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[FreeTutorials.Eu] Udemy - Machine Learning A-Z Become Kaggle Master
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2019-2-16 19:07
2024-8-18 23:05
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Eu
Udemy
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Machine
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A-Z
Become
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文件列表
10. Multiple Linear Regression/10. Case Study Part5.mp4
45.73MB
10. Multiple Linear Regression/11. Case Study Part6 (RFE).mp4
64.15MB
10. Multiple Linear Regression/1. Introduction.mp4
16.46MB
10. Multiple Linear Regression/2. Case Study part1.mp4
83.04MB
10. Multiple Linear Regression/3. Case Study part2.mp4
98.41MB
10. Multiple Linear Regression/4. Case Study part3.mp4
68.67MB
10. Multiple Linear Regression/5. Adjusted R Square.mp4
8.08MB
10. Multiple Linear Regression/6. Case Study Part1.mp4
68.55MB
10. Multiple Linear Regression/7. Case Study Part2.mp4
72.9MB
10. Multiple Linear Regression/8. Case Study Part3.mp4
66.56MB
10. Multiple Linear Regression/9. Case Study Part4.mp4
132.2MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/1. Introduction to the Problem Statement.mp4
40.85MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/2. Playing With Data.mp4
81.36MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/3. Building Model Part1.mp4
55.07MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/4. Building Model Part2.mp4
87.8MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/5. Building Model Part3.mp4
48.52MB
11. HotstarNetflix Real world Case Study for Multiple Linear Regression/6. Verification of Model.mp4
39.49MB
12. Gradient Descent/1. Pre-Req For Gradient Descent Part1.mp4
61.24MB
12. Gradient Descent/2. Pre-Req For Gradient Descent Part2.mp4
32.9MB
12. Gradient Descent/3. Cost Functions.mp4
13.16MB
12. Gradient Descent/4. Defining Cost Functions More Formally.mp4
36.51MB
12. Gradient Descent/5. Gradient Descent.mp4
37.66MB
12. Gradient Descent/6. Optimisation.mp4
21.68MB
12. Gradient Descent/7. Closed Form Vs Gradient Descent.mp4
26.61MB
12. Gradient Descent/8. Gradient Descent case study.mp4
71.66MB
13. KNN/10. Case Study.mp4
70.71MB
13. KNN/11. Classification Case1.mp4
84.22MB
13. KNN/12. Classification Case2.mp4
52.23MB
13. KNN/13. Classification Case3.mp4
52.97MB
13. KNN/14. Classification Case4.mp4
41.1MB
13. KNN/1. Introduction to Classification.mp4
54.11MB
13. KNN/2. Defining Classification Mathematically.mp4
39.99MB
13. KNN/3. Introduction to KNN.mp4
47.13MB
13. KNN/4. Accuracy of KNN.mp4
57.16MB
13. KNN/5. Effectiveness of KNN.mp4
48.23MB
13. KNN/6. Distance Metrics.mp4
47.9MB
13. KNN/7. Distance Metrics Part2.mp4
28.83MB
13. KNN/8. Finding k.mp4
33.32MB
13. KNN/9. KNN on Regression.mp4
9.28MB
14. Model Performance Metrics/1. Performance Metrics Part1.mp4
113.83MB
14. Model Performance Metrics/2. Performance Metrics Part2.mp4
90.48MB
14. Model Performance Metrics/3. Performance Metrics Part3.mp4
24.02MB
15. Model Selection Part1/1. Model Creation Case1.mp4
52.09MB
15. Model Selection Part1/2. Model Creation Case2.mp4
34.67MB
15. Model Selection Part1/3. Gridsearch Case study Part1.mp4
124.24MB
15. Model Selection Part1/4. Gridsearch Case study Part2.mp4
178.88MB
16. Naive Bayes/10. Case Study 2 Part1.mp4
74.57MB
16. Naive Bayes/11. Case Study 2 Part2.mp4
25.35MB
16. Naive Bayes/1. Introduction to Naive Bayes.mp4
73.37MB
16. Naive Bayes/2. Bayes Theorem.mp4
63.05MB
16. Naive Bayes/3. Practical Example from NB with One Column.mp4
80.59MB
16. Naive Bayes/4. Practical Example from NB with Multiple Columns.mp4
59.83MB
16. Naive Bayes/5. Naive Bayes On Text Data Part1.mp4
54.74MB
16. Naive Bayes/6. Naive Bayes On Text Data Part2.mp4
46.06MB
16. Naive Bayes/7. Laplace Smoothing.mp4
55.26MB
16. Naive Bayes/8. Bernoulli Naive Bayes.mp4
27.11MB
16. Naive Bayes/9. Case Study 1.mp4
95.46MB
17. Logistic Regression/1. Introduction.mp4
26.6MB
17. Logistic Regression/2. Sigmoid Function.mp4
44.31MB
17. Logistic Regression/3. Log Odds.mp4
41.83MB
17. Logistic Regression/4. Case Study.mp4
198.2MB
18. Support Vector Machine (SVM)/10. Kernel Part2.mp4
71.13MB
18. Support Vector Machine (SVM)/11. Case Study 2.mp4
90MB
18. Support Vector Machine (SVM)/12. Case Study 3 Part1.mp4
56.01MB
18. Support Vector Machine (SVM)/13. Case Study 3 Part2.mp4
61.28MB
18. Support Vector Machine (SVM)/14. Case Study 4.mp4
164.41MB
18. Support Vector Machine (SVM)/1. Introduction.mp4
58.71MB
18. Support Vector Machine (SVM)/2. Hyperplane Part1.mp4
27.07MB
18. Support Vector Machine (SVM)/3. Hyperplane Part2.mp4
65.32MB
18. Support Vector Machine (SVM)/4. Maths Behind SVM.mp4
24.04MB
18. Support Vector Machine (SVM)/5. Support Vectors.mp4
11.04MB
18. Support Vector Machine (SVM)/6. Slack Variable.mp4
33.27MB
18. Support Vector Machine (SVM)/7. SVM Case Study Part1.mp4
74.15MB
18. Support Vector Machine (SVM)/8. SVM Case Study Part2.mp4
66.16MB
18. Support Vector Machine (SVM)/9. Kernel Part1.mp4
49.24MB
19. Decision Tree/10. DT Case Study Part2.mp4
95.71MB
19. Decision Tree/1. Introduction.mp4
29.78MB
19. Decision Tree/2. Example of DT.mp4
40.59MB
19. Decision Tree/3. Homogenity.mp4
20.61MB
19. Decision Tree/4. Gini Index.mp4
44.19MB
19. Decision Tree/5. Information Gain Part1.mp4
29.29MB
19. Decision Tree/6. Information Gain Part2.mp4
27.37MB
19. Decision Tree/7. Advantages and Disadvantages of DT.mp4
15.45MB
19. Decision Tree/8. Preventing Overfitting Issues in DT.mp4
40.29MB
19. Decision Tree/9. DT Case Study Part1.mp4
125.45MB
1. Python Fundamentals/10. Functions.mp4
85.62MB
1. Python Fundamentals/11. String Part1.mp4
106.01MB
1. Python Fundamentals/12. String Part2.mp4
27.38MB
1. Python Fundamentals/13. List Part1.mp4
10.04MB
1. Python Fundamentals/14. List Part2.mp4
87.32MB
1. Python Fundamentals/15. List Part3.mp4
73.56MB
1. Python Fundamentals/16. List Part4.mp4
63.85MB
1. Python Fundamentals/17. Tuples.mp4
67.33MB
1. Python Fundamentals/18. Sets.mp4
58.16MB
1. Python Fundamentals/19. Dictionaries.mp4
61.6MB
1. Python Fundamentals/1. Introduction to the course.mp4
93.85MB
1. Python Fundamentals/20. Comprehentions.mp4
70.54MB
1. Python Fundamentals/2. Introduction to Kaggle.mp4
90.07MB
1. Python Fundamentals/3. Installation of Python and Anaconda.mp4
82.29MB
1. Python Fundamentals/4. Python Introduction.mp4
10.25MB
1. Python Fundamentals/5. Variables in Python.mp4
110.46MB
1. Python Fundamentals/6. Numeric Operations in Python.mp4
36.92MB
1. Python Fundamentals/7. Logical Operations.mp4
17.32MB
1. Python Fundamentals/8. If else Loop.mp4
64.01MB
1. Python Fundamentals/9. for while Loop.mp4
77.78MB
20. Ensembling/10. Adaboost Part2.mp4
38.46MB
20. Ensembling/11. Adaboost Case Study.mp4
53.65MB
20. Ensembling/12. XGBoost.mp4
23.11MB
20. Ensembling/13. Boosting Part1.mp4
13.69MB
20. Ensembling/14. Boosting Part2.mp4
35.51MB
20. Ensembling/15. XGboost Algorithm.mp4
38.76MB
20. Ensembling/16. Case Study Part1.mp4
141.54MB
20. Ensembling/17. Case Study Part2.mp4
136.7MB
20. Ensembling/18. Case Study Part3.mp4
75.43MB
20. Ensembling/1. Introduction to Ensembles.mp4
39.28MB
20. Ensembling/2. Bagging.mp4
71.21MB
20. Ensembling/3. Advantages.mp4
14.87MB
20. Ensembling/4. Runtime.mp4
16.38MB
20. Ensembling/5. Case study.mp4
73.09MB
20. Ensembling/6. Introduction to Boosting.mp4
33.05MB
20. Ensembling/7. Weak Learners.mp4
17.9MB
20. Ensembling/8. Shallow Decision Tree.mp4
14.96MB
20. Ensembling/9. Adaboost Part1.mp4
41.53MB
21. Model Selection Part2/1. Model Selection Part1.mp4
104.3MB
21. Model Selection Part2/2. Model Selection Part2.mp4
41.33MB
21. Model Selection Part2/3. Model Selection Part3.mp4
35.66MB
22. Unsupervised Learning/10. Case Study Part2.mp4
61.33MB
22. Unsupervised Learning/11. More on Segmentation.mp4
18.06MB
22. Unsupervised Learning/12. Hierarchial Clustering.mp4
38.02MB
22. Unsupervised Learning/13. Case Study.mp4
34.4MB
22. Unsupervised Learning/1. Introduction to Clustering.mp4
59.13MB
22. Unsupervised Learning/2. Segmentation.mp4
28.65MB
22. Unsupervised Learning/3. Kmeans.mp4
57.71MB
22. Unsupervised Learning/4. Maths Behind Kmeans.mp4
53.75MB
22. Unsupervised Learning/5. More Maths.mp4
9.43MB
22. Unsupervised Learning/6. Kmeans plus.mp4
51.78MB
22. Unsupervised Learning/7. Value of K.mp4
35.82MB
22. Unsupervised Learning/8. Hopkins test.mp4
12.27MB
22. Unsupervised Learning/9. Case Study Part1.mp4
95.82MB
23. Dimension Reduction/1. Introduction.mp4
156.68MB
23. Dimension Reduction/2. PCA.mp4
98.39MB
23. Dimension Reduction/3. Maths Behind PCA.mp4
96.82MB
23. Dimension Reduction/4. Case Study Part1.mp4
45.47MB
23. Dimension Reduction/5. Case Study Part2.mp4
123.06MB
24. Advanced Machine Learning Algorithms/10. Adjusted R Square.mp4
20.13MB
24. Advanced Machine Learning Algorithms/1. Introduction.mp4
30.94MB
24. Advanced Machine Learning Algorithms/2. Example Part1.mp4
27.48MB
24. Advanced Machine Learning Algorithms/3. Example Part2.mp4
45.11MB
24. Advanced Machine Learning Algorithms/4. Optimal Solution.mp4
65.23MB
24. Advanced Machine Learning Algorithms/5. Case study.mp4
39.97MB
24. Advanced Machine Learning Algorithms/6. Regularization.mp4
48.6MB
24. Advanced Machine Learning Algorithms/7. Ridge and Lasso.mp4
39.95MB
24. Advanced Machine Learning Algorithms/8. Case Study.mp4
106.22MB
24. Advanced Machine Learning Algorithms/9. Model Selection.mp4
31.3MB
25. Deep Learning/1. Expectations.mp4
9.36MB
25. Deep Learning/2. Introduction.mp4
48.76MB
25. Deep Learning/3. History.mp4
61.86MB
25. Deep Learning/4. Perceptron.mp4
29.78MB
25. Deep Learning/5. Multi Layered Perceptron.mp4
63.83MB
25. Deep Learning/6. Neural Network Playground.mp4
103.7MB
26. Project Kaggle/10. Response encoding and one hot encoder.mp4
54.68MB
26. Project Kaggle/11. Laplace Smoothing and Calibrated classifier.mp4
48.25MB
26. Project Kaggle/12. Significance of first categorical column.mp4
71.74MB
26. Project Kaggle/13. Second Categorical column.mp4
45.7MB
26. Project Kaggle/14. Third Categorical column.mp4
66.72MB
26. Project Kaggle/15. Data pre-processing before building machine learning model.mp4
50.59MB
26. Project Kaggle/16. Building Machine Learning model part1.mp4
124.01MB
26. Project Kaggle/17. Building Machine Learning model part2.mp4
135.18MB
26. Project Kaggle/18. Building Machine Learning model part3.mp4
38.41MB
26. Project Kaggle/19. Building Machine Learning model part4.mp4
33.07MB
26. Project Kaggle/1. Introduction to the Problem Statement.mp4
93.36MB
26. Project Kaggle/20. Building Machine Learning model part5.mp4
41.94MB
26. Project Kaggle/21. Building Machine Learning model part6.mp4
50.82MB
26. Project Kaggle/2. Playing With The Data.mp4
137.05MB
26. Project Kaggle/3. Translating the Problem In Machine Learning World.mp4
113.02MB
26. Project Kaggle/4. Dealing with Text Data.mp4
98.05MB
26. Project Kaggle/5. Train, Test And Cross Validation Split.mp4
116.21MB
26. Project Kaggle/6. Understanding Evaluation Matrix Log Loss.mp4
85.5MB
26. Project Kaggle/7. Building A Worst Model.mp4
68.49MB
26. Project Kaggle/8. Evaluating Worst ML Model.mp4
58.87MB
26. Project Kaggle/9. First Categorical column analysis.mp4
71.13MB
2. Numpy/1. Introduction.mp4
24.74MB
2. Numpy/2. Numpy Operations Part1.mp4
128.75MB
2. Numpy/3. Numpy Operations Part2.mp4
169.97MB
3. Pandas/10. groupby.mp4
46.92MB
3. Pandas/11. Merging Part2.mp4
33.9MB
3. Pandas/12. Pivot Table.mp4
27.7MB
3. Pandas/1. Introduction.mp4
39.1MB
3. Pandas/2. Series.mp4
61.49MB
3. Pandas/3. DataFrame.mp4
66.19MB
3. Pandas/4. Operations Part1.mp4
12.02MB
3. Pandas/5. Operations Part2.mp4
44.1MB
3. Pandas/6. Indexes.mp4
50.11MB
3. Pandas/7. loc and iloc.mp4
59.37MB
3. Pandas/8. Reading CSV.mp4
42.47MB
3. Pandas/9. Merging Part1.mp4
30.01MB
4. Some Fun With Maths/1. Linear Algebra Vectors.mp4
162.41MB
4. Some Fun With Maths/2. Linear Algebra Matrix Part1.mp4
95.26MB
4. Some Fun With Maths/3. Linear Algebra Matrix Part2.mp4
77.99MB
4. Some Fun With Maths/4. Linear Algebra Going From 2D to nD Part1.mp4
27.71MB
4. Some Fun With Maths/5. Linear Algebra 2D to nD Part2.mp4
25.78MB
5. Inferential Statistics/10. Normal Distribution.mp4
19.02MB
5. Inferential Statistics/11. z Score.mp4
23.8MB
5. Inferential Statistics/12. Sampling.mp4
38.73MB
5. Inferential Statistics/13. Sampling Distribution.mp4
25.51MB
5. Inferential Statistics/14. Central Limit Theorem.mp4
13.1MB
5. Inferential Statistics/15. Confidence Interval Part1.mp4
34.55MB
5. Inferential Statistics/16. Confidence Interval Part2.mp4
13.39MB
5. Inferential Statistics/1. Inferential Statistics.mp4
10.31MB
5. Inferential Statistics/2. Probability Theory.mp4
54.79MB
5. Inferential Statistics/3. Probability Distribution.mp4
24.24MB
5. Inferential Statistics/4. Expected Values Part1.mp4
24.25MB
5. Inferential Statistics/5. Expected Values Part2.mp4
14.49MB
5. Inferential Statistics/6. Without Experiment.mp4
28.68MB
5. Inferential Statistics/7. Binomial Distribution.mp4
17.58MB
5. Inferential Statistics/8. Commulative Distribution.mp4
8.37MB
5. Inferential Statistics/9. PDF.mp4
21MB
6. Hypothesis Testing/10. Types of Error.mp4
15.3MB
6. Hypothesis Testing/11. t- distribution Part1.mp4
21.31MB
6. Hypothesis Testing/12. t- distribution Part2.mp4
29.32MB
6. Hypothesis Testing/1. Introduction.mp4
31.09MB
6. Hypothesis Testing/2. NULL And Alternate Hypothesis.mp4
28.79MB
6. Hypothesis Testing/3. Examples.mp4
27.75MB
6. Hypothesis Testing/4. OneTwo Tailed Tests.mp4
38MB
6. Hypothesis Testing/5. Critical Value Method.mp4
24.71MB
6. Hypothesis Testing/6. z Table.mp4
58.63MB
6. Hypothesis Testing/7. Examples.mp4
26.42MB
6. Hypothesis Testing/8. More Examples.mp4
16.47MB
6. Hypothesis Testing/9. p Value.mp4
33.48MB
7. Data Visualisation/1. Matplotlib.mp4
172.76MB
7. Data Visualisation/2. Seaborn.mp4
184.74MB
7. Data Visualisation/3. Case Study.mp4
113.2MB
7. Data Visualisation/4. Seaborn On Time Series Data.mp4
54.06MB
8. Exploratory Data Analysis/10. Univariate Analysis Part1.mp4
82.78MB
8. Exploratory Data Analysis/11. Univariate Analysis Part2.mp4
60.85MB
8. Exploratory Data Analysis/12. Segmented Analysis.mp4
24.47MB
8. Exploratory Data Analysis/13. Bivariate Analysis.mp4
60.6MB
8. Exploratory Data Analysis/14. Derived Columns.mp4
41.89MB
8. Exploratory Data Analysis/1. Introduction.mp4
3.79MB
8. Exploratory Data Analysis/2. Data Sourcing and Cleaning part1.mp4
15.56MB
8. Exploratory Data Analysis/3. Data Sourcing and Cleaning part2.mp4
15.62MB
8. Exploratory Data Analysis/4. Data Sourcing and Cleaning part3.mp4
10.03MB
8. Exploratory Data Analysis/5. Data Sourcing and Cleaning part4.mp4
10.37MB
8. Exploratory Data Analysis/6. Data Sourcing and Cleaning part5.mp4
12.41MB
8. Exploratory Data Analysis/7. Data Sourcing and Cleaning part6.mp4
53.7MB
8. Exploratory Data Analysis/8. Data Cleaning part1.mp4
76.24MB
8. Exploratory Data Analysis/9. Data Cleaning part2.mp4
29.7MB
9. Simple Linear Regression/10. Residual Square Error (RSE).mp4
4.55MB
9. Simple Linear Regression/1. Introduction to Machine Learning.mp4
11.16MB
9. Simple Linear Regression/2. Types of Machine Learning.mp4
35.38MB
9. Simple Linear Regression/3. Introduction to Linear Regression (LR).mp4
17.88MB
9. Simple Linear Regression/4. How LR Works.mp4
58.68MB
9. Simple Linear Regression/5. Some Fun With Maths Behind LR.mp4
52.75MB
9. Simple Linear Regression/6. R Square.mp4
52.47MB
9. Simple Linear Regression/7. LR Case Study Part1.mp4
137.5MB
9. Simple Linear Regression/8. LR Case Study Part2.mp4
53.38MB
9. Simple Linear Regression/9. LR Case Study Part3.mp4
46.44MB
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