Spark Ray and Python for Scalable Data Science

Focused View

7:01:38

122 View

1 - Spark, Ray, and Python for Scalable Data Science - Introduction.mp4

01:58

2 - Topics.mp4

00:42

3 - 1.1 Introduction and Materials.mp4

03:30

4 - 1.2 The Data Science Process.mp4

05:02

5 - 1.3 A Brief Historical Diversion.mp4

09:55

6 - 1.4 Distributed Systems Primer.mp4

09:33

7 - 1.5 Python Distributed Computing Frameworks.mp4

06:22

8 - 1.6 The What and Why of Spark.mp4

07:33

9 - 1.7 The Spark Platform.mp4

04:29

10 - 1.8 Spark versus Ray.mp4

06:22

11 - Topics.mp4

00:47

12 - 2.1 Course Coding Setup.mp4

07:23

13 - 2.2 Your First PySpark Job.mp4

20:48

14 - 2.3 Introduction to RDDs.mp4

06:33

15 - 2.4 Transformations versus Actions.mp4

15:31

16 - 2.5 RDD Deep Dive.mp4

11:22

17 - 2.6 The Spark Execution Context.mp4

05:54

18 - 2.7 Spark versus Hadoop.mp4

05:56

19 - 2.8 Spark Application Lifecycle.mp4

16:53

20 - Topics.mp4

00:56

21 - 3.1 Introduction to Exploratory Data Analysis.mp4

07:36

22 - 3.2 A Quick Tour of Jupyter Notebooks.mp4

14:21

23 - 3.3 Parsing Data at Scale.mp4

26:47

24 - 3.4 Spark DataFrames - Integration into Existing Workflows.mp4

10:35

25 - 3.5 Scaling Exploratory Data Analysis with Spark.mp4

13:53

26 - 3.6 Making Sense of Data - Summary Statistics and Data Visualization.mp4

11:47

27 - 3.7 Working with Text - Introduction to NLP.mp4

09:35

28 - 3.8 Tokenization and Vectorization with MLlib.mp4

08:58

29 - Topics.mp4

00:38

30 - 4.1 The What and Why of Ray.mp4

06:44

31 - 4.2 The Ray Programming Model.mp4

09:17

32 - 4.3 Parallelizing Functions with Ray Tasks.mp4

15:31

33 - 4.4 Asynchronous Programming with Actors.mp4

15:21

34 - 4.5 Cellular Automata and the Game of Life.mp4

09:10

36 - Topics.mp4

00:53

37 - 5.1 Introduction to Model Evaluation.mp4

08:31

38 - 5.2 Serializing Data for Machine Learning Applications.mp4

07:08

39 - 5.3 Cross Validation with scikit-learn.mp4

09:14

40 - 5.4 Strategies for Tuning Machine Learning Models.mp4

10:45

41 - 5.5 Grid Search in Python.mp4

10:59

42 - 5.6 Distributed Hyperparameter Optimization with Ray Tune.mp4

11:42

43 - 5.7 Resource Efficient Search with Principled Early Stopping.mp4

13:24

44 - 5.8 Diving Deeper into Ray, Internals.mp4

04:47

45 - 5.9 Serving Machine Learning Models.mp4

09:12

46 - 5.10 Deploying AI Applications with Ray Serve.mp4

16:48

47 - 5.11 Monitoring Model Performance in Production.mp4

09:34

48 - Spark, Ray, and Python for Scalable Data Science - Summary.mp4

00:59

More details

User Reviews

Rating

average 0

Total votes0

Focused display

Pearson's video training library is an indispensable learning tool for today's competitive job market. Having essential technology training and certifications can open doors for career advancement and life enrichment. We take learning personally. We've published hundreds of up-to-date videos on wide variety of key topics for Professionals and IT Certification candidates. Now you can learn from renowned industry experts from anywhere in the world, without leaving home.