FreeCoursesOnline Me Packt Hands-On Machine Learning with Scala and Spark FCO

1. 01.Advanced Text Processing in Spark and Building a Classification Model/0101.The Course Overview.mp419.2MB
2. 01.Advanced Text Processing in Spark and Building a Classification Model/0102.Analyzing Text Input Data.mp418.88MB
3. 01.Advanced Text Processing in Spark and Building a Classification Model/0103.Feature Generation from Text – Count Vectorizer, TFIDF, LDA.mp414.1MB
4. 01.Advanced Text Processing in Spark and Building a Classification Model/0104.Extracting Features from Data – Transforming Text into Vector of Numbers.mp422.71MB
5. 01.Advanced Text Processing in Spark and Building a Classification Model/0105.Bag-of-Words and Skip Gram.mp48.37MB
6. 01.Advanced Text Processing in Spark and Building a Classification Model/0106.Training Classification Models – Implementing Word2Vect Using Apache Spark.mp416.28MB
7. 02.Building a Regression Model with Spark/0201.Logistic Regression Explanation.mp48.62MB
8. 02.Building a Regression Model with Spark/0202.Writing a Logistic Regression Model Per Author in Apache Spark.mp48.62MB
9. 02.Building a Regression Model with Spark/0203.Training Regression Model.mp415.34MB
10. 02.Building a Regression Model with Spark/0204.Key Concepts, Machine Learning Pipelines, and Operations.mp410.42MB
11. 02.Building a Regression Model with Spark/0205.Learn How to Validate Models Using Cross-Validation.mp418.64MB
12. 03.Building a Clustering Model with Spark/0301.Analyzing Time of Post Using Clustering – (GMM Explanation).mp46.1MB
13. 03.Building a Clustering Model with Spark/0302.Implementing GMM in Apache Spark.mp431.52MB
14. 03.Building a Clustering Model with Spark/0303.K-Means Clustering Explanation and Use Cases.mp44.09MB
15. 03.Building a Clustering Model with Spark/0304.Implementing K-Means Clustering in Apache Spark.mp418.19MB
16. 03.Building a Clustering Model with Spark/0305.Measure Accuracy Using Area Under ROC.mp412.57MB
17. 04.Dimensionality Reductions and Recommendation Engines/0401.Dimensionality Reduction Using Singular Value Decomposition (SVD).mp414.06MB
18. 04.Dimensionality Reductions and Recommendation Engines/0402.Building Recommendation Engine in Spark Using Collaborative Filtering.mp418.21MB
19. 04.Dimensionality Reductions and Recommendation Engines/0403.Using Recommendation Engine to Get Top Recommendations.mp426.32MB
20. 04.Dimensionality Reductions and Recommendation Engines/0404.Dense and Sparse Vectors.mp413.71MB
21. 04.Dimensionality Reductions and Recommendation Engines/0405.LabeledPoints, Rating, and Other Data Types.mp410.48MB
22. 05.Deep Learning with Spark/0501.The Spark versus Deep Learning Use Case.mp47.71MB
23. 05.Deep Learning with Spark/0502.Spark for Parallelizing Deep Learning Evaluation.mp415.27MB
24. 05.Deep Learning with Spark/0503.Deep Learning As a Feature Generator for Existing Spark ML Algorithms.mp411.52MB
25. 05.Deep Learning with Spark/0504.SparkDeep Learning Made Simple.mp415.22MB