MLS-C00 AWS Certified Machine Learning Specialty - Pearson

1. 09 - 1.7 Understand important ML related services.mp4699.75 Mb
2. 48 - 7.1 Sagemaker Features.mp4681.5 Mb
3. 11 - 2.1 Learn data ingestion concepts.mp4640.68 Mb
4. 27 - 4.1 Understand AWS ML Systems - Overview (Sagemaker, AWS ML, EMR, MXNet).mp4430.45 Mb
5. 14 - 2.4 Learn ETL solutions (Extract-Transform-Load).mp4362.27 Mb
6. 49 - 7.2 DeepLense Features.mp4331.77 Mb
7. 05 - 1.3 Review the exam guide.mp4331.57 Mb
8. 33 - 4.7 Understand Deep Learning on AWS.mp4292.69 Mb
9. 46 - 6.4 Deploy Machine Learning Model using AWS Sagemaker.mp4284.22 Mb
10. 43 - 6.1 Create Machine Learning Data Pipeline.mp4281.18 Mb
11. 28 - 4.2 Use Feature Engineering.mp4271.25 Mb
12. 52 - 7.5 Cloud9.mp4266.49 Mb
13. 36 - 5.2 Use Containerization with Machine Learning and Deep Learning.mp4233.4 Mb
14. 41 - 5.7 Understand cost and efficiency of ML systems.mp4229.19 Mb
15. 13 - 2.3 Learn data storage concepts.mp4227.46 Mb
16. 45 - 6.3 Create Machine Learning Model using AWS Sagemaker.mp4226.35 Mb
17. 19 - 3.1 Understand data visualization - Overview.mp4217.14 Mb
18. 17 - 2.7 Learn data backup and recovery concepts.mp4210.18 Mb
19. 40 - 5.6 Understand production security.mp4208.18 Mb
20. 44 - 6.2 Perform Exploratory Data Analysis using AWS Sagemaker.mp4200.25 Mb
21. 35 - 5.1 Understand ML operations - Overview.mp4189.53 Mb
22. 50 - 7.3 Kinesis Features.mp4182.8 Mb
23. 03 - 1.1 Get an overview of the certification.mp4181.26 Mb
24. 37 - 5.3 Implement continuous deployment and delivery for Machine Learning.mp4176.4 Mb
25. 39 - 5.5 Troubleshoot production deployment.mp4165.17 Mb
26. 16 - 2.6 Understand data security.mp4162.01 Mb
27. 51 - 7.4 AWS Flavored Python.mp4160.63 Mb
28. 20 - 3.2 Learn Clustering.mp4159.48 Mb
29. 32 - 4.6 Understand ML Inference.mp4153.58 Mb
30. 30 - 4.4 Evaluate a Model.mp4145.17 Mb
31. 12 - 2.2 Using data cleaning and preparation.mp4143.95 Mb
32. 29 - 4.3 Train a Model.mp4115.57 Mb
33. 25 - 3.7 Use data normalization techniques.mp4112.18 Mb
34. 15 - 2.5 Understand data batch vs data streaming.mp4110.68 Mb
35. 07 - 1.5 Learn the best practices of ML on AWS.mp4108.77 Mb
36. 24 - 3.6 Understand data distributions.mp491.86 Mb
37. 23 - 3.5 Understand Principal Component Analysis (PCA).mp491.79 Mb
38. 04 - 1.2 Use exam study resources.mp490.59 Mb
39. 08 - 1.6 Learn the techniques to accelerate hands-on practice.mp490.06 Mb
40. 06 - 1.4 Learn the exam strategy.mp487 Mb
41. 31 - 4.5 Tune a Model.mp484.48 Mb
42. 21 - 3.3 Use Summary Statistics.mp479.59 Mb
43. 38 - 5.4 Understand A_B Testing production deployment.mp468.63 Mb
44. 01 - AWS Certified Machine Learning-Specialty (ML-S) - Introduction.mp464.76 Mb
45. 22 - 3.4 Implement Heatmap.mp453.8 Mb
46. 02 - Learning objectives.mp438.07 Mb
47. 10 - Learning objectives.mp436.07 Mb
48. 34 - Learning objectives.mp434.14 Mb
49. 18 - Learning objectives.mp429.58 Mb
50. 47 - Learning objectives.mp428.57 Mb
51. 42 - Learning objectives.mp425.93 Mb
52. 26 - Learning objectives.mp425.55 Mb
53. 53 - AWS Certified Machine Learning-Specialty (ML-S) - Summary.mp420.8 Mb