FreeCourseSite com Udemy Machine Learning and Data Science Hands on with Python and

FreeCourseSite com Udemy Machine Learning and Data Science Hands on with Python and

Name	[FreeCourseSite.com] Udemy - Machine Learning and Data Science Hands-on with Python and R	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	33.1 GB
Total Files	1047
Last Seen	2025-07-18 23:36
Hash	1FEF239CF341E6D4EFB6A9BB7F966EC38DEAC2B6

/1. Machine Learning - Statistics Essentials/
1. Machine Learning Introduction.mp4	21.0 MB
1. Machine Learning Introduction.vtt	4.5 KB
10. Technical Terminology.mp4	57.5 MB
10. Technical Terminology.vtt	11.3 KB
11. Error of Observation and Non Observation.mp4	32.7 MB
11. Error of Observation and Non Observation.vtt	32.7 MB
12. Systematic Sampling.mp4	57.6 MB
12. Systematic Sampling.vtt	8.1 KB
13. Cluster Sampling.mp4	61.6 MB
13. Cluster Sampling.vtt	10.2 KB
14. Statistics Data Types.mp4	26.8 MB
14. Statistics Data Types.vtt	26.8 MB
15. Qualitative Data and Visualization.mp4	39.5 MB
15. Qualitative Data and Visualization.vtt	8.3 KB
16. Machine Learning.mp4	58.8 MB
16. Machine Learning.vtt	8.7 KB
17. Relative Frequency Probability.mp4	66.0 MB
17. Relative Frequency Probability.vtt	9.4 KB
18. Joint Probability.mp4	90.1 MB
18. Joint Probability.vtt	10.0 KB
19. Conditional Probability.mp4	44.9 MB
19. Conditional Probability.vtt	8.3 KB
2. Introduction to Machine Learning with Python.mp4	6.8 MB
2. Introduction to Machine Learning with Python.vtt	3.4 KB
20. Concept of Independence.mp4	42.3 MB
20. Concept of Independence.vtt	5.9 KB
21. Total Probability.mp4	60.5 MB
21. Total Probability.vtt	9.5 KB
22. Random Variable.mp4	49.0 MB
22. Random Variable.vtt	8.5 KB
23. Probability Distribution.mp4	72.1 MB
23. Probability Distribution.vtt	10.7 KB
24. Cumulative Probability Distribution.mp4	39.4 MB
24. Cumulative Probability Distribution.vtt	8.9 KB
25. Bernoulli Distribution.mp4	40.6 MB
25. Bernoulli Distribution.vtt	8.4 KB
26. Gaussian Distribution.mp4	35.3 MB
26. Gaussian Distribution.vtt	8.2 KB
27. Geometric Distribution.mp4	34.8 MB
27. Geometric Distribution.vtt	7.4 KB
28. Continuous and Normal Distribution.mp4	51.5 MB
28. Continuous and Normal Distribution.vtt	9.8 KB
29. Mathematical Expression and Computation.mp4	35.5 MB
29. Mathematical Expression and Computation.vtt	8.9 KB
3. Analytics in Machine Learning.mp4	49.3 MB
3. Analytics in Machine Learning.vtt	8.7 KB
30. Transpose of Matrix.mp4	48.3 MB
30. Transpose of Matrix.vtt	8.6 KB
31. Properties of Matrix.mp4	50.0 MB
31. Properties of Matrix.vtt	11.9 KB
32. Determinants.mp4	50.0 MB
32. Determinants.vtt	8.8 KB
33. Error Types.mp4	55.8 MB
33. Error Types.vtt	8.5 KB
34. Critical Value Approach.mp4	59.9 MB
34. Critical Value Approach.vtt	7.8 KB
35. Right and Left Sided Critical Approach.mp4	62.1 MB
35. Right and Left Sided Critical Approach.vtt	9.6 KB
36. P-Value Approach.mp4	83.7 MB
36. P-Value Approach.vtt	9.0 KB
37. P-Value Approach Continues.mp4	58.5 MB
37. P-Value Approach Continues.vtt	8.0 KB
38. Hypothesis Testing.mp4	45.6 MB
38. Hypothesis Testing.vtt	9.5 KB
39. Left Tail Test.mp4	24.0 MB
39. Left Tail Test.vtt	4.8 KB
4. Big Data Machine Learning.mp4	53.5 MB
4. Big Data Machine Learning.vtt	7.4 KB
40. Two Tail Test.mp4	43.7 MB
40. Two Tail Test.vtt	9.0 KB
41. Confidence Interval.mp4	55.2 MB
41. Confidence Interval.vtt	8.3 KB
42. Example of Confidence Interval.mp4	66.0 MB
42. Example of Confidence Interval.vtt	10.6 KB
43. Normal and Non Normal Distribution.mp4	34.0 MB
43. Normal and Non Normal Distribution.vtt	9.3 KB
44. Normality Test.mp4	47.9 MB
44. Normality Test.vtt	8.9 KB
45. Normality Test Continues.mp4	43.0 MB
45. Normality Test Continues.vtt	9.2 KB
46. Determining the Transformation.mp4	23.2 MB
46. Determining the Transformation.vtt	5.8 KB
47. T-Test.mp4	47.4 MB
47. T-Test.vtt	9.9 KB
48. T-Test Continue.mp4	49.5 MB
48. T-Test Continue.vtt	7.3 KB
49. More on T-Test.mp4	58.2 MB
49. More on T-Test.vtt	8.8 KB
5. Emerging Trends Machine Learning.mp4	75.9 MB
5. Emerging Trends Machine Learning.vtt	8.0 KB
50. Test of Independence.mp4	56.6 MB
50. Test of Independence.vtt	10.6 KB
51. Example of Test of Independence.mp4	53.6 MB
51. Example of Test of Independence.vtt	9.4 KB
52. Goodness of Fit Test.mp4	42.2 MB
52. Goodness of Fit Test.vtt	6.6 KB
53. Example of Goodness of Fit Test.mp4	39.8 MB
53. Example of Goodness of Fit Test.vtt	6.9 KB
54. Co-Variance.mp4	18.9 MB
54. Co-Variance.vtt	5.1 KB
55. Co-Variance Continues.mp4	25.2 MB
55. Co-Variance Continues.vtt	7.5 KB
6. Data Mining.mp4	45.9 MB
6. Data Mining.vtt	8.1 KB
7. Data Mining Continues.mp4	71.0 MB
7. Data Mining Continues.vtt	7.0 KB
8. Supervised and Unsupervised.mp4	47.6 MB
8. Supervised and Unsupervised.vtt	7.6 KB
9. Sampling Method in Machine Learning.mp4	32.6 MB
9. Sampling Method in Machine Learning.vtt	7.6 KB
/10. Natural Language Processing (NLP) Tutorials/
1. Intoroduction to NLP.mp4	34.3 MB
1. Intoroduction to NLP.vtt	7.4 KB
10. Stemming and Lemmatization Continues.mp4	64.2 MB
10. Stemming and Lemmatization Continues.vtt	7.5 KB
11. Convert Token No Stopwords.mp4	65.7 MB
11. Convert Token No Stopwords.vtt	5.9 KB
12. Machine Learning Algorithms.mp4	62.9 MB
12. Machine Learning Algorithms.vtt	6.5 KB
2. Text Preprocessing.mp4	41.3 MB
2. Text Preprocessing.vtt	6.4 KB
3. Feature Extraction.mp4	4.7 MB
3. Feature Extraction.vtt	1.6 KB
4. NLP Installation.mp4	62.6 MB
4. NLP Installation.vtt	10.1 KB
5. NLP - Demo.mp4	93.8 MB
5. NLP - Demo.vtt	10.7 KB
6. Replacing Contractions.mp4	141.6 MB
6. Replacing Contractions.vtt	10.6 KB
7. Tokenize Dataset.mp4	72.8 MB
7. Tokenize Dataset.vtt	5.4 KB
8. Remove Stopwords.mp4	71.6 MB
8. Remove Stopwords.vtt	5.8 KB
9. Stemming and Lemmatization.mp4	100.7 MB
9. Stemming and Lemmatization.vtt	9.3 KB
/11. Bayesian Machine Learning AB Testing/
1. Introduction to Bayesian Machine Learning.mp4	38.6 MB
1. Introduction to Bayesian Machine Learning.vtt	10.1 KB
2. Example of Bayesian Machine Learning.mp4	33.4 MB
2. Example of Bayesian Machine Learning.vtt	6.8 KB
3. Example of Bayesian Machine Learning Continues.mp4	37.9 MB
3. Example of Bayesian Machine Learning Continues.vtt	4.5 KB
4. MCMC Module of PYMC Implementation.mp4	45.5 MB
4. MCMC Module of PYMC Implementation.vtt	4.2 KB
5. Running the MCMC Module.mp4	44.6 MB
5. Running the MCMC Module.vtt	4.9 KB
6. Multiple Variant Testing Using Hierarchial Model.mp4	48.2 MB
6. Multiple Variant Testing Using Hierarchial Model.vtt	7.6 KB
7. Example of Multiple Variant Testing.mp4	30.8 MB
7. Example of Multiple Variant Testing.vtt	2.4 KB
8. Example of Multiple Variant Testing Continues.mp4	54.8 MB
8. Example of Multiple Variant Testing Continues.vtt	8.1 KB
/12. Machine Learning with R/
1. Introduction to Machine Learning with Python.mp4	61.1 MB
1. Introduction to Machine Learning with Python.vtt	9.4 KB
10. 2.10 Problem and Solution.mp4	83.5 MB
10. 2.10 Problem and Solution.vtt	7.8 KB
100. Diagnostic Checking.mp4	63.5 MB
100. Diagnostic Checking.vtt	8.9 KB
101. Forecasting Using Stock Price.mp4	114.2 MB
101. Forecasting Using Stock Price.vtt	9.9 KB
102. Stock Price Index.mp4	104.7 MB
102. Stock Price Index.vtt	9.0 KB
103. Stock Price Index Continues.mp4	99.8 MB
103. Stock Price Index Continues.vtt	7.3 KB
104. Prophet Stock.mp4	52.5 MB
104. Prophet Stock.vtt	3.7 KB
105. Run Prophet Stock.mp4	82.0 MB
105. Run Prophet Stock.vtt	6.9 KB
106. Time Series Data Denationalization.mp4	106.2 MB
106. Time Series Data Denationalization.vtt	9.6 KB
107. Time Series Data Denationalization Continues.mp4	82.3 MB
107. Time Series Data Denationalization Continues.vtt	6.8 KB
108. Average of Quarter Denationalization.mp4	133.1 MB
108. Average of Quarter Denationalization.vtt	9.6 KB
109. Regression of Denationalization.mp4	108.8 MB
109. Regression of Denationalization.vtt	7.9 KB
11. Exponentiation Right to Left.mp4	55.8 MB
11. Exponentiation Right to Left.vtt	6.6 KB
110. Gradient Boosting Machines.mp4	70.3 MB
110. Gradient Boosting Machines.vtt	9.3 KB
111. Errors in Gradient Boosting Machines.mp4	60.4 MB
111. Errors in Gradient Boosting Machines.vtt	10.5 KB
112. What is Error Rate in Gradient Boosting Machines.mp4	60.4 MB
112. What is Error Rate in Gradient Boosting Machines.vtt	7.0 KB
113. Optimization Gradient Boosting Machines.mp4	54.3 MB
113. Optimization Gradient Boosting Machines.vtt	6.8 KB
114. Gradient Boosting Trees (GBT).mp4	40.3 MB
114. Gradient Boosting Trees (GBT).vtt	5.6 KB
115. Dataset Boosting in Gradient.mp4	101.1 MB
115. Dataset Boosting in Gradient.vtt	10.8 KB
116. Example of Dataset Boosting in Gradient.mp4	100.4 MB
116. Example of Dataset Boosting in Gradient.vtt	11.1 KB
117. Example of Dataset Boosting in Gradient Continues.mp4	118.7 MB
117. Example of Dataset Boosting in Gradient Continues.vtt	12.9 KB
118. Market Basket Analysis Association Rules.mp4	103.2 MB
118. Market Basket Analysis Association Rules.vtt	11.0 KB
119. Market Basket Analysis Association Rules Continues.mp4	82.1 MB
119. Market Basket Analysis Association Rules Continues.vtt	9.8 KB
12. 2.13 Avoiding Some Common Mistakes.mp4	73.2 MB
12. 2.13 Avoiding Some Common Mistakes.vtt	7.3 KB
120. Market Basket Analysis Interpretation.mp4	52.7 MB
120. Market Basket Analysis Interpretation.vtt	6.9 KB
121. Implementation of Market Basket Analysis.mp4	31.8 MB
121. Implementation of Market Basket Analysis.vtt	4.7 KB
122. Example of Market Basket Analysis.mp4	88.9 MB
122. Example of Market Basket Analysis.vtt	9.3 KB
123. Datamining in Market Basket Analysis.mp4	90.1 MB
123. Datamining in Market Basket Analysis.vtt	11.0 KB
124. Market Basket Analysis Using Rstudio.mp4	82.3 MB
124. Market Basket Analysis Using Rstudio.vtt	9.6 KB
125. Market Basket Analysis Using Rstudio Continues.mp4	98.7 MB
125. Market Basket Analysis Using Rstudio Continues.vtt	98.7 MB
126. More on Rstudio in Market Analysis.mp4	128.5 MB
126. More on Rstudio in Market Analysis.vtt	11.5 KB
127. New Development in Machine Learning.mp4	97.8 MB
127. New Development in Machine Learning.vtt	97.8 MB
128. Data Scientist in Machine Learnirng.mp4	77.6 MB
128. Data Scientist in Machine Learnirng.vtt	10.3 KB
129. Types of Detection in Machine Learning.mp4	107.9 MB
129. Types of Detection in Machine Learning.vtt	9.7 KB
13. Simple Linear Regression.mp4	71.5 MB
13. Simple Linear Regression.vtt	10.7 KB
130. Example of New Development in Machine Learning.mp4	83.1 MB
130. Example of New Development in Machine Learning.vtt	9.4 KB
131. Example of New Development in Machine Learning Continues.mp4	55.7 MB
131. Example of New Development in Machine Learning Continues.vtt	4.6 KB
14. Simple Linear Regression Continues.mp4	41.6 MB
14. Simple Linear Regression Continues.vtt	6.2 KB
15. What is Rsquare.mp4	81.4 MB
15. What is Rsquare.vtt	7.9 KB
16. Standard Error.mp4	57.2 MB
16. Standard Error.vtt	7.5 KB
17. General Statistics.mp4	54.9 MB
17. General Statistics.vtt	4.1 KB
18. General Statistics Continues.mp4	52.7 MB
18. General Statistics Continues.vtt	5.9 KB
19. Simple Linear Regression and More of Statistics.mp4	72.6 MB
19. Simple Linear Regression and More of Statistics.vtt	11.0 KB
2. How do Machine Learn.mp4	54.2 MB
2. How do Machine Learn.vtt	8.3 KB
20. Open the Studio.mp4	42.4 MB
20. Open the Studio.vtt	6.0 KB
21. What is R Square.mp4	83.4 MB
21. What is R Square.vtt	8.2 KB
22. What is STD Error.mp4	58.1 MB
22. What is STD Error.vtt	6.9 KB
23. Reject Null Hypothesis.mp4	88.3 MB
23. Reject Null Hypothesis.vtt	8.4 KB
24. Variance Covariance and Correlation.mp4	85.9 MB
24. Variance Covariance and Correlation.vtt	11.8 KB
25. Root names and Types of Distribution Function.mp4	75.2 MB
25. Root names and Types of Distribution Function.vtt	10.8 KB
26. Generating Random Numbers and Combination Function.mp4	66.2 MB
26. Generating Random Numbers and Combination Function.vtt	7.1 KB
27. Probabilities for Discrete Distribution Function.mp4	87.6 MB
27. Probabilities for Discrete Distribution Function.vtt	9.1 KB
28. Quantile Function and Poison Distribution.mp4	81.1 MB
28. Quantile Function and Poison Distribution.vtt	8.6 KB
29. Students T Distribution, Hypothesis and Example.mp4	66.3 MB
29. Students T Distribution, Hypothesis and Example.vtt	7.3 KB
3. Steps to Apply Machine Learning.mp4	47.9 MB
3. Steps to Apply Machine Learning.vtt	7.4 KB
30. Chai-Square Distribution.mp4	43.3 MB
30. Chai-Square Distribution.vtt	5.0 KB
31. Data Visualization.mp4	81.6 MB
31. Data Visualization.vtt	7.3 KB
32. More on Data Visualization.mp4	74.0 MB
32. More on Data Visualization.vtt	6.9 KB
33. Multiple Linear Regression.mp4	94.8 MB
33. Multiple Linear Regression.vtt	8.0 KB
34. Multiple Linear Regression Continues.mp4	73.4 MB
34. Multiple Linear Regression Continues.vtt	6.5 KB
35. Regression Variables.mp4	106.4 MB
35. Regression Variables.vtt	6.3 KB
36. Generalized Linear Model.mp4	98.3 MB
36. Generalized Linear Model.vtt	10.8 KB
37. Generalized Least Square.mp4	93.1 MB
37. Generalized Least Square.vtt	7.6 KB
38. KNN- Various Methods of Distance Measurements.mp4	55.5 MB
38. KNN- Various Methods of Distance Measurements.vtt	9.2 KB
39. Overview of KNN- (Steps involved).mp4	74.6 MB
39. Overview of KNN- (Steps involved).vtt	10.2 KB
4. Regression and Classification Problems.mp4	65.4 MB
4. Regression and Classification Problems.vtt	8.2 KB
40. Data normalization and prediction on Test Data.mp4	90.6 MB
40. Data normalization and prediction on Test Data.vtt	8.2 KB
41. Improvement of Model Performance and ROC.mp4	89.2 MB
41. Improvement of Model Performance and ROC.vtt	10.9 KB
42. Decision Tree Classifier.mp4	60.6 MB
42. Decision Tree Classifier.vtt	7.7 KB
43. More on Decision Tree Classifier.mp4	85.5 MB
43. More on Decision Tree Classifier.vtt	6.8 KB
44. Pruning of Decision Trees.mp4	87.9 MB
44. Pruning of Decision Trees.vtt	6.9 KB
45. Decision Tree Remaining.mp4	64.1 MB
45. Decision Tree Remaining.vtt	5.7 KB
46. Decision Tree Remaining Continues.mp4	49.0 MB
46. Decision Tree Remaining Continues.vtt	5.4 KB
47. General concept of Random Forest.mp4	67.4 MB
47. General concept of Random Forest.vtt	11.2 KB
48. Ada Boosting and Ensemble Learning.mp4	99.8 MB
48. Ada Boosting and Ensemble Learning.vtt	11.1 KB
49. Data Visualization and Preparation.mp4	93.6 MB
49. Data Visualization and Preparation.vtt	10.2 KB
5. Basic Data Manipulation in R.mp4	75.2 MB
5. Basic Data Manipulation in R.vtt	8.3 KB
50. Tuning Random Forest Model.mp4	66.5 MB
50. Tuning Random Forest Model.vtt	7.3 KB
51. Evaluation of Random Forest Model Performance.mp4	69.1 MB
51. Evaluation of Random Forest Model Performance.vtt	6.9 KB
52. Introduction to Kmeans Clustering.mp4	78.7 MB
52. Introduction to Kmeans Clustering.vtt	11.5 KB
53. Kmeans Elbow Point and Dataset.mp4	94.9 MB
53. Kmeans Elbow Point and Dataset.vtt	10.4 KB
54. Example of Kmeans Dataset.mp4	128.6 MB
54. Example of Kmeans Dataset.vtt	11.1 KB
55. Creating a Graph for Kmeans Clustering.mp4	132.8 MB
55. Creating a Graph for Kmeans Clustering.vtt	10.7 KB
56. Creating a Graph for Kmeans Clustering Continues.mp4	95.0 MB
56. Creating a Graph for Kmeans Clustering Continues.vtt	7.2 KB
57. Aggregation Function of Clustering.mp4	82.3 MB
57. Aggregation Function of Clustering.vtt	8.5 KB
58. Conditional Probability with Bayes Algorithm.mp4	87.0 MB
58. Conditional Probability with Bayes Algorithm.vtt	9.7 KB
59. Venn Diagram Naive Bayes Classification.mp4	64.6 MB
59. Venn Diagram Naive Bayes Classification.vtt	8.9 KB
6. More on Data Manipulation in R.mp4	65.2 MB
6. More on Data Manipulation in R.vtt	6.7 KB
60. Component OF Bayes Theorem using Frequency Table.mp4	91.2 MB
60. Component OF Bayes Theorem using Frequency Table.vtt	10.8 KB
61. Naive Bayes Classification Algorithm and Laplace Estimator.mp4	73.8 MB
61. Naive Bayes Classification Algorithm and Laplace Estimator.vtt	8.9 KB
62. Example of Naive Bayes Classification.mp4	85.6 MB
62. Example of Naive Bayes Classification.vtt	10.0 KB
63. Example of Naive Bayes Classification Continues.mp4	105.0 MB
63. Example of Naive Bayes Classification Continues.vtt	11.3 KB
64. Spam and Ham Messages in Word Cloud.mp4	94.6 MB
64. Spam and Ham Messages in Word Cloud.vtt	9.2 KB
65. Implementation of Dictionary and Document Term Matrix.mp4	85.4 MB
65. Implementation of Dictionary and Document Term Matrix.vtt	7.1 KB
66. Executes the Function Naive Bayes.mp4	94.2 MB
66. Executes the Function Naive Bayes.vtt	9.2 KB
67. Support Vector Machine with Black Box Method.mp4	62.5 MB
67. Support Vector Machine with Black Box Method.vtt	9.5 KB
68. Linearly and Non- Linearly Support Vector Machine.mp4	55.6 MB
68. Linearly and Non- Linearly Support Vector Machine.vtt	9.8 KB
69. Kernal Trick.mp4	60.0 MB
69. Kernal Trick.vtt	9.9 KB
7. Basic Data Manipulation in R - Practical.mp4	75.2 MB
7. Basic Data Manipulation in R - Practical.vtt	8.3 KB
70. Gaussian RBF Kernal and OCR with SVMs.mp4	85.1 MB
70. Gaussian RBF Kernal and OCR with SVMs.vtt	9.3 KB
71. Examples of Gaussian RBF Kernal and OCR with SVMs.mp4	80.7 MB
71. Examples of Gaussian RBF Kernal and OCR with SVMs.vtt	7.0 KB
72. Summary of Support Vector Machine.mp4	82.1 MB
72. Summary of Support Vector Machine.vtt	8.2 KB
73. Feature Selection Dimension Reduction Technique.mp4	90.9 MB
73. Feature Selection Dimension Reduction Technique.vtt	10.0 KB
74. Feature Extraction Dimension Reduction Technique.mp4	86.5 MB
74. Feature Extraction Dimension Reduction Technique.vtt	10.1 KB
75. Dimension Reduction Technique Example.mp4	92.4 MB
75. Dimension Reduction Technique Example.vtt	9.0 KB
76. Dimension Reduction Technique Example Continues.mp4	88.3 MB
76. Dimension Reduction Technique Example Continues.vtt	7.9 KB
77. Introduction Principal Component Analysis.mp4	70.0 MB
77. Introduction Principal Component Analysis.vtt	11.3 KB
78. Steps of PCA.mp4	64.4 MB
78. Steps of PCA.vtt	10.2 KB
79. Steps of PCA Continues.mp4	62.8 MB
79. Steps of PCA Continues.vtt	9.4 KB
8. Create a Vector.mp4	66.7 MB
8. Create a Vector.vtt	6.9 KB
80. Eigen Values.mp4	39.6 MB
80. Eigen Values.vtt	7.1 KB
81. Eigen Vectors.mp4	41.5 MB
81. Eigen Vectors.vtt	7.1 KB
82. Principal Component Analysis using Pr-Comp.mp4	109.1 MB
82. Principal Component Analysis using Pr-Comp.vtt	10.0 KB
83. Principal Component Analysis using Pr-Comp Continues.mp4	80.3 MB
83. Principal Component Analysis using Pr-Comp Continues.vtt	8.3 KB
84. C Bind Type in PCA.mp4	94.0 MB
84. C Bind Type in PCA.vtt	7.8 KB
85. R Type Model.mp4	127.2 MB
85. R Type Model.vtt	10.8 KB
86. Black Box Method in Neural Network.mp4	91.6 MB
86. Black Box Method in Neural Network.vtt	8.6 KB
87. Characteristics of a Neural Networks.mp4	76.2 MB
87. Characteristics of a Neural Networks.vtt	9.0 KB
88. Network Topology of a Neural Networks.mp4	73.9 MB
88. Network Topology of a Neural Networks.vtt	10.6 KB
89. Weight Adjustment and Case Update.mp4	84.9 MB
89. Weight Adjustment and Case Update.vtt	11.2 KB
9. 2.7 Problem and Solution.mp4	73.3 MB
9. 2.7 Problem and Solution.vtt	6.6 KB
90. Introduction Model Building in R.mp4	105.8 MB
90. Introduction Model Building in R.vtt	9.9 KB
91. Installing the Package of Model Building in R.mp4	92.8 MB
91. Installing the Package of Model Building in R.vtt	10.2 KB
92. Nodes in Model Building in R.mp4	74.2 MB
92. Nodes in Model Building in R.vtt	7.9 KB
93. Example of Model Building in R.mp4	85.6 MB
93. Example of Model Building in R.vtt	8.3 KB
94. Time Series Analysis.mp4	71.8 MB
94. Time Series Analysis.vtt	7.6 KB
95. Pattern in Time Series Data.mp4	53.5 MB
95. Pattern in Time Series Data.vtt	7.5 KB
96. Time Series Modelling.mp4	58.7 MB
96. Time Series Modelling.vtt	8.5 KB
97. Moving Average Model.mp4	70.5 MB
97. Moving Average Model.vtt	9.6 KB
98. Auto Correlation Function.mp4	45.2 MB
98. Auto Correlation Function.vtt	8.4 KB
99. Inference of ACF and PFCF.mp4	47.4 MB
99. Inference of ACF and PFCF.vtt	7.3 KB
/13. BIP - Business Intelligence Publisher using Siebel/
1. Introduction to BIP.mp4	22.0 MB
1. Introduction to BIP.vtt	5.0 KB
10. Siebel Applets &sbquo; Business Obejct and Business Components Part 2.mp4	94.7 MB
10. Siebel Applets &sbquo; Business Obejct and Business Components Part 2.vtt	10.1 KB
11. IntegrationObjectsANDIntegrationObjectComponents.mp4	106.0 MB
11. IntegrationObjectsANDIntegrationObjectComponents.vtt	11.1 KB
12. Siebel Views and View Associations to Reports.mp4	86.8 MB
12. Siebel Views and View Associations to Reports.vtt	7.6 KB
13. Siebel HI-OpenUI framworks for BIP Reports and demo of AddIn.mp4	44.8 MB
13. Siebel HI-OpenUI framworks for BIP Reports and demo of AddIn.vtt	6.3 KB
14. Process_Flow_Overview.mp4	54.3 MB
14. Process_Flow_Overview.vtt	8.5 KB
15. Process_Flow_ConnectedMode.mp4	44.3 MB
15. Process_Flow_ConnectedMode.vtt	6.3 KB
16. Process_Flow_DisconnectedMode.mp4	44.2 MB
16. Process_Flow_DisconnectedMode.vtt	7.1 KB
17. Siebel Report Business Service.mp4	81.1 MB
17. Siebel Report Business Service.vtt	8.2 KB
2. User Types.mp4	10.9 MB
2. User Types.vtt	3.9 KB
3. Running Modes.mp4	35.1 MB
3. Running Modes.vtt	6.7 KB
4. Learning about BIP Add-Ins.mp4	62.7 MB
4. Learning about BIP Add-Ins.vtt	7.0 KB
5. BIP_Into_5_BIP_AddIn2 and BIP_Into_6.mp4	67.5 MB
5. BIP_Into_5_BIP_AddIn2 and BIP_Into_6.vtt	7.2 KB
6. BIP_Into_7_Customized Reports Overview.mp4	62.2 MB
6. BIP_Into_7_Customized Reports Overview.vtt	6.8 KB
7. BIP_Into_8_Developing Reports Overview.mp4	20.1 MB
7. BIP_Into_8_Developing Reports Overview.vtt	4.8 KB
8. Showing Report Views on Application.mp4	115.4 MB
8. Showing Report Views on Application.vtt	11.6 KB
9. Siebel Applets &sbquo; Business Obejct and Business Components Part 1.mp4	91.6 MB
9. Siebel Applets &sbquo; Business Obejct and Business Components Part 1.vtt	10.5 KB
/14. BI - Business Intelligence/
1. BI Intro,definition.mp4	53.7 MB
1. BI Intro,definition.vtt	10.7 KB
10. planning deliverables,stage 3.mp4	35.8 MB
10. planning deliverables,stage 3.vtt	6.9 KB
100. Regression Model(Continues).mp4	46.9 MB
100. Regression Model(Continues).vtt	10.6 KB
101. Market Basket Analysis Applications.mp4	49.0 MB
101. Market Basket Analysis Applications.vtt	11.7 KB
102. Market Basket Analysis Applications(Continues).mp4	37.7 MB
102. Market Basket Analysis Applications(Continues).vtt	10.7 KB
11. Project Requirement,Data Analysis,Application part 1.mp4	55.5 MB
11. Project Requirement,Data Analysis,Application part 1.vtt	11.0 KB
12. Project Requirement,Data Analysis,Application part 2.mp4	68.3 MB
12. Project Requirement,Data Analysis,Application part 2.vtt	8.9 KB
13. Project Requirement,Data Analysis,Application part 3.mp4	49.3 MB
13. Project Requirement,Data Analysis,Application part 3.vtt	8.0 KB
14. Meta Data.mp4	11.6 MB
14. Meta Data.vtt	2.1 KB
15. data standardisation,meta data,etl,business analysis part 1.mp4	64.5 MB
15. data standardisation,meta data,etl,business analysis part 1.vtt	11.0 KB
16. data standardisation,meta data,etl,business analysis part 2.mp4	53.6 MB
16. data standardisation,meta data,etl,business analysis part 2.vtt	9.7 KB
17. data standardisation,meta data,etl,business analysis part 3.mp4	21.5 MB
17. data standardisation,meta data,etl,business analysis part 3.vtt	3.4 KB
18. ETL Design,Meta DATA ,STAGE 5 CONSTRUCTION DEVELOPMENT RECONCILATION Part 1.mp4	49.4 MB
18. ETL Design,Meta DATA ,STAGE 5 CONSTRUCTION DEVELOPMENT RECONCILATION Part 1.vtt	10.1 KB
19. ETL Design,Meta DATA ,STAGE 5 CONSTRUCTION DEVELOPMENT RECONCILATION Part 2.mp4	68.5 MB
19. ETL Design,Meta DATA ,STAGE 5 CONSTRUCTION DEVELOPMENT RECONCILATION Part 2.vtt	12.0 KB
2. multidimensional db part 1.mp4	52.5 MB
2. multidimensional db part 1.vtt	9.0 KB
20. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 1.mp4	48.9 MB
20. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 1.vtt	9.9 KB
21. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 2.mp4	18.2 MB
21. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 2.vtt	4.3 KB
22. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 3.mp4	63.8 MB
22. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 3.vtt	11.3 KB
23. database & recovery,release evaluation.mp4	32.0 MB
23. database & recovery,release evaluation.vtt	32.0 MB
24. post implementation review,toyota case.mp4	47.1 MB
24. post implementation review,toyota case.vtt	8.2 KB
25. frame work for BI Part 1.mp4	61.6 MB
25. frame work for BI Part 1.vtt	11.9 KB
26. frame work for BI Part 2.mp4	58.8 MB
26. frame work for BI Part 2.vtt	9.5 KB
27. frame work for BI Part 3.mp4	34.7 MB
27. frame work for BI Part 3.vtt	5.3 KB
28. frame work for BI Part 4.mp4	40.0 MB
28. frame work for BI Part 4.vtt	5.1 KB
29. strategic imperitive of BI Part 1.mp4	51.7 MB
29. strategic imperitive of BI Part 1.vtt	8.0 KB
3. multidimensional db part 2.mp4	64.2 MB
3. multidimensional db part 2.vtt	11.0 KB
30. strategic imperitive of BI Part 2.mp4	43.8 MB
30. strategic imperitive of BI Part 2.vtt	6.7 KB
31. Target System.mp4	50.1 MB
31. Target System.vtt	7.9 KB
32. Data warehouse and ETL.mp4	34.6 MB
32. Data warehouse and ETL.vtt	6.4 KB
33. Facebook dataspace management with open source tools.mp4	40.2 MB
33. Facebook dataspace management with open source tools.vtt	6.2 KB
34. Agile Development Process.mp4	36.2 MB
34. Agile Development Process.vtt	5.9 KB
35. Agile Development Process Continues.mp4	46.8 MB
35. Agile Development Process Continues.vtt	7.5 KB
36. Challenges on dash board.mp4	33.8 MB
36. Challenges on dash board.vtt	4.6 KB
37. Building Users Expert Profile.mp4	65.8 MB
37. Building Users Expert Profile.vtt	8.3 KB
38. Semantic Technologies.mp4	55.7 MB
38. Semantic Technologies.vtt	7.2 KB
39. Semantic Tools.mp4	56.3 MB
39. Semantic Tools.vtt	6.9 KB
4. multidimensional db part 3.mp4	58.8 MB
4. multidimensional db part 3.vtt	10.5 KB
40. BI Algorithm By Example.mp4	44.1 MB
40. BI Algorithm By Example.vtt	8.7 KB
41. Benefits of BI.mp4	29.0 MB
41. Benefits of BI.vtt	8.3 KB
42. Benefits of BI Continues.mp4	45.8 MB
42. Benefits of BI Continues.vtt	8.3 KB
43. Amazon.com and Net Flix.mp4	40.9 MB
43. Amazon.com and Net Flix.vtt	7.4 KB
44. What is Information Governance.mp4	52.4 MB
44. What is Information Governance.vtt	7.9 KB
45. Other BI Applications are used to store.mp4	47.5 MB
45. Other BI Applications are used to store.vtt	7.1 KB
46. Designing and Implementing BI Program.mp4	49.0 MB
46. Designing and Implementing BI Program.vtt	6.0 KB
47. ETL.mp4	39.2 MB
47. ETL.vtt	7.7 KB
48. ETL Continues.mp4	32.3 MB
48. ETL Continues.vtt	6.3 KB
49. Loading.mp4	36.8 MB
49. Loading.vtt	7.2 KB
5. dbms platform.mp4	12.4 MB
5. dbms platform.vtt	2.9 KB
50. Type 2 Dimension.mp4	54.4 MB
50. Type 2 Dimension.vtt	8.8 KB
51. Loading Fact Tables.mp4	49.7 MB
51. Loading Fact Tables.vtt	7.5 KB
52. Genearl Idea.mp4	43.4 MB
52. Genearl Idea.vtt	7.4 KB
53. Conceptual Model.mp4	38.7 MB
53. Conceptual Model.vtt	8.0 KB
54. Conceptual Model Continues.mp4	52.4 MB
54. Conceptual Model Continues.vtt	8.6 KB
55. On Going Or Future Works.mp4	53.9 MB
55. On Going Or Future Works.vtt	11.6 KB
56. Why Meta Data.mp4	44.8 MB
56. Why Meta Data.vtt	12.7 KB
57. Essentials Capabilities.mp4	28.8 MB
57. Essentials Capabilities.vtt	7.6 KB
58. Common Warehouse Metamodels.mp4	32.3 MB
58. Common Warehouse Metamodels.vtt	7.0 KB
59. Data Advantage Group.mp4	56.6 MB
59. Data Advantage Group.vtt	10.4 KB
6. technical non technical infrastructre part 1.mp4	45.2 MB
6. technical non technical infrastructre part 1.vtt	12.4 KB
60. DBMS Meta Data Tips.mp4	67.4 MB
60. DBMS Meta Data Tips.vtt	10.7 KB
61. For Building The Dataware house(Extraction Team).mp4	54.2 MB
61. For Building The Dataware house(Extraction Team).vtt	8.3 KB
62. Meta Data Essentials For IT.mp4	51.0 MB
62. Meta Data Essentials For IT.vtt	8.1 KB
63. Business Metadata.mp4	43.1 MB
63. Business Metadata.vtt	9.7 KB
64. Business Meta Data (Continues).mp4	25.4 MB
64. Business Meta Data (Continues).vtt	5.3 KB
65. Project Planning.mp4	59.6 MB
65. Project Planning.vtt	9.3 KB
66. Project Planning (Continues).mp4	32.7 MB
66. Project Planning (Continues).vtt	5.8 KB
67. Deployment Process.mp4	78.1 MB
67. Deployment Process.vtt	13.8 KB
68. Chapter Outline.mp4	41.3 MB
68. Chapter Outline.vtt	9.2 KB
69. Break-Even Analysis.mp4	39.7 MB
69. Break-Even Analysis.vtt	9.0 KB
7. technical non technical infrastructre part 2.mp4	53.7 MB
7. technical non technical infrastructre part 2.vtt	10.4 KB
70. Examples Of Break-Even Analysis.mp4	45.8 MB
70. Examples Of Break-Even Analysis.vtt	9.9 KB
71. Multivirate Analysis.mp4	52.4 MB
71. Multivirate Analysis.vtt	8.5 KB
72. Multivirate Analysis (Continues).mp4	32.4 MB
72. Multivirate Analysis (Continues).vtt	7.7 KB
73. Graphs.mp4	43.5 MB
73. Graphs.vtt	10.7 KB
74. Why Meta Data Is Important.mp4	41.4 MB
74. Why Meta Data Is Important.vtt	7.6 KB
75. System Development.mp4	31.4 MB
75. System Development.vtt	8.8 KB
76. Project Risk Assesment Factors.mp4	48.6 MB
76. Project Risk Assesment Factors.vtt	11.1 KB
77. Managing Project Time.mp4	38.7 MB
77. Managing Project Time.vtt	9.0 KB
78. Prototyping Benefits.mp4	64.4 MB
78. Prototyping Benefits.vtt	12.3 KB
79. Incremental Development.mp4	60.8 MB
79. Incremental Development.vtt	12.1 KB
8. change control board part 1.mp4	60.0 MB
8. change control board part 1.vtt	9.7 KB
80. Incremental Development(Continues).mp4	50.2 MB
80. Incremental Development(Continues).vtt	10.3 KB
81. What is Cluster Analysis.mp4	51.3 MB
81. What is Cluster Analysis.vtt	10.2 KB
82. Types Of Clusters.mp4	51.7 MB
82. Types Of Clusters.vtt	7.4 KB
83. Cluster Benefits.mp4	37.4 MB
83. Cluster Benefits.vtt	6.8 KB
84. Kmeans Clustering Method.mp4	90.1 MB
84. Kmeans Clustering Method.vtt	14.0 KB
85. What Is The Problem With PAM.mp4	64.6 MB
85. What Is The Problem With PAM.vtt	12.5 KB
86. BIRCH (1996).mp4	59.4 MB
86. BIRCH (1996).vtt	8.8 KB
87. Density Rechable And Density Conected.mp4	55.4 MB
87. Density Rechable And Density Conected.vtt	9.1 KB
88. Denclue Technical Issues.mp4	69.0 MB
88. Denclue Technical Issues.vtt	11.6 KB
89. The Wave Cluster Algorithm.mp4	50.6 MB
89. The Wave Cluster Algorithm.vtt	8.0 KB
9. change control board part 2.mp4	50.9 MB
9. change control board part 2.vtt	10.3 KB
90. More On Conceptual Clustering.mp4	63.8 MB
90. More On Conceptual Clustering.vtt	9.3 KB
91. Clustering in Quest.mp4	61.2 MB
91. Clustering in Quest.vtt	11.8 KB
92. Why Constraints Based Cluster Analysis.mp4	54.3 MB
92. Why Constraints Based Cluster Analysis.vtt	8.4 KB
93. What Is Outlier Discovery.mp4	44.0 MB
93. What Is Outlier Discovery.vtt	7.4 KB
94. Segmentation In Data Mining.mp4	48.7 MB
94. Segmentation In Data Mining.vtt	10.7 KB
95. Bottle Neck Of GSP & Spade.mp4	54.1 MB
95. Bottle Neck Of GSP & Spade.vtt	54.1 MB
96. Why Deal with Sequential Data.mp4	43.6 MB
96. Why Deal with Sequential Data.vtt	11.7 KB
97. Algorithm Definition.mp4	43.9 MB
97. Algorithm Definition.vtt	10.3 KB
98. Introduction To Regression Analysis.mp4	37.1 MB
98. Introduction To Regression Analysis.vtt	7.6 KB
99. Regression Model.mp4	55.6 MB
99. Regression Model.vtt	11.2 KB
/2. Machine Learning with Tensorflow for Beginners/
1. Introduction to Machine Learning with Tensorflow.mp4	18.7 MB
1. Introduction to Machine Learning with Tensorflow.vtt	5.5 KB
10. Understanding what Anaconda cloud is.mp4	84.7 MB
10. Understanding what Anaconda cloud is.vtt	8.7 KB
100. Run Optimizer.mp4	14.3 MB
100. Run Optimizer.vtt	1.9 KB
101. Create a Range.mp4	53.9 MB
101. Create a Range.vtt	6.5 KB
102. Introduction to Neural Networks.mp4	5.9 MB
102. Introduction to Neural Networks.vtt	1.3 KB
103. Basic-Concepts.mp4	106.5 MB
103. Basic-Concepts.vtt	13.2 KB
104. Activative Functions.mp4	104.8 MB
104. Activative Functions.vtt	11.1 KB
105. Activative Functions Input to Output.mp4	60.5 MB
105. Activative Functions Input to Output.vtt	60.5 MB
106. Classification Functions.mp4	64.7 MB
106. Classification Functions.vtt	8.6 KB
107. Tensorflow-Playground.mp4	143.3 MB
107. Tensorflow-Playground.vtt	14.5 KB
108. Mnist-Dataset.mp4	57.0 MB
108. Mnist-Dataset.vtt	11.0 KB
109. Mnist-Dataset Continue.mp4	98.3 MB
109. Mnist-Dataset Continue.vtt	12.4 KB
11. Installation of Anaconda for Windows.mp4	52.7 MB
11. Installation of Anaconda for Windows.vtt	7.5 KB
110. More on Mnist-Dataset.mp4	85.9 MB
110. More on Mnist-Dataset.vtt	7.9 KB
12. Installation of Anaconda in Linux.mp4	30.6 MB
12. Installation of Anaconda in Linux.vtt	4.0 KB
13. Using the Jupyter notebook.mp4	27.3 MB
13. Using the Jupyter notebook.vtt	3.4 KB
14. Getting started with Anaconda.mp4	142.8 MB
14. Getting started with Anaconda.vtt	11.3 KB
15. Determining options for Cloudberry.mp4	41.4 MB
15. Determining options for Cloudberry.vtt	0.0 KB
16. Introduction to Third Party Libraries.mp4	8.6 MB
16. Introduction to Third Party Libraries.vtt	3.6 KB
17. Numpy-Array.mp4.mtd	0.4 KB
17. Numpy-Array.vtt	13.6 KB
18. Numpy-Array Continue.mp4	88.2 MB
18. Numpy-Array Continue.vtt	9.4 KB
19. Arrays.mp4	115.7 MB
19. Arrays.vtt	13.8 KB
2. Understanding Machine Learning.mp4	16.3 MB
2. Understanding Machine Learning.vtt	8.7 KB
20. Arrays Continue.mp4	58.1 MB
20. Arrays Continue.vtt	6.3 KB
21. Indexing.mp4	66.4 MB
21. Indexing.vtt	7.6 KB
22. Indexing Continue.mp4	89.2 MB
22. Indexing Continue.vtt	9.4 KB
23. Universal Functions.mp4	114.9 MB
23. Universal Functions.vtt	11.0 KB
24. Introoduction to Pandas.mp4	27.3 MB
24. Introoduction to Pandas.vtt	4.8 KB
25. Pandas Series.mp4	35.1 MB
25. Pandas Series.vtt	4.8 KB
26. Pandas Series Continue.mp4	39.9 MB
26. Pandas Series Continue.vtt	5.7 KB
27. Import Randin.mp4	68.1 MB
27. Import Randin.vtt	9.6 KB
28. Import Randin Continue.mp4	75.9 MB
28. Import Randin Continue.vtt	10.5 KB
29. Paratmeters.mp4	92.0 MB
29. Paratmeters.vtt	10.6 KB
3. How do Machines Learns.mp4	54.4 MB
3. How do Machines Learns.vtt	14.7 KB
30. Indexing and Database.mp4	39.7 MB
30. Indexing and Database.vtt	4.7 KB
31. Missing Data.mp4	31.8 MB
31. Missing Data.vtt	5.3 KB
32. Missing Data-Groupby.mp4	21.2 MB
32. Missing Data-Groupby.vtt	3.3 KB
33. Missing Data-Groupby Continue.mp4	28.2 MB
33. Missing Data-Groupby Continue.vtt	4.2 KB
34. Concat-Merge-Join.mp4	83.8 MB
34. Concat-Merge-Join.vtt	11.3 KB
35. Operations.mp4	50.4 MB
35. Operations.vtt	6.3 KB
36. Import-Export.mp4	109.7 MB
36. Import-Export.vtt	11.8 KB
37. Python Visualisation.mp4	51.4 MB
37. Python Visualisation.vtt	4.9 KB
38. Mat Plotting.mp4	66.5 MB
38. Mat Plotting.vtt	11.7 KB
39. Multiple Plot Subsections.mp4	65.4 MB
39. Multiple Plot Subsections.vtt	7.8 KB
4. Uses of Machine Learning.mp4	31.7 MB
4. Uses of Machine Learning.vtt	10.2 KB
40. API Functionality.mp4	67.9 MB
40. API Functionality.vtt	8.2 KB
41. Title of the Plot.mp4	96.2 MB
41. Title of the Plot.vtt	180.9 MB
42. Change Size of Articles.mp4	62.7 MB
42. Change Size of Articles.vtt	8.1 KB
43. Two Different Crops.mp4	57.6 MB
43. Two Different Crops.vtt	7.7 KB
44. Mat Plotting Label.mp4	51.7 MB
44. Mat Plotting Label.vtt	6.6 KB
45. Marker Color.mp4	76.2 MB
45. Marker Color.vtt	9.4 KB
46. Create a New Dataframe.mp4	42.2 MB
46. Create a New Dataframe.vtt	4.9 KB
47. Change the Style.mp4	46.6 MB
47. Change the Style.vtt	6.1 KB
48. Index and Value.mp4	43.4 MB
48. Index and Value.vtt	5.3 KB
49. Seaborn-Statistical Data Visualization.mp4	61.9 MB
49. Seaborn-Statistical Data Visualization.vtt	7.6 KB
5. Examples with tensorflow by Google.mp4	60.1 MB
5. Examples with tensorflow by Google.vtt	9.2 KB
50. seaborn library.mp4	100.6 MB
50. seaborn library.vtt	12.9 KB
51. Jointplot.mp4	85.9 MB
51. Jointplot.vtt	10.1 KB
52. Pairplot.mp4	115.1 MB
52. Pairplot.vtt	11.9 KB
53. Barplot.mp4	102.3 MB
53. Barplot.vtt	10.7 KB
54. Boxplot.mp4	51.8 MB
54. Boxplot.vtt	5.9 KB
55. Stripplot.mp4	81.8 MB
55. Stripplot.vtt	7.3 KB
56. Matrix.mp4	97.3 MB
56. Matrix.vtt	0.0 KB
57. Matrix Continue.mp4	34.9 MB
57. Matrix Continue.vtt	3.3 KB
58. Grid.mp4	116.2 MB
58. Grid.vtt	8.9 KB
59. Grid Continue.mp4	59.4 MB
59. Grid Continue.vtt	5.9 KB
6. Setting up the Workstation.mp4	7.4 MB
6. Setting up the Workstation.vtt	3.4 KB
60. Style.mp4	15.6 MB
60. Style.vtt	1.5 KB
61. Python Libraries Conclusion.mp4	13.7 MB
61. Python Libraries Conclusion.vtt	1.8 KB
62. Introduction To Conda Envirement.mp4	21.7 MB
62. Introduction To Conda Envirement.vtt	3.8 KB
63. Scikit Learn.mp4	18.1 MB
63. Scikit Learn.vtt	6.3 KB
64. Scikit Learn Continue.mp4	43.8 MB
64. Scikit Learn Continue.vtt	8.5 KB
65. Datasets.mp4	31.7 MB
65. Datasets.vtt	10.2 KB
66. California Dataset.mp4	63.4 MB
66. California Dataset.vtt	9.1 KB
67. Data Visualization.mp4	92.8 MB
67. Data Visualization.vtt	9.8 KB
68. Datavisualization Continue.mp4	58.2 MB
68. Datavisualization Continue.vtt	8.5 KB
69. Downloading a Test Data.mp4	95.0 MB
69. Downloading a Test Data.vtt	11.1 KB
7. Understanding program languages.mp4	6.8 MB
7. Understanding program languages.vtt	3.8 KB
70. Population Parameter.mp4	82.6 MB
70. Population Parameter.vtt	7.9 KB
71. Processing.mp4	108.6 MB
71. Processing.vtt	48.6 MB
72. Null Values with Median Value.mp4	84.0 MB
72. Null Values with Median Value.vtt	9.5 KB
73. Replace Missing Values.mp4	34.1 MB
73. Replace Missing Values.vtt	3.6 KB
74. Label Enconder.mp4	27.3 MB
74. Label Enconder.vtt	4.2 KB
75. Import Labelencoder.mp4	95.1 MB
75. Import Labelencoder.vtt	10.2 KB
76. Custom Transformation.mp4	29.6 MB
76. Custom Transformation.vtt	3.1 KB
77. Transformer Custom Transformer.mp4	58.7 MB
77. Transformer Custom Transformer.vtt	5.8 KB
78. Housing with Custom Colums.mp4	59.8 MB
78. Housing with Custom Colums.vtt	4.6 KB
79. Numeric Hosing Data.mp4	126.1 MB
79. Numeric Hosing Data.vtt	9.8 KB
8. Understanding and Functions of Jupyter.mp4	68.4 MB
8. Understanding and Functions of Jupyter.vtt	8.7 KB
80. Liner Regression.mp4	52.0 MB
80. Liner Regression.vtt	7.6 KB
81. Fine Tuning Model.mp4	43.4 MB
81. Fine Tuning Model.vtt	5.3 KB
82. Fine Tuning Model Continue.mp4	60.8 MB
82. Fine Tuning Model Continue.vtt	7.3 KB
83. Quick-Recap.mp4	5.6 MB
83. Quick-Recap.vtt	2.0 KB
84. Tensorflow.mp4	60.6 MB
84. Tensorflow.vtt	9.7 KB
85. Tensorflow-Hello-World.mp4	57.3 MB
85. Tensorflow-Hello-World.vtt	11.4 KB
86. Basic Ops.mp4	82.1 MB
86. Basic Ops.vtt	12.6 KB
87. Basic Ops Continue.mp4	73.7 MB
87. Basic Ops Continue.vtt	66.4 MB
88. More on Basic Ops.mp4	71.1 MB
88. More on Basic Ops.vtt	9.0 KB
89. Eager-Mode.mp4	51.2 MB
89. Eager-Mode.vtt	6.2 KB
9. Learning of Jupyter installation.mp4	5.3 MB
9. Learning of Jupyter installation.vtt	2.9 KB
90. Concept.mp4	39.3 MB
90. Concept.vtt	9.6 KB
91. Linear-Regression.mp4	26.5 MB
91. Linear-Regression.vtt	4.8 KB
92. Linear-Model.mp4	47.6 MB
92. Linear-Model.vtt	8.3 KB
93. Matrix Multiplication Function.mp4	79.2 MB
93. Matrix Multiplication Function.vtt	12.1 KB
94. Practice for a Simple Linear Model.mp4	25.6 MB
94. Practice for a Simple Linear Model.vtt	4.1 KB
95. Cost Function.mp4	24.1 MB
95. Cost Function.vtt	4.1 KB
96. Creative Optimizer.mp4	37.9 MB
96. Creative Optimizer.vtt	5.4 KB
97. RR Input and Output Value.mp4	28.8 MB
97. RR Input and Output Value.vtt	4.6 KB
98. Logistic-Regression.mp4	54.1 MB
98. Logistic-Regression.vtt	7.0 KB
99. Global Variabales Initializer.mp4	38.3 MB
99. Global Variabales Initializer.vtt	4.6 KB
/3. Machine Learning Project #1 - Shipping and Time Estimation/
1. Introduction to Shipping and pricing.mp4	27.0 MB
1. Introduction to Shipping and pricing.vtt	3.9 KB
10. Demand Forecasting.mp4	89.3 MB
10. Demand Forecasting.vtt	8.9 KB
11. Distribution of Attributes.mp4	66.8 MB
11. Distribution of Attributes.vtt	6.6 KB
12. Spending Distribution.mp4	86.7 MB
12. Spending Distribution.vtt	5.5 KB
13. Normalization and Discretization.mp4	125.3 MB
13. Normalization and Discretization.vtt	5.8 KB
2. Inventory Status.mp4	109.7 MB
2. Inventory Status.vtt	8.2 KB
3. Defining Data Type.mp4	100.1 MB
3. Defining Data Type.vtt	6.9 KB
4. Data for Validation.mp4	108.3 MB
4. Data for Validation.vtt	6.8 KB
5. Finding the Corelation.mp4	76.2 MB
5. Finding the Corelation.vtt	7.9 KB
6. Density for Numeric Attribute.mp4	92.2 MB
6. Density for Numeric Attribute.vtt	6.8 KB
7. Method for Train Control.mp4	53.0 MB
7. Method for Train Control.vtt	2.8 KB
8. Assigning a Training Set.mp4	131.3 MB
8. Assigning a Training Set.vtt	6.0 KB
9. Mean Absolute Error.mp4	74.9 MB
9. Mean Absolute Error.vtt	6.7 KB
/4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/
1. Introduction to Supply Chain.mp4	105.2 MB
1. Introduction to Supply Chain.vtt	6.6 KB
2. G Plot of Heatmap.mp4	82.6 MB
2. G Plot of Heatmap.vtt	4.8 KB
3. Checking the Function Argument.mp4	127.1 MB
3. Checking the Function Argument.vtt	4.0 KB
4. Heatmap for Discretized Dataset.mp4	92.9 MB
4. Heatmap for Discretized Dataset.vtt	8.1 KB
5. Distinguished Methods with Single.mp4	45.7 MB
5. Distinguished Methods with Single.vtt	4.1 KB
6. Analyzing both the Plots.mp4	76.4 MB
6. Analyzing both the Plots.vtt	6.0 KB
7. Defining the Lengths.mp4	106.4 MB
7. Defining the Lengths.vtt	6.7 KB
8. Using Different Clusters.mp4	56.8 MB
8. Using Different Clusters.vtt	4.0 KB
/5. Machine Learning Project #3 - Predicting Prices using Regression/
1. Introduction to Predicting Prices Using Regression.mp4	61.8 MB
1. Introduction to Predicting Prices Using Regression.vtt	11.0 KB
10. Replacing Features with Values.mp4	87.8 MB
10. Replacing Features with Values.vtt	9.0 KB
11. Assigning Quantatative Variables.mp4	48.1 MB
11. Assigning Quantatative Variables.vtt	5.4 KB
12. Converting Columns to Cordinal Forms.mp4	51.2 MB
12. Converting Columns to Cordinal Forms.vtt	4.7 KB
13. Evaluating the Garage Finish Colummn.mp4	69.4 MB
13. Evaluating the Garage Finish Colummn.vtt	7.2 KB
14. Checking Shape of Data Frame.mp4	15.6 MB
14. Checking Shape of Data Frame.vtt	2.2 KB
15. Spliting Data to Train and Test.mp4	72.2 MB
15. Spliting Data to Train and Test.vtt	8.8 KB
16. Algorithm for Predicting Test Values.mp4	29.4 MB
16. Algorithm for Predicting Test Values.vtt	4.2 KB
2. Proximity to Various Conditions.mp4	67.5 MB
2. Proximity to Various Conditions.vtt	11.1 KB
3. Number of Fire Places.mp4	31.7 MB
3. Number of Fire Places.vtt	5.2 KB
4. Adding the Test Value.mp4	86.6 MB
4. Adding the Test Value.vtt	86.6 MB
5. Index to the ID Column.mp4	71.5 MB
5. Index to the ID Column.vtt	8.5 KB
6. Model on Data Set.mp4	86.2 MB
6. Model on Data Set.vtt	8.9 KB
7. Missing Value Imputation.mp4	59.1 MB
7. Missing Value Imputation.vtt	6.2 KB
8. Substituting Features with Value.mp4	96.2 MB
8. Substituting Features with Value.vtt	9.1 KB
9. Imputing a Row using at Command.mp4	75.1 MB
9. Imputing a Row using at Command.vtt	7.4 KB
/6. Machine Learning Project #4 - Banking and Credit Frauds/
1. Introduction to Banking System.mp4	17.9 MB
1. Introduction to Banking System.vtt	6.6 KB
2. Laon Status Grade.mp4	98.0 MB
2. Laon Status Grade.vtt	8.1 KB
3. Logistic Regression and Logistic Question.mp4	67.7 MB
3. Logistic Regression and Logistic Question.vtt	5.7 KB
4. Beta Value.mp4	50.6 MB
4. Beta Value.vtt	2.9 KB
5. Predict Value.mp4	81.6 MB
5. Predict Value.vtt	5.7 KB
6. Performance Value.mp4	66.7 MB
6. Performance Value.vtt	4.4 KB
7. Fals Positive Rate.mp4	45.5 MB
7. Fals Positive Rate.vtt	3.6 KB
/7. Machine Learning Project #5 - Fraud Detection in Credit Payments/
1. Introduction to Fraud Detection in Credit Payments.mp4	18.2 MB
1. Introduction to Fraud Detection in Credit Payments.vtt	6.6 KB
10. VRS.mp4	112.7 MB
10. VRS.vtt	7.0 KB
11. CRS Efficiency and Efficiency.mp4	55.7 MB
11. CRS Efficiency and Efficiency.vtt	5.8 KB
2. Installation of Packages.mp4	76.3 MB
2. Installation of Packages.vtt	7.4 KB
3. Risk Analytics.mp4	86.5 MB
3. Risk Analytics.vtt	10.5 KB
4. Trading Companies and Stocks.mp4	102.4 MB
4. Trading Companies and Stocks.vtt	9.4 KB
5. DEA with Input or Profit and Loss.mp4	92.0 MB
5. DEA with Input or Profit and Loss.vtt	7.5 KB
6. Efficiency Profit and Loss.mp4	67.9 MB
6. Efficiency Profit and Loss.vtt	5.4 KB
7. Rank Functions.mp4	80.2 MB
7. Rank Functions.vtt	6.9 KB
8. RHS Constaints.mp4	93.7 MB
8. RHS Constaints.vtt	8.5 KB
9. Profit and Loss Report.mp4	76.7 MB
9. Profit and Loss Report.vtt	6.1 KB
/8. AWS Machine Learning/
1. Introduction to Amazon Machine Learning (AML).mp4	40.0 MB
1. Introduction to Amazon Machine Learning (AML).vtt	8.5 KB
10. Example of Data Insight In AML.mp4	70.1 MB
10. Example of Data Insight In AML.vtt	11.5 KB
11. More on Data Insight In AML.mp4	57.2 MB
11. More on Data Insight In AML.vtt	8.3 KB
12. ML Model Example in Data Sources.mp4	95.1 MB
12. ML Model Example in Data Sources.vtt	12.8 KB
13. Creating ML Model Evaluating.mp4	88.7 MB
13. Creating ML Model Evaluating.vtt	8.6 KB
14. Advanced Setting In ML Model.mp4	40.3 MB
14. Advanced Setting In ML Model.vtt	4.9 KB
15. Creating ML Model for Batch Prediction.mp4	89.0 MB
15. Creating ML Model for Batch Prediction.vtt	9.9 KB
16. Batch Prediction Result.mp4	49.9 MB
16. Batch Prediction Result.vtt	5.7 KB
17. Overvies of ML Model Handson.mp4	68.5 MB
17. Overvies of ML Model Handson.vtt	7.4 KB
18. ML objects Handson in ML.mp4	47.8 MB
18. ML objects Handson in ML.vtt	4.2 KB
2. Lifecycle of AML.mp4	45.6 MB
2. Lifecycle of AML.vtt	11.9 KB
3. Connecting to Data Source in AML.mp4	19.7 MB
3. Connecting to Data Source in AML.vtt	3.7 KB
4. Creating Data Scheme in AML.mp4	28.2 MB
4. Creating Data Scheme in AML.vtt	6.3 KB
5. Invaild Value and Varible Target in AML.mp4	4.6 MB
5. Invaild Value and Varible Target in AML.vtt	1.1 KB
6. ML Models in AML.mp4	61.6 MB
6. ML Models in AML.vtt	12.7 KB
7. Manging ML Object in AML.mp4	12.6 MB
7. Manging ML Object in AML.vtt	2.6 KB
8. Creating DataSource Handson.mp4	109.2 MB
8. Creating DataSource Handson.vtt	11.5 KB
9. Creating DataSource Handson Continues.mp4	73.3 MB
9. Creating DataSource Handson Continues.vtt	8.1 KB
/9. Deep Learning Tutorials/
1. Introduction to Deep Learning.mp4	29.4 MB
1. Introduction to Deep Learning.vtt	5.1 KB
10. Data for Classifier.mp4	52.2 MB
10. Data for Classifier.vtt	5.4 KB
11. Implementing with Keras.mp4	47.8 MB
11. Implementing with Keras.vtt	3.8 KB
12. Values in Data Set.mp4	75.9 MB
12. Values in Data Set.vtt	6.3 KB
13. Components in Data Set.mp4	83.0 MB
13. Components in Data Set.vtt	6.9 KB
14. Models in Data Set.mp4	65.1 MB
14. Models in Data Set.vtt	5.9 KB
2. Structure of Neural Network.mp4	36.9 MB
2. Structure of Neural Network.vtt	5.1 KB
3. Moving Through Neural Network.mp4	39.9 MB
3. Moving Through Neural Network.vtt	6.0 KB
4. Types of Activation Functions.mp4	21.4 MB
4. Types of Activation Functions.vtt	3.3 KB
5. Optimizing Back Propagation.mp4	47.2 MB
5. Optimizing Back Propagation.vtt	7.0 KB
6. Briefing on Tensor Flow.mp4	37.5 MB
6. Briefing on Tensor Flow.vtt	5.2 KB
7. Installation of Tensor Flow.mp4	24.4 MB
7. Installation of Tensor Flow.vtt	2.8 KB
8. Implementatiion on Neural Package.mp4	85.8 MB
8. Implementatiion on Neural Package.vtt	7.0 KB
9. Implementatiion on Neural Package Continues.mp4	72.4 MB
9. Implementatiion on Neural Package Continues.vtt	7.6 KB
/
[CourseClub.NET].url	0.1 KB
[FCS Forum].url	0.1 KB
[FreeCourseSite.com].url	0.1 KB
Total files 1047