1. Machine Learning - Statistics Essentials/1. Machine Learning Introduction.mp420.06MB

1. Machine Learning - Statistics Essentials/10. Technical Terminology.mp454.82MB

1. Machine Learning - Statistics Essentials/11. Error of Observation and Non Observation.mp431.16MB

1. Machine Learning - Statistics Essentials/12. Systematic Sampling.mp454.93MB

1. Machine Learning - Statistics Essentials/13. Cluster Sampling.mp458.79MB

1. Machine Learning - Statistics Essentials/14. Statistics Data Types.mp425.59MB

1. Machine Learning - Statistics Essentials/15. Qualitative Data and Visualization.mp437.69MB

1. Machine Learning - Statistics Essentials/16. Machine Learning.mp456.07MB

1. Machine Learning - Statistics Essentials/17. Relative Frequency Probability.mp462.98MB

1. Machine Learning - Statistics Essentials/18. Joint Probability.mp485.96MB

1. Machine Learning - Statistics Essentials/19. Conditional Probability.mp442.78MB

1. Machine Learning - Statistics Essentials/2. Introduction to Machine Learning with Python.mp46.52MB

1. Machine Learning - Statistics Essentials/20. Concept of Independence.mp440.3MB

1. Machine Learning - Statistics Essentials/21. Total Probability.mp457.65MB

1. Machine Learning - Statistics Essentials/22. Random Variable.mp446.71MB

1. Machine Learning - Statistics Essentials/23. Probability Distribution.mp468.8MB

1. Machine Learning - Statistics Essentials/24. Cumulative Probability Distribution.mp437.58MB

1. Machine Learning - Statistics Essentials/25. Bernoulli Distribution.mp438.71MB

1. Machine Learning - Statistics Essentials/26. Gaussian Distribution.mp433.68MB

1. Machine Learning - Statistics Essentials/27. Geometric Distribution.mp433.2MB

1. Machine Learning - Statistics Essentials/28. Continuous and Normal Distribution.mp449.07MB

1. Machine Learning - Statistics Essentials/29. Mathematical Expression and Computation.mp433.82MB

1. Machine Learning - Statistics Essentials/3. Analytics in Machine Learning.mp447.03MB

1. Machine Learning - Statistics Essentials/30. Transpose of Matrix.mp446.05MB

1. Machine Learning - Statistics Essentials/31. Properties of Matrix.mp447.72MB

1. Machine Learning - Statistics Essentials/32. Determinants.mp447.64MB

1. Machine Learning - Statistics Essentials/33. Error Types.mp453.25MB

1. Machine Learning - Statistics Essentials/34. Critical Value Approach.mp457.08MB

1. Machine Learning - Statistics Essentials/35. Right and Left Sided Critical Approach.mp459.27MB

1. Machine Learning - Statistics Essentials/36. P-Value Approach.mp479.84MB

1. Machine Learning - Statistics Essentials/37. P-Value Approach Continues.mp455.8MB

1. Machine Learning - Statistics Essentials/38. Hypothesis Testing.mp443.49MB

1. Machine Learning - Statistics Essentials/39. Left Tail Test.mp422.9MB

1. Machine Learning - Statistics Essentials/4. Big Data Machine Learning.mp450.99MB

1. Machine Learning - Statistics Essentials/40. Two Tail Test.mp441.64MB

1. Machine Learning - Statistics Essentials/41. Confidence Interval.mp452.67MB

1. Machine Learning - Statistics Essentials/42. Example of Confidence Interval.mp462.96MB

1. Machine Learning - Statistics Essentials/43. Normal and Non Normal Distribution.mp432.45MB

1. Machine Learning - Statistics Essentials/44. Normality Test.mp445.72MB

1. Machine Learning - Statistics Essentials/45. Normality Test Continues.mp440.97MB

1. Machine Learning - Statistics Essentials/46. Determining the Transformation.mp422.14MB

1. Machine Learning - Statistics Essentials/47. T-Test.mp445.2MB

1. Machine Learning - Statistics Essentials/48. T-Test Continue.mp447.22MB

1. Machine Learning - Statistics Essentials/49. More on T-Test.mp455.52MB

1. Machine Learning - Statistics Essentials/5. Emerging Trends Machine Learning.mp472.39MB

1. Machine Learning - Statistics Essentials/50. Test of Independence.mp453.96MB

1. Machine Learning - Statistics Essentials/51. Example of Test of Independence.mp451.13MB

1. Machine Learning - Statistics Essentials/52. Goodness of Fit Test.mp440.22MB

1. Machine Learning - Statistics Essentials/53. Example of Goodness of Fit Test.mp437.93MB

1. Machine Learning - Statistics Essentials/54. Co-Variance.mp417.99MB

1. Machine Learning - Statistics Essentials/55. Co-Variance Continues.mp424.04MB

1. Machine Learning - Statistics Essentials/6. Data Mining.mp443.82MB

1. Machine Learning - Statistics Essentials/7. Data Mining Continues.mp467.73MB

1. Machine Learning - Statistics Essentials/8. Supervised and Unsupervised.mp445.4MB

1. Machine Learning - Statistics Essentials/9. Sampling Method in Machine Learning.mp431.14MB

10. Natural Language Processing (NLP) Tutorials/1. Intoroduction to NLP.mp432.7MB

10. Natural Language Processing (NLP) Tutorials/10. Stemming and Lemmatization Continues.mp461.22MB

10. Natural Language Processing (NLP) Tutorials/11. Convert Token No Stopwords.mp462.67MB

10. Natural Language Processing (NLP) Tutorials/12. Machine Learning Algorithms.mp460.01MB

10. Natural Language Processing (NLP) Tutorials/2. Text Preprocessing.mp439.41MB

10. Natural Language Processing (NLP) Tutorials/3. Feature Extraction.mp44.48MB

10. Natural Language Processing (NLP) Tutorials/4. NLP Installation.mp459.69MB

10. Natural Language Processing (NLP) Tutorials/5. NLP - Demo.mp489.44MB

10. Natural Language Processing (NLP) Tutorials/6. Replacing Contractions.mp4135.03MB

10. Natural Language Processing (NLP) Tutorials/7. Tokenize Dataset.mp469.46MB

10. Natural Language Processing (NLP) Tutorials/8. Remove Stopwords.mp468.24MB

10. Natural Language Processing (NLP) Tutorials/9. Stemming and Lemmatization.mp496.03MB

11. Bayesian Machine Learning AB Testing/1. Introduction to Bayesian Machine Learning.mp436.82MB

11. Bayesian Machine Learning AB Testing/2. Example of Bayesian Machine Learning.mp431.87MB

11. Bayesian Machine Learning AB Testing/3. Example of Bayesian Machine Learning Continues.mp436.13MB

11. Bayesian Machine Learning AB Testing/4. MCMC Module of PYMC Implementation.mp443.41MB

11. Bayesian Machine Learning AB Testing/5. Running the MCMC Module.mp442.54MB

11. Bayesian Machine Learning AB Testing/6. Multiple Variant Testing Using Hierarchial Model.mp445.95MB

11. Bayesian Machine Learning AB Testing/7. Example of Multiple Variant Testing.mp429.38MB

11. Bayesian Machine Learning AB Testing/8. Example of Multiple Variant Testing Continues.mp452.25MB

12. Machine Learning with R/1. Introduction to Machine Learning with Python.mp458.25MB

12. Machine Learning with R/10. 2.10 Problem and Solution.mp479.67MB

12. Machine Learning with R/100. Diagnostic Checking.mp460.55MB

12. Machine Learning with R/101. Forecasting Using Stock Price.mp4108.9MB

12. Machine Learning with R/102. Stock Price Index.mp499.87MB

12. Machine Learning with R/103. Stock Price Index Continues.mp495.16MB

12. Machine Learning with R/104. Prophet Stock.mp450.06MB

12. Machine Learning with R/105. Run Prophet Stock.mp478.21MB

12. Machine Learning with R/106. Time Series Data Denationalization.mp4101.32MB

12. Machine Learning with R/107. Time Series Data Denationalization Continues.mp478.48MB

12. Machine Learning with R/108. Average of Quarter Denationalization.mp4126.96MB

12. Machine Learning with R/109. Regression of Denationalization.mp4103.77MB

12. Machine Learning with R/11. Exponentiation Right to Left.mp453.17MB

12. Machine Learning with R/110. Gradient Boosting Machines.mp467MB

12. Machine Learning with R/111. Errors in Gradient Boosting Machines.mp457.6MB

12. Machine Learning with R/112. What is Error Rate in Gradient Boosting Machines.mp457.55MB

12. Machine Learning with R/113. Optimization Gradient Boosting Machines.mp451.82MB

12. Machine Learning with R/114. Gradient Boosting Trees (GBT).mp438.39MB

12. Machine Learning with R/115. Dataset Boosting in Gradient.mp496.43MB

12. Machine Learning with R/116. Example of Dataset Boosting in Gradient.mp495.79MB

12. Machine Learning with R/117. Example of Dataset Boosting in Gradient Continues.mp4113.25MB

12. Machine Learning with R/118. Market Basket Analysis Association Rules.mp498.38MB

12. Machine Learning with R/119. Market Basket Analysis Association Rules Continues.mp478.3MB

12. Machine Learning with R/12. 2.13 Avoiding Some Common Mistakes.mp469.82MB

12. Machine Learning with R/120. Market Basket Analysis Interpretation.mp450.28MB

12. Machine Learning with R/121. Implementation of Market Basket Analysis.mp430.32MB

12. Machine Learning with R/122. Example of Market Basket Analysis.mp484.78MB

12. Machine Learning with R/123. Datamining in Market Basket Analysis.mp485.97MB

12. Machine Learning with R/124. Market Basket Analysis Using Rstudio.mp478.53MB

12. Machine Learning with R/125. Market Basket Analysis Using Rstudio Continues.mp494.13MB

12. Machine Learning with R/126. More on Rstudio in Market Analysis.mp4122.52MB

12. Machine Learning with R/127. New Development in Machine Learning.mp493.23MB

12. Machine Learning with R/128. Data Scientist in Machine Learnirng.mp474.05MB

12. Machine Learning with R/129. Types of Detection in Machine Learning.mp4102.86MB

12. Machine Learning with R/13. Simple Linear Regression.mp468.16MB

12. Machine Learning with R/130. Example of New Development in Machine Learning.mp479.23MB

12. Machine Learning with R/131. Example of New Development in Machine Learning Continues.mp453.15MB

12. Machine Learning with R/14. Simple Linear Regression Continues.mp439.71MB

12. Machine Learning with R/15. What is Rsquare.mp477.58MB

12. Machine Learning with R/16. Standard Error.mp454.56MB

12. Machine Learning with R/17. General Statistics.mp452.34MB

12. Machine Learning with R/18. General Statistics Continues.mp450.23MB

12. Machine Learning with R/19. Simple Linear Regression and More of Statistics.mp469.26MB

12. Machine Learning with R/2. How do Machine Learn.mp451.66MB

12. Machine Learning with R/20. Open the Studio.mp440.4MB

12. Machine Learning with R/21. What is R Square.mp479.51MB

12. Machine Learning with R/22. What is STD Error.mp455.37MB

12. Machine Learning with R/23. Reject Null Hypothesis.mp484.23MB

12. Machine Learning with R/24. Variance Covariance and Correlation.mp481.89MB

12. Machine Learning with R/25. Root names and Types of Distribution Function.mp471.71MB

12. Machine Learning with R/26. Generating Random Numbers and Combination Function.mp463.1MB

12. Machine Learning with R/27. Probabilities for Discrete Distribution Function.mp483.57MB

12. Machine Learning with R/28. Quantile Function and Poison Distribution.mp477.31MB

12. Machine Learning with R/29. Students T Distribution, Hypothesis and Example.mp463.21MB

12. Machine Learning with R/3. Steps to Apply Machine Learning.mp445.69MB

12. Machine Learning with R/30. Chai-Square Distribution.mp441.33MB

12. Machine Learning with R/31. Data Visualization.mp477.8MB

12. Machine Learning with R/32. More on Data Visualization.mp470.53MB

12. Machine Learning with R/33. Multiple Linear Regression.mp490.37MB

12. Machine Learning with R/34. Multiple Linear Regression Continues.mp469.98MB

12. Machine Learning with R/35. Regression Variables.mp4101.45MB

12. Machine Learning with R/36. Generalized Linear Model.mp493.7MB

12. Machine Learning with R/37. Generalized Least Square.mp488.79MB

12. Machine Learning with R/38. KNN- Various Methods of Distance Measurements.mp452.96MB

12. Machine Learning with R/39. Overview of KNN- (Steps involved).mp471.1MB

12. Machine Learning with R/4. Regression and Classification Problems.mp462.38MB

12. Machine Learning with R/40. Data normalization and prediction on Test Data.mp486.41MB

12. Machine Learning with R/41. Improvement of Model Performance and ROC.mp485.09MB

12. Machine Learning with R/42. Decision Tree Classifier.mp457.8MB

12. Machine Learning with R/43. More on Decision Tree Classifier.mp481.5MB

12. Machine Learning with R/44. Pruning of Decision Trees.mp483.84MB

12. Machine Learning with R/45. Decision Tree Remaining.mp461.11MB

12. Machine Learning with R/46. Decision Tree Remaining Continues.mp446.7MB

12. Machine Learning with R/47. General concept of Random Forest.mp464.3MB

12. Machine Learning with R/48. Ada Boosting and Ensemble Learning.mp495.21MB

12. Machine Learning with R/49. Data Visualization and Preparation.mp489.28MB

12. Machine Learning with R/5. Basic Data Manipulation in R.mp471.68MB

12. Machine Learning with R/50. Tuning Random Forest Model.mp463.4MB

12. Machine Learning with R/51. Evaluation of Random Forest Model Performance.mp465.88MB

12. Machine Learning with R/52. Introduction to Kmeans Clustering.mp475.07MB

12. Machine Learning with R/53. Kmeans Elbow Point and Dataset.mp490.51MB

12. Machine Learning with R/54. Example of Kmeans Dataset.mp4122.65MB

12. Machine Learning with R/55. Creating a Graph for Kmeans Clustering.mp4126.69MB

12. Machine Learning with R/56. Creating a Graph for Kmeans Clustering Continues.mp490.64MB

12. Machine Learning with R/57. Aggregation Function of Clustering.mp478.46MB

12. Machine Learning with R/58. Conditional Probability with Bayes Algorithm.mp482.98MB

12. Machine Learning with R/59. Venn Diagram Naive Bayes Classification.mp461.65MB

12. Machine Learning with R/6. More on Data Manipulation in R.mp462.14MB

12. Machine Learning with R/60. Component OF Bayes Theorem using Frequency Table.mp486.98MB

12. Machine Learning with R/61. Naive Bayes Classification Algorithm and Laplace Estimator.mp470.4MB

12. Machine Learning with R/62. Example of Naive Bayes Classification.mp481.66MB

12. Machine Learning with R/63. Example of Naive Bayes Classification Continues.mp4100.12MB

12. Machine Learning with R/64. Spam and Ham Messages in Word Cloud.mp490.21MB

12. Machine Learning with R/65. Implementation of Dictionary and Document Term Matrix.mp481.48MB

12. Machine Learning with R/66. Executes the Function Naive Bayes.mp489.85MB

12. Machine Learning with R/67. Support Vector Machine with Black Box Method.mp459.63MB

12. Machine Learning with R/68. Linearly and Non- Linearly Support Vector Machine.mp452.99MB

12. Machine Learning with R/69. Kernal Trick.mp457.19MB

12. Machine Learning with R/7. Basic Data Manipulation in R - Practical.mp471.74MB

12. Machine Learning with R/70. Gaussian RBF Kernal and OCR with SVMs.mp481.18MB

12. Machine Learning with R/71. Examples of Gaussian RBF Kernal and OCR with SVMs.mp476.93MB

12. Machine Learning with R/72. Summary of Support Vector Machine.mp478.27MB

12. Machine Learning with R/73. Feature Selection Dimension Reduction Technique.mp486.7MB

12. Machine Learning with R/74. Feature Extraction Dimension Reduction Technique.mp482.53MB

12. Machine Learning with R/75. Dimension Reduction Technique Example.mp488.1MB

12. Machine Learning with R/76. Dimension Reduction Technique Example Continues.mp484.19MB

12. Machine Learning with R/77. Introduction Principal Component Analysis.mp466.74MB

12. Machine Learning with R/78. Steps of PCA.mp461.43MB

12. Machine Learning with R/79. Steps of PCA Continues.mp459.88MB

12. Machine Learning with R/8. Create a Vector.mp463.58MB

12. Machine Learning with R/80. Eigen Values.mp437.75MB

12. Machine Learning with R/81. Eigen Vectors.mp439.57MB

12. Machine Learning with R/82. Principal Component Analysis using Pr-Comp.mp4104.06MB

12. Machine Learning with R/83. Principal Component Analysis using Pr-Comp Continues.mp476.54MB

12. Machine Learning with R/84. C Bind Type in PCA.mp489.65MB

12. Machine Learning with R/85. R Type Model.mp4121.3MB

12. Machine Learning with R/86. Black Box Method in Neural Network.mp487.36MB

12. Machine Learning with R/87. Characteristics of a Neural Networks.mp472.69MB

12. Machine Learning with R/88. Network Topology of a Neural Networks.mp470.49MB

12. Machine Learning with R/89. Weight Adjustment and Case Update.mp480.93MB

12. Machine Learning with R/9. 2.7 Problem and Solution.mp469.89MB

12. Machine Learning with R/90. Introduction Model Building in R.mp4100.93MB

12. Machine Learning with R/91. Installing the Package of Model Building in R.mp488.49MB

12. Machine Learning with R/92. Nodes in Model Building in R.mp470.8MB

12. Machine Learning with R/93. Example of Model Building in R.mp481.6MB

12. Machine Learning with R/94. Time Series Analysis.mp468.49MB

12. Machine Learning with R/95. Pattern in Time Series Data.mp451.02MB

12. Machine Learning with R/96. Time Series Modelling.mp455.94MB

12. Machine Learning with R/97. Moving Average Model.mp467.21MB

12. Machine Learning with R/98. Auto Correlation Function.mp443.08MB

12. Machine Learning with R/99. Inference of ACF and PFCF.mp445.22MB

13. BIP - Business Intelligence Publisher using Siebel/1. Introduction to BIP.mp421MB

13. BIP - Business Intelligence Publisher using Siebel/10. Siebel Applets ‚ Business Obejct and Business Components Part 2.mp490.35MB

13. BIP - Business Intelligence Publisher using Siebel/11. IntegrationObjectsANDIntegrationObjectComponents.mp4101.06MB

13. BIP - Business Intelligence Publisher using Siebel/12. Siebel Views and View Associations to Reports.mp482.77MB

13. BIP - Business Intelligence Publisher using Siebel/13. Siebel HI-OpenUI framworks for BIP Reports and demo of AddIn.mp442.71MB

13. BIP - Business Intelligence Publisher using Siebel/14. Process_Flow_Overview.mp451.8MB

13. BIP - Business Intelligence Publisher using Siebel/15. Process_Flow_ConnectedMode.mp442.29MB

13. BIP - Business Intelligence Publisher using Siebel/16. Process_Flow_DisconnectedMode.mp442.12MB

13. BIP - Business Intelligence Publisher using Siebel/17. Siebel Report Business Service.mp477.34MB

13. BIP - Business Intelligence Publisher using Siebel/2. User Types.mp410.38MB

13. BIP - Business Intelligence Publisher using Siebel/3. Running Modes.mp433.52MB

13. BIP - Business Intelligence Publisher using Siebel/4. Learning about BIP Add-Ins.mp459.81MB

13. BIP - Business Intelligence Publisher using Siebel/5. BIP_Into_5_BIP_AddIn2 and BIP_Into_6.mp464.35MB

13. BIP - Business Intelligence Publisher using Siebel/6. BIP_Into_7_Customized Reports Overview.mp459.34MB

13. BIP - Business Intelligence Publisher using Siebel/7. BIP_Into_8_Developing Reports Overview.mp419.14MB

13. BIP - Business Intelligence Publisher using Siebel/8. Showing Report Views on Application.mp4110.09MB

13. BIP - Business Intelligence Publisher using Siebel/9. Siebel Applets ‚ Business Obejct and Business Components Part 1.mp487.33MB

14. BI - Business Intelligence/1. BI Intro,definition.mp451.19MB

14. BI - Business Intelligence/10. planning deliverables,stage 3.mp434.1MB

14. BI - Business Intelligence/100. Regression Model(Continues).mp444.73MB

14. BI - Business Intelligence/101. Market Basket Analysis Applications.mp446.71MB

14. BI - Business Intelligence/102. Market Basket Analysis Applications(Continues).mp435.93MB

14. BI - Business Intelligence/11. Project Requirement,Data Analysis,Application part 1.mp452.97MB

14. BI - Business Intelligence/12. Project Requirement,Data Analysis,Application part 2.mp465.11MB

14. BI - Business Intelligence/13. Project Requirement,Data Analysis,Application part 3.mp446.98MB

14. BI - Business Intelligence/14. Meta Data.mp411.09MB

14. BI - Business Intelligence/15. data standardisation,meta data,etl,business analysis part 1.mp461.46MB

14. BI - Business Intelligence/16. data standardisation,meta data,etl,business analysis part 2.mp451.14MB

14. BI - Business Intelligence/17. data standardisation,meta data,etl,business analysis part 3.mp420.52MB

14. BI - Business Intelligence/18. ETL Design,Meta DATA ,STAGE 5 CONSTRUCTION DEVELOPMENT RECONCILATION Part 1.mp447.14MB

14. BI - Business Intelligence/19. ETL Design,Meta DATA ,STAGE 5 CONSTRUCTION DEVELOPMENT RECONCILATION Part 2.mp465.35MB

14. BI - Business Intelligence/2. multidimensional db part 1.mp450.11MB

14. BI - Business Intelligence/20. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 1.mp446.66MB

14. BI - Business Intelligence/21. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 2.mp417.37MB

14. BI - Business Intelligence/22. ETL,APPLICATION dEVELOPMENT,DATA gaps,meta data repository,deployment Part 3.mp460.84MB

14. BI - Business Intelligence/23. database & recovery,release evaluation.mp430.53MB

14. BI - Business Intelligence/24. post implementation review,toyota case.mp444.88MB

14. BI - Business Intelligence/25. frame work for BI Part 1.mp458.71MB

14. BI - Business Intelligence/26. frame work for BI Part 2.mp456.09MB

14. BI - Business Intelligence/27. frame work for BI Part 3.mp433.11MB

14. BI - Business Intelligence/28. frame work for BI Part 4.mp438.18MB

14. BI - Business Intelligence/29. strategic imperitive of BI Part 1.mp449.28MB

14. BI - Business Intelligence/3. multidimensional db part 2.mp461.19MB

14. BI - Business Intelligence/30. strategic imperitive of BI Part 2.mp441.76MB

14. BI - Business Intelligence/31. Target System.mp447.82MB

14. BI - Business Intelligence/32. Data warehouse and ETL.mp433.03MB

14. BI - Business Intelligence/33. Facebook dataspace management with open source tools.mp438.35MB

14. BI - Business Intelligence/34. Agile Development Process.mp434.55MB

14. BI - Business Intelligence/35. Agile Development Process Continues.mp444.66MB

14. BI - Business Intelligence/36. Challenges on dash board.mp432.28MB

14. BI - Business Intelligence/37. Building Users Expert Profile.mp462.77MB

14. BI - Business Intelligence/38. Semantic Technologies.mp453.11MB

14. BI - Business Intelligence/39. Semantic Tools.mp453.66MB

14. BI - Business Intelligence/4. multidimensional db part 3.mp456.1MB

14. BI - Business Intelligence/40. BI Algorithm By Example.mp442.01MB

14. BI - Business Intelligence/41. Benefits of BI.mp427.67MB

14. BI - Business Intelligence/42. Benefits of BI Continues.mp443.66MB

14. BI - Business Intelligence/43. Amazon.com and Net Flix.mp438.96MB

14. BI - Business Intelligence/44. What is Information Governance.mp449.97MB

14. BI - Business Intelligence/45. Other BI Applications are used to store.mp445.27MB

14. BI - Business Intelligence/46. Designing and Implementing BI Program.mp446.72MB

14. BI - Business Intelligence/47. ETL.mp437.37MB

14. BI - Business Intelligence/48. ETL Continues.mp430.78MB

14. BI - Business Intelligence/49. Loading.mp435.06MB

14. BI - Business Intelligence/5. dbms platform.mp411.8MB

14. BI - Business Intelligence/50. Type 2 Dimension.mp451.92MB

14. BI - Business Intelligence/51. Loading Fact Tables.mp447.39MB

14. BI - Business Intelligence/52. Genearl Idea.mp441.4MB

14. BI - Business Intelligence/53. Conceptual Model.mp436.9MB

14. BI - Business Intelligence/54. Conceptual Model Continues.mp449.97MB

14. BI - Business Intelligence/55. On Going Or Future Works.mp451.43MB

14. BI - Business Intelligence/56. Why Meta Data.mp442.77MB

14. BI - Business Intelligence/57. Essentials Capabilities.mp427.42MB

14. BI - Business Intelligence/58. Common Warehouse Metamodels.mp430.76MB

14. BI - Business Intelligence/59. Data Advantage Group.mp454MB

14. BI - Business Intelligence/6. technical non technical infrastructre part 1.mp443.12MB

14. BI - Business Intelligence/60. DBMS Meta Data Tips.mp464.31MB

14. BI - Business Intelligence/61. For Building The Dataware house(Extraction Team).mp451.68MB

14. BI - Business Intelligence/62. Meta Data Essentials For IT.mp448.65MB

14. BI - Business Intelligence/63. Business Metadata.mp441.09MB

14. BI - Business Intelligence/64. Business Meta Data (Continues).mp424.21MB

14. BI - Business Intelligence/65. Project Planning.mp456.86MB

14. BI - Business Intelligence/66. Project Planning (Continues).mp431.2MB

14. BI - Business Intelligence/67. Deployment Process.mp474.44MB

14. BI - Business Intelligence/68. Chapter Outline.mp439.34MB

14. BI - Business Intelligence/69. Break-Even Analysis.mp437.84MB

14. BI - Business Intelligence/7. technical non technical infrastructre part 2.mp451.18MB

14. BI - Business Intelligence/70. Examples Of Break-Even Analysis.mp443.71MB

14. BI - Business Intelligence/71. Multivirate Analysis.mp449.96MB

14. BI - Business Intelligence/72. Multivirate Analysis (Continues).mp430.93MB

14. BI - Business Intelligence/73. Graphs.mp441.52MB

14. BI - Business Intelligence/74. Why Meta Data Is Important.mp439.52MB

14. BI - Business Intelligence/75. System Development.mp429.91MB

14. BI - Business Intelligence/76. Project Risk Assesment Factors.mp446.31MB

14. BI - Business Intelligence/77. Managing Project Time.mp436.94MB

14. BI - Business Intelligence/78. Prototyping Benefits.mp461.45MB

14. BI - Business Intelligence/79. Incremental Development.mp457.96MB

14. BI - Business Intelligence/8. change control board part 1.mp457.25MB

14. BI - Business Intelligence/80. Incremental Development(Continues).mp447.9MB

14. BI - Business Intelligence/81. What is Cluster Analysis.mp448.92MB

14. BI - Business Intelligence/82. Types Of Clusters.mp449.3MB

14. BI - Business Intelligence/83. Cluster Benefits.mp435.65MB

14. BI - Business Intelligence/84. Kmeans Clustering Method.mp485.92MB

14. BI - Business Intelligence/85. What Is The Problem With PAM.mp461.58MB

14. BI - Business Intelligence/86. BIRCH (1996).mp456.65MB

14. BI - Business Intelligence/87. Density Rechable And Density Conected.mp452.84MB

14. BI - Business Intelligence/88. Denclue Technical Issues.mp465.83MB

14. BI - Business Intelligence/89. The Wave Cluster Algorithm.mp448.29MB

14. BI - Business Intelligence/9. change control board part 2.mp448.58MB

14. BI - Business Intelligence/90. More On Conceptual Clustering.mp460.84MB

14. BI - Business Intelligence/91. Clustering in Quest.mp458.39MB

14. BI - Business Intelligence/92. Why Constraints Based Cluster Analysis.mp451.78MB

14. BI - Business Intelligence/93. What Is Outlier Discovery.mp441.92MB

14. BI - Business Intelligence/94. Segmentation In Data Mining.mp446.47MB

14. BI - Business Intelligence/95. Bottle Neck Of GSP & Spade.mp451.55MB

14. BI - Business Intelligence/96. Why Deal with Sequential Data.mp441.58MB

14. BI - Business Intelligence/97. Algorithm Definition.mp441.85MB

14. BI - Business Intelligence/98. Introduction To Regression Analysis.mp435.34MB

14. BI - Business Intelligence/99. Regression Model.mp453.02MB

2. Machine Learning with Tensorflow for Beginners/1. Introduction to Machine Learning with Tensorflow.mp417.82MB

2. Machine Learning with Tensorflow for Beginners/10. Understanding what Anaconda cloud is.mp480.82MB

2. Machine Learning with Tensorflow for Beginners/100. Run Optimizer.mp413.63MB

2. Machine Learning with Tensorflow for Beginners/101. Create a Range.mp451.4MB

2. Machine Learning with Tensorflow for Beginners/102. Introduction to Neural Networks.mp45.61MB

2. Machine Learning with Tensorflow for Beginners/103. Basic-Concepts.mp4101.53MB

2. Machine Learning with Tensorflow for Beginners/104. Activative Functions.mp499.94MB

2. Machine Learning with Tensorflow for Beginners/105. Activative Functions Input to Output.mp457.72MB

2. Machine Learning with Tensorflow for Beginners/106. Classification Functions.mp461.74MB

2. Machine Learning with Tensorflow for Beginners/107. Tensorflow-Playground.mp4136.67MB

2. Machine Learning with Tensorflow for Beginners/108. Mnist-Dataset.mp454.38MB

2. Machine Learning with Tensorflow for Beginners/109. Mnist-Dataset Continue.mp493.75MB

2. Machine Learning with Tensorflow for Beginners/11. Installation of Anaconda for Windows.mp450.24MB

2. Machine Learning with Tensorflow for Beginners/110. More on Mnist-Dataset.mp481.92MB

2. Machine Learning with Tensorflow for Beginners/12. Installation of Anaconda in Linux.mp429.15MB

2. Machine Learning with Tensorflow for Beginners/13. Using the Jupyter notebook.mp426.08MB

2. Machine Learning with Tensorflow for Beginners/14. Getting started with Anaconda.mp4136.15MB

2. Machine Learning with Tensorflow for Beginners/15. Determining options for Cloudberry.mp439.51MB

2. Machine Learning with Tensorflow for Beginners/16. Introduction to Third Party Libraries.mp48.19MB

2. Machine Learning with Tensorflow for Beginners/18. Numpy-Array Continue.mp484.07MB

2. Machine Learning with Tensorflow for Beginners/19. Arrays.mp4110.36MB

2. Machine Learning with Tensorflow for Beginners/2. Understanding Machine Learning.mp415.54MB

2. Machine Learning with Tensorflow for Beginners/20. Arrays Continue.mp455.4MB

2. Machine Learning with Tensorflow for Beginners/21. Indexing.mp463.28MB

2. Machine Learning with Tensorflow for Beginners/22. Indexing Continue.mp485.08MB

2. Machine Learning with Tensorflow for Beginners/23. Universal Functions.mp4109.59MB

2. Machine Learning with Tensorflow for Beginners/24. Introoduction to Pandas.mp426.06MB

2. Machine Learning with Tensorflow for Beginners/25. Pandas Series.mp433.47MB

2. Machine Learning with Tensorflow for Beginners/26. Pandas Series Continue.mp438.07MB

2. Machine Learning with Tensorflow for Beginners/27. Import Randin.mp464.96MB

2. Machine Learning with Tensorflow for Beginners/28. Import Randin Continue.mp472.37MB

2. Machine Learning with Tensorflow for Beginners/29. Paratmeters.mp487.75MB

2. Machine Learning with Tensorflow for Beginners/3. How do Machines Learns.mp451.9MB

2. Machine Learning with Tensorflow for Beginners/30. Indexing and Database.mp437.9MB

2. Machine Learning with Tensorflow for Beginners/31. Missing Data.mp430.3MB

2. Machine Learning with Tensorflow for Beginners/32. Missing Data-Groupby.mp420.18MB

2. Machine Learning with Tensorflow for Beginners/33. Missing Data-Groupby Continue.mp426.92MB

2. Machine Learning with Tensorflow for Beginners/34. Concat-Merge-Join.mp479.93MB

2. Machine Learning with Tensorflow for Beginners/35. Operations.mp448.08MB

2. Machine Learning with Tensorflow for Beginners/36. Import-Export.mp4104.66MB

2. Machine Learning with Tensorflow for Beginners/37. Python Visualisation.mp449.04MB

2. Machine Learning with Tensorflow for Beginners/38. Mat Plotting.mp463.42MB

2. Machine Learning with Tensorflow for Beginners/39. Multiple Plot Subsections.mp462.39MB

2. Machine Learning with Tensorflow for Beginners/4. Uses of Machine Learning.mp430.21MB

2. Machine Learning with Tensorflow for Beginners/40. API Functionality.mp464.75MB

2. Machine Learning with Tensorflow for Beginners/41. Title of the Plot.mp491.75MB

2. Machine Learning with Tensorflow for Beginners/42. Change Size of Articles.mp459.75MB

2. Machine Learning with Tensorflow for Beginners/43. Two Different Crops.mp454.92MB

2. Machine Learning with Tensorflow for Beginners/44. Mat Plotting Label.mp449.35MB

2. Machine Learning with Tensorflow for Beginners/45. Marker Color.mp472.66MB

2. Machine Learning with Tensorflow for Beginners/46. Create a New Dataframe.mp440.21MB

2. Machine Learning with Tensorflow for Beginners/47. Change the Style.mp444.45MB

2. Machine Learning with Tensorflow for Beginners/48. Index and Value.mp441.35MB

2. Machine Learning with Tensorflow for Beginners/49. Seaborn-Statistical Data Visualization.mp459.06MB

2. Machine Learning with Tensorflow for Beginners/5. Examples with tensorflow by Google.mp457.34MB

2. Machine Learning with Tensorflow for Beginners/50. seaborn library.mp495.97MB

2. Machine Learning with Tensorflow for Beginners/51. Jointplot.mp481.97MB

2. Machine Learning with Tensorflow for Beginners/52. Pairplot.mp4109.81MB

2. Machine Learning with Tensorflow for Beginners/53. Barplot.mp497.54MB

2. Machine Learning with Tensorflow for Beginners/54. Boxplot.mp449.36MB

2. Machine Learning with Tensorflow for Beginners/55. Stripplot.mp478.06MB

2. Machine Learning with Tensorflow for Beginners/56. Matrix.mp492.83MB

2. Machine Learning with Tensorflow for Beginners/57. Matrix Continue.mp433.32MB

2. Machine Learning with Tensorflow for Beginners/58. Grid.mp4110.79MB

2. Machine Learning with Tensorflow for Beginners/59. Grid Continue.mp456.6MB

2. Machine Learning with Tensorflow for Beginners/6. Setting up the Workstation.mp47.06MB

2. Machine Learning with Tensorflow for Beginners/60. Style.mp414.89MB

2. Machine Learning with Tensorflow for Beginners/61. Python Libraries Conclusion.mp413.05MB

2. Machine Learning with Tensorflow for Beginners/62. Introduction To Conda Envirement.mp420.66MB

2. Machine Learning with Tensorflow for Beginners/63. Scikit Learn.mp417.29MB

2. Machine Learning with Tensorflow for Beginners/64. Scikit Learn Continue.mp441.75MB

2. Machine Learning with Tensorflow for Beginners/65. Datasets.mp430.21MB

2. Machine Learning with Tensorflow for Beginners/66. California Dataset.mp460.44MB

2. Machine Learning with Tensorflow for Beginners/67. Data Visualization.mp488.53MB

2. Machine Learning with Tensorflow for Beginners/68. Datavisualization Continue.mp455.48MB

2. Machine Learning with Tensorflow for Beginners/69. Downloading a Test Data.mp490.58MB

2. Machine Learning with Tensorflow for Beginners/7. Understanding program languages.mp46.48MB

2. Machine Learning with Tensorflow for Beginners/70. Population Parameter.mp478.79MB

2. Machine Learning with Tensorflow for Beginners/71. Processing.mp4103.57MB

2. Machine Learning with Tensorflow for Beginners/72. Null Values with Median Value.mp480.14MB

2. Machine Learning with Tensorflow for Beginners/73. Replace Missing Values.mp432.48MB

2. Machine Learning with Tensorflow for Beginners/74. Label Enconder.mp426.02MB

2. Machine Learning with Tensorflow for Beginners/75. Import Labelencoder.mp490.69MB

2. Machine Learning with Tensorflow for Beginners/76. Custom Transformation.mp428.24MB

2. Machine Learning with Tensorflow for Beginners/77. Transformer Custom Transformer.mp456MB

2. Machine Learning with Tensorflow for Beginners/78. Housing with Custom Colums.mp457.03MB

2. Machine Learning with Tensorflow for Beginners/79. Numeric Hosing Data.mp4120.21MB

2. Machine Learning with Tensorflow for Beginners/8. Understanding and Functions of Jupyter.mp465.23MB

2. Machine Learning with Tensorflow for Beginners/80. Liner Regression.mp449.63MB

2. Machine Learning with Tensorflow for Beginners/81. Fine Tuning Model.mp441.43MB

2. Machine Learning with Tensorflow for Beginners/82. Fine Tuning Model Continue.mp457.98MB

2. Machine Learning with Tensorflow for Beginners/83. Quick-Recap.mp45.35MB

2. Machine Learning with Tensorflow for Beginners/84. Tensorflow.mp457.75MB

2. Machine Learning with Tensorflow for Beginners/85. Tensorflow-Hello-World.mp454.6MB

2. Machine Learning with Tensorflow for Beginners/86. Basic Ops.mp478.34MB

2. Machine Learning with Tensorflow for Beginners/87. Basic Ops Continue.mp470.26MB

2. Machine Learning with Tensorflow for Beginners/88. More on Basic Ops.mp467.83MB

2. Machine Learning with Tensorflow for Beginners/89. Eager-Mode.mp448.81MB

2. Machine Learning with Tensorflow for Beginners/9. Learning of Jupyter installation.mp45.03MB

2. Machine Learning with Tensorflow for Beginners/90. Concept.mp437.51MB

2. Machine Learning with Tensorflow for Beginners/91. Linear-Regression.mp425.28MB

2. Machine Learning with Tensorflow for Beginners/92. Linear-Model.mp445.39MB

2. Machine Learning with Tensorflow for Beginners/93. Matrix Multiplication Function.mp475.5MB

2. Machine Learning with Tensorflow for Beginners/94. Practice for a Simple Linear Model.mp424.42MB

2. Machine Learning with Tensorflow for Beginners/95. Cost Function.mp423MB

2. Machine Learning with Tensorflow for Beginners/96. Creative Optimizer.mp436.16MB

2. Machine Learning with Tensorflow for Beginners/97. RR Input and Output Value.mp427.46MB

2. Machine Learning with Tensorflow for Beginners/98. Logistic-Regression.mp451.55MB

2. Machine Learning with Tensorflow for Beginners/99. Global Variabales Initializer.mp436.5MB

3. Machine Learning Project #1 - Shipping and Time Estimation/1. Introduction to Shipping and pricing.mp425.71MB

3. Machine Learning Project #1 - Shipping and Time Estimation/10. Demand Forecasting.mp485.19MB

3. Machine Learning Project #1 - Shipping and Time Estimation/11. Distribution of Attributes.mp463.71MB

3. Machine Learning Project #1 - Shipping and Time Estimation/12. Spending Distribution.mp482.72MB

3. Machine Learning Project #1 - Shipping and Time Estimation/13. Normalization and Discretization.mp4119.5MB

3. Machine Learning Project #1 - Shipping and Time Estimation/2. Inventory Status.mp4104.65MB

3. Machine Learning Project #1 - Shipping and Time Estimation/3. Defining Data Type.mp495.45MB

3. Machine Learning Project #1 - Shipping and Time Estimation/4. Data for Validation.mp4103.3MB

3. Machine Learning Project #1 - Shipping and Time Estimation/5. Finding the Corelation.mp472.68MB

3. Machine Learning Project #1 - Shipping and Time Estimation/6. Density for Numeric Attribute.mp487.96MB

3. Machine Learning Project #1 - Shipping and Time Estimation/7. Method for Train Control.mp450.5MB

3. Machine Learning Project #1 - Shipping and Time Estimation/8. Assigning a Training Set.mp4125.2MB

3. Machine Learning Project #1 - Shipping and Time Estimation/9. Mean Absolute Error.mp471.41MB

4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/1. Introduction to Supply Chain.mp4100.34MB

4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/2. G Plot of Heatmap.mp478.74MB

4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/3. Checking the Function Argument.mp4121.19MB

4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/4. Heatmap for Discretized Dataset.mp488.57MB

4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/5. Distinguished Methods with Single.mp443.58MB

4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/6. Analyzing both the Plots.mp472.83MB

4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/7. Defining the Lengths.mp4101.48MB

4. Machine Learning Project #2 - Supply Chain-Demand Trends Analysis/8. Using Different Clusters.mp454.16MB

5. Machine Learning Project #3 - Predicting Prices using Regression/1. Introduction to Predicting Prices Using Regression.mp458.91MB

5. Machine Learning Project #3 - Predicting Prices using Regression/10. Replacing Features with Values.mp483.71MB

5. Machine Learning Project #3 - Predicting Prices using Regression/11. Assigning Quantatative Variables.mp445.85MB

5. Machine Learning Project #3 - Predicting Prices using Regression/12. Converting Columns to Cordinal Forms.mp448.87MB

5. Machine Learning Project #3 - Predicting Prices using Regression/13. Evaluating the Garage Finish Colummn.mp466.18MB

5. Machine Learning Project #3 - Predicting Prices using Regression/14. Checking Shape of Data Frame.mp414.86MB

5. Machine Learning Project #3 - Predicting Prices using Regression/15. Spliting Data to Train and Test.mp468.83MB

5. Machine Learning Project #3 - Predicting Prices using Regression/16. Algorithm for Predicting Test Values.mp428MB

5. Machine Learning Project #3 - Predicting Prices using Regression/2. Proximity to Various Conditions.mp464.34MB

5. Machine Learning Project #3 - Predicting Prices using Regression/3. Number of Fire Places.mp430.23MB

5. Machine Learning Project #3 - Predicting Prices using Regression/4. Adding the Test Value.mp482.62MB

5. Machine Learning Project #3 - Predicting Prices using Regression/5. Index to the ID Column.mp468.2MB

5. Machine Learning Project #3 - Predicting Prices using Regression/6. Model on Data Set.mp482.18MB

5. Machine Learning Project #3 - Predicting Prices using Regression/7. Missing Value Imputation.mp456.37MB

5. Machine Learning Project #3 - Predicting Prices using Regression/8. Substituting Features with Value.mp491.78MB

5. Machine Learning Project #3 - Predicting Prices using Regression/9. Imputing a Row using at Command.mp471.67MB

6. Machine Learning Project #4 - Banking and Credit Frauds/1. Introduction to Banking System.mp417.11MB

6. Machine Learning Project #4 - Banking and Credit Frauds/2. Laon Status Grade.mp493.48MB

6. Machine Learning Project #4 - Banking and Credit Frauds/3. Logistic Regression and Logistic Question.mp464.52MB

6. Machine Learning Project #4 - Banking and Credit Frauds/4. Beta Value.mp448.28MB

6. Machine Learning Project #4 - Banking and Credit Frauds/5. Predict Value.mp477.82MB

6. Machine Learning Project #4 - Banking and Credit Frauds/6. Performance Value.mp463.65MB

6. Machine Learning Project #4 - Banking and Credit Frauds/7. Fals Positive Rate.mp443.37MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/1. Introduction to Fraud Detection in Credit Payments.mp417.35MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/10. VRS.mp4107.46MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/11. CRS Efficiency and Efficiency.mp453.09MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/2. Installation of Packages.mp472.81MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/3. Risk Analytics.mp482.51MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/4. Trading Companies and Stocks.mp497.65MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/5. DEA with Input or Profit and Loss.mp487.78MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/6. Efficiency Profit and Loss.mp464.71MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/7. Rank Functions.mp476.44MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/8. RHS Constaints.mp489.36MB

7. Machine Learning Project #5 - Fraud Detection in Credit Payments/9. Profit and Loss Report.mp473.11MB

8. AWS Machine Learning/1. Introduction to Amazon Machine Learning (AML).mp438.18MB

8. AWS Machine Learning/10. Example of Data Insight In AML.mp466.85MB

8. AWS Machine Learning/11. More on Data Insight In AML.mp454.57MB

8. AWS Machine Learning/12. ML Model Example in Data Sources.mp490.66MB

8. AWS Machine Learning/13. Creating ML Model Evaluating.mp484.6MB

8. AWS Machine Learning/14. Advanced Setting In ML Model.mp438.46MB

8. AWS Machine Learning/15. Creating ML Model for Batch Prediction.mp484.89MB

8. AWS Machine Learning/16. Batch Prediction Result.mp447.61MB

8. AWS Machine Learning/17. Overvies of ML Model Handson.mp465.33MB

8. AWS Machine Learning/18. ML objects Handson in ML.mp445.63MB

8. AWS Machine Learning/2. Lifecycle of AML.mp443.45MB

8. AWS Machine Learning/3. Connecting to Data Source in AML.mp418.8MB

8. AWS Machine Learning/4. Creating Data Scheme in AML.mp426.88MB

8. AWS Machine Learning/5. Invaild Value and Varible Target in AML.mp44.41MB

8. AWS Machine Learning/6. ML Models in AML.mp458.71MB

8. AWS Machine Learning/7. Manging ML Object in AML.mp412.02MB

8. AWS Machine Learning/8. Creating DataSource Handson.mp4104.1MB

8. AWS Machine Learning/9. Creating DataSource Handson Continues.mp469.95MB

9. Deep Learning Tutorials/1. Introduction to Deep Learning.mp428.08MB

9. Deep Learning Tutorials/10. Data for Classifier.mp449.77MB

9. Deep Learning Tutorials/11. Implementing with Keras.mp445.54MB

9. Deep Learning Tutorials/12. Values in Data Set.mp472.42MB

9. Deep Learning Tutorials/13. Components in Data Set.mp479.14MB

9. Deep Learning Tutorials/14. Models in Data Set.mp462.07MB

9. Deep Learning Tutorials/2. Structure of Neural Network.mp435.22MB

9. Deep Learning Tutorials/3. Moving Through Neural Network.mp438.04MB

9. Deep Learning Tutorials/4. Types of Activation Functions.mp420.42MB

9. Deep Learning Tutorials/5. Optimizing Back Propagation.mp444.98MB

9. Deep Learning Tutorials/6. Briefing on Tensor Flow.mp435.78MB

9. Deep Learning Tutorials/7. Installation of Tensor Flow.mp423.24MB

9. Deep Learning Tutorials/8. Implementatiion on Neural Package.mp481.87MB

9. Deep Learning Tutorials/9. Implementatiion on Neural Package Continues.mp469.05MB