example Part2.vtt |
10.74KB |
| 3. Examples.mp4 |
27.75MB |
| 3. Examples.vtt |
6.68KB |
| 3. Gridsearch Case study Part1.mp4 |
124.24MB |
| 3. Gridsearch Case study Part1.vtt |
13.48KB |
| 3. History.mp4 |
61.86MB |
| 3. History.vtt |
17.97KB |
| 3. Homogenity.mp4 |
20.61MB |
| 3. Homogenity.vtt |
5.84KB |
| 3. Hyperplane Part2.mp4 |
65.32MB |
| 3. Hyperplane Part2.vtt |
16.77KB |
| 3. Installation of Python and Anaconda.mp4 |
82.29MB |
| 3. Installation of Python and Anaconda.vtt |
11.12KB |
| 3. Introduction to KNN.mp4 |
47.13MB |
| 3. Introduction to KNN.vtt |
13.69KB |
| 3. Introduction to Linear Regression (LR).mp4 |
17.88MB |
| 3. Introduction to Linear Regression (LR).vtt |
2.97KB |
| 3. Kmeans.mp4 |
57.71MB |
| 3. Kmeans.vtt |
10.13KB |
| 3. Linear Algebra Matrix Part2.mp4 |
77.99MB |
| 3. Linear Algebra Matrix Part2.vtt |
19.40KB |
| 3. Log Odds.mp4 |
41.83MB |
| 3. Log Odds.vtt |
10.91KB |
| 3. Maths Behind PCA.mp4 |
96.82MB |
| 3. Maths Behind PCA.vtt |
25.52KB |
| 3. Model Selection Part3.mp4 |
35.66MB |
| 3. Numpy Operations Part2.mp4 |
169.97MB |
| 3. Numpy Operations Part2.vtt |
29.79KB |
| 3. Performance Metrics Part3.mp4 |
24.02MB |
| 3. Performance Metrics Part3.vtt |
6.24KB |
| 3. Practical Example from NB with One Column.mp4 |
80.59MB |
| 3. Practical Example from NB with One Column.vtt |
10.68KB |
| 3. Probability Distribution.mp4 |
24.24MB |
| 3. Probability Distribution.vtt |
5.47KB |
| 3. Translating the Problem In Machine Learning World.mp4 |
113.02MB |
| 3. Translating the Problem In Machine Learning World.vtt |
11.88KB |
| 4.1 Python-code-udemy.zip.zip |
16.42KB |
| 4. Accuracy of KNN.mp4 |
57.16MB |
| 4. Accuracy of KNN.vtt |
14.85KB |
| 4. Building Model Part2.mp4 |
87.80MB |
| 4. Building Model Part2.vtt |
9.31KB |
| 4. Case Study.mp4 |
198.20MB |
| 4. Case Study.vtt |
20.41KB |
| 4. Case Study Part1.mp4 |
45.47MB |
| 4. Case Study Part1.vtt |
6.08KB |
| 4. Case Study part3.mp4 |
68.67MB |
| 4. Case Study part3.vtt |
7.75KB |
| 4. Data Sourcing and Cleaning part3.mp4 |
10.03MB |
| 4. Data Sourcing and Cleaning part3.vtt |
3.37KB |
| 4. Dealing with Text Data.mp4 |
98.05MB |
| 4. Dealing with Text Data.vtt |
9.90KB |
| 4. Defining Cost Functions More Formally.mp4 |
36.51MB |
| 4. Defining Cost Functions More Formally.vtt |
8.59KB |
| 4. Expected Values Part1.mp4 |
24.25MB |
| 4. Expected Values Part1.vtt |
5.52KB |
| 4. Gini Index.mp4 |
44.19MB |
| 4. Gini Index.vtt |
8.88KB |
| 4. Gridsearch Case study Part2.mp4 |
178.88MB |
| 4. Gridsearch Case study Part2.vtt |
18.44KB |
| 4. How LR Works.mp4 |
58.68MB |
| 4. How LR Works.vtt |
9.93KB |
| 4. Linear Algebra Going From 2D to nD Part1.mp4 |
27.71MB |
| 4. Linear Algebra Going From 2D to nD Part1.vtt |
9.94KB |
| 4. Maths Behind Kmeans.mp4 |
53.75MB |
| 4. Maths Behind Kmeans.vtt |
13.18KB |
| 4. Maths Behind SVM.mp4 |
24.04MB |
| 4. Maths Behind SVM.vtt |
8.15KB |
| 4. OneTwo Tailed Tests.mp4 |
38.00MB |
| 4. OneTwo Tailed Tests.vtt |
10.14KB |
| 4. Operations Part1.mp4 |
12.02MB |
| 4. Operations Part1.vtt |
1.44KB |
| 4. Optimal Solution.mp4 |
65.23MB |
| 4. Optimal Solution.vtt |
16.71KB |
| 4. Perceptron.mp4 |
29.78MB |
| 4. Perceptron.vtt |
8.24KB |
| 4. Practical Example from NB with Multiple Columns.mp4 |
59.83MB |
| 4. Practical Example from NB with Multiple Columns.vtt |
13.16KB |
| 4. Python Introduction.mp4 |
10.25MB |
| 4. Python Introduction.vtt |
3.54KB |
| 4. Runtime.mp4 |
16.38MB |
| 4. Runtime.vtt |
4.66KB |
| 4. Seaborn On Time Series Data.mp4 |
54.06MB |
| 4. Seaborn On Time Series Data.vtt |
5.60KB |
| 5. Adjusted R Square.mp4 |
8.08MB |
| 5. Adjusted R Square.vtt |
855B |
| 5. Building Model Part3.mp4 |
48.52MB |
| 5. Building Model Part3.vtt |
4.65KB |
| 5. Case study.mp4 |
73.09MB |
| 5. Case study.mp4 |
39.97MB |
| 5. Case study.vtt |
6.89KB |
| 5. Case study.vtt |
4.21KB |
| 5. Case Study Part2.mp4 |
123.06MB |
| 5. Case Study Part2.vtt |
18.98KB |
| 5. Critical Value Method.mp4 |
24.71MB |
| 5. Critical Value Method.vtt |
4.55KB |
| 5. Data Sourcing and Cleaning part4.mp4 |
10.37MB |
| 5. Data Sourcing and Cleaning part4.vtt |
3.85KB |
| 5. Effectiveness of KNN.mp4 |
48.23MB |
| 5. Effectiveness of KNN.vtt |
15.86KB |
| 5. Expected Values Part2.mp4 |
14.49MB |
| 5. Expected Values Part2.vtt |
3.87KB |
| 5. Gradient Descent.mp4 |
37.66MB |
| 5. Gradient Descent.vtt |
12.51KB |
| 5. Information Gain Part1.mp4 |
29.29MB |
| 5. Information Gain Part1.vtt |
6.68KB |
| 5. Linear Algebra 2D to nD Part2.mp4 |
25.78MB |
| 5. Linear Algebra 2D to nD Part2.vtt |
8.16KB |
| 5. More Maths.mp4 |
9.43MB |
| 5. More Maths.vtt |
2.91KB |
| 5. Multi Layered Perceptron.mp4 |
63.83MB |
| 5. Multi Layered Perceptron.vtt |
14.50KB |
| 5. Naive Bayes On Text Data Part1.mp4 |
54.74MB |
| 5. Naive Bayes On Text Data Part1.vtt |
9.99KB |
| 5. Operations Part2.mp4 |
44.10MB |
| 5. Operations Part2.vtt |
6.10KB |
| 5. Some Fun With Maths Behind LR.mp4 |
52.75MB |
| 5. Some Fun With Maths Behind LR.vtt |
10.98KB |
| 5. Support Vectors.mp4 |
11.04MB |
| 5. Support Vectors.vtt |
3.95KB |
| 5. Train, Test And Cross Validation Split.mp4 |
116.21MB |
| 5. Train, Test And Cross Validation Split.vtt |
12.27KB |
| 5. Variables in Python.mp4 |
110.46MB |
| 5. Variables in Python.vtt |
20.73KB |
| 6. Case Study Part1.mp4 |
68.55MB |
| 6. Case Study Part1.vtt |
8.83KB |
| 6. Data Sourcing and Cleaning part5.mp4 |
12.41MB |
| 6. Data Sourcing and Cleaning part5.vtt |
3.73KB |
| 6. Distance Metrics.mp4 |
47.90MB |
| 6. Distance Metrics.vtt |
14.65KB |
| 6. Indexes.mp4 |
50.11MB |
| 6. Indexes.vtt |
7.44KB |
| 6. Information Gain Part2.mp4 |
27.37MB |
| 6. Information Gain Part2.vtt |
5.65KB |
| 6. Introduction to Boosting.mp4 |
33.05MB |
| 6. Introduction to Boosting.vtt |
6.47KB |
| 6. Kmeans plus.mp4 |
51.78MB |
| 6. Kmeans plus.vtt |
11.43KB |
| 6. Naive Bayes On Text Data Part2.mp4 |
46.06MB |
| 6. Naive Bayes On Text Data Part2.vtt |
6.58KB |
| 6. Neural Network Playground.mp4 |
103.70MB |
| 6. Neural Network Playground.vtt |
13.60KB |
| 6. Numeric Operations in Python.mp4 |
36.92MB |
| 6. Numeric Operations in Python.vtt |
7.14KB |
| 6. Optimisation.mp4 |
21.68MB |
| 6. Optimisation.vtt |
5.06KB |
| 6. Regularization.mp4 |
48.60MB |
| 6. Regularization.vtt |
10.32KB |
| 6. R Square.mp4 |
52.47MB |
| 6. R Square.vtt |
12.33KB |
| 6. Slack Variable.mp4 |
33.27MB |
| 6. Slack Variable.vtt |
10.22KB |
| 6. Understanding Evaluation Matrix Log Loss.mp4 |
85.50MB |
| 6. Understanding Evaluation Matrix Log Loss.vtt |
19.98KB |
| 6. Verification of Model.mp4 |
39.49MB |
| 6. Verification of Model.vtt |
4.74KB |
| 6. Without Experiment.mp4 |
28.68MB |
| 6. Without Experiment.vtt |
7.20KB |
| 6. z Table.mp4 |
58.63MB |
| 6. z Table.vtt |
8.80KB |
| 7. Advantages and Disadvantages of DT.mp4 |
15.45MB |
| 7. Advantages and Disadvantages of DT.vtt |
4.43KB |
| 7. Binomial Distribution.mp4 |
17.58MB |
| 7. Binomial Distribution.vtt |
4.21KB |
| 7. Building A Worst Model.mp4 |
68.49MB |
| 7. Building A Worst Model.vtt |
10.66KB |
| 7. Case Study Part2.mp4 |
72.90MB |
| 7. Case Study Part2.vtt |
12.31KB |
| 7. Closed Form Vs Gradient Descent.mp4 |
26.61MB |
| 7. Closed Form Vs Gradient Descent.vtt |
5.77KB |
| 7. Data Sourcing and Cleaning part6.mp4 |
53.70MB |
| 7. Data Sourcing and Cleaning part6.vtt |
4.36KB |
| 7. Distance Metrics Part2.mp4 |
28.83MB |
| 7. Distance Metrics Part2.vtt |
9.26KB |
| 7. Examples.mp4 |
26.42MB |
| 7. Examples.vtt |
3.55KB |
| 7. Laplace Smoothing.mp4 |
55.26MB |
| 7. Laplace Smoothing.vtt |
4.94KB |
| 7. loc and iloc.mp4 |
59.37MB |
| 7. loc and iloc.vtt |
9.34KB |
| 7. Logical Operations.mp4 |
17.32MB |
| 7. Logical Operations.vtt |
3.22KB |
| 7. LR Case Study Part1.mp4 |
137.50MB |
| 7. LR Case Study Part1.vtt |
17.46KB |
| 7. Ridge and Lasso.mp4 |
39.95MB |
| 7. Ridge and Lasso.vtt |
7.70KB |
| 7. SVM Case Study Part1.mp4 |
74.15MB |
| 7. SVM Case Study Part1.vtt |
6.49KB |
| 7. Value of K.mp4 |
35.82MB |
| 7. Value of K.vtt |
7.62KB |
| 7. Weak Learners.mp4 |
17.90MB |
| 7. Weak Learners.vtt |
3.11KB |
| 8. Bernoulli Naive Bayes.mp4 |
27.11MB |
| 8. Bernoulli Naive Bayes.vtt |
2.04KB |
| 8. Case Study.mp4 |
106.22MB |
| 8. Case Study.vtt |
10.68KB |
| 8. Case Study Part3.mp4 |
66.56MB |
| 8. Case Study Part3.vtt |
7.65KB |
| 8. Commulative Distribution.mp4 |
8.37MB |
| 8. Commulative Distribution.vtt |
2.72KB |
| 8. Data Cleaning part1.mp4 |
76.24MB |
| 8. Data Cleaning part1.vtt |
16.71KB |
| 8. Evaluating Worst ML Model.mp4 |
58.87MB |
| 8. Evaluating Worst ML Model.vtt |
7.07KB |
| 8. Finding k.mp4 |
33.32MB |
| 8. Finding k.vtt |
11.49KB |
| 8. Gradient Descent case study.mp4 |
71.66MB |
| 8. Gradient Descent case study.vtt |
6.85KB |
| 8. Hopkins test.mp4 |
12.27MB |
| 8. Hopkins test.vtt |
3.02KB |
| 8. If else Loop.mp4 |
64.01MB |
| 8. If else Loop.vtt |
10.03KB |
| 8. LR Case Study Part2.mp4 |
53.38MB |
| 8. LR Case Study Part2.vtt |
5.44KB |
| 8. More Examples.mp4 |
16.47MB |
| 8. More Examples.vtt |
3.38KB |
| 8. Preventing Overfitting Issues in DT.mp4 |
40.29MB |
| 8. Preventing Overfitting Issues in DT.vtt |
11.77KB |
| 8. Reading CSV.mp4 |
42.47MB |
| 8. Reading CSV.vtt |
6.93KB |
| 8. Shallow Decision Tree.mp4 |
14.96MB |
| 8. Shallow Decision Tree.vtt |
2.73KB |
| 8. SVM Case Study Part2.mp4 |
66.16MB |
| 8. SVM Case Study Part2.vtt |
8.41KB |
| 9. Adaboost Part1.mp4 |
41.53MB |
| 9. Adaboost Part1.vtt |
8.25KB |
| 9. Case Study 1.mp4 |
95.46MB |
| 9. Case Study 1.vtt |
10.81KB |
| 9. Case Study Part1.mp4 |
95.82MB |
| 9. Case Study Part1.vtt |
13.18KB |
| 9. Case Study Part4.mp4 |
132.20MB |
| 9. Case Study Part4.vtt |
17.82KB |
| 9. Data Cleaning part2.mp4 |
29.70MB |
| 9. Data Cleaning part2.vtt |
11.04KB |
| 9. DT Case Study Part1.mp4 |
125.45MB |
| 9. DT Case Study Part1.vtt |
12.92KB |
| 9. First Categorical column analysis.mp4 |
71.13MB |
| 9. First Categorical column analysis.vtt |
14.66KB |
| 9. for while Loop.mp4 |
77.78MB |
| 9. for while Loop.vtt |
12.99KB |
| 9. Kernel Part1.mp4 |
49.24MB |
| 9. Kernel Part1.vtt |
9.36KB |
| 9. KNN on Regression.mp4 |
9.28MB |
| 9. KNN on Regression.vtt |
2.92KB |
| 9. LR Case Study Part3.mp4 |
46.44MB |
| 9. LR Case Study Part3.vtt |
5.54KB |
| 9. Merging Part1.mp4 |
30.01MB |
| 9. Merging Part1.vtt |
4.34KB |
| 9. Model Selection.mp4 |
31.30MB |
| 9. Model Selection.vtt |
6.52KB |
| 9. PDF.mp4 |
21.00MB |
| 9. PDF.vtt |
5.42KB |
| 9. p Value.mp4 |
33.48MB |
| 9. p Value.vtt |
6.47KB |