Filename | Size |
| 01 - AWS Certified Machine Learning-Specialty (ML-S) - Introduction.mp4 | 64.8 MB |
| 02 - Learning objectives.mp4 | 38.1 MB |
| 03 - 1.1 Get an overview of the certification.mp4 | 181.3 MB |
| 04 - 1.2 Use exam study resources.mp4 | 90.6 MB |
| 05 - 1.3 Review the exam guide.mp4 | 331.6 MB |
| 06 - 1.4 Learn the exam strategy.mp4 | 87 MB |
| 07 - 1.5 Learn the best practices of ML on AWS.mp4 | 108.8 MB |
| 08 - 1.6 Learn the techniques to accelerate hands-on practice.mp4 | 90.1 MB |
| 09 - 1.7 Understand important ML related services.mp4 | 699.7 MB |
| 10 - Learning objectives.mp4 | 36.1 MB |
| 11 - 2.1 Learn data ingestion concepts.mp4 | 640.7 MB |
| 12 - 2.2 Using data cleaning and preparation.mp4 | 143.9 MB |
| 13 - 2.3 Learn data storage concepts.mp4 | 227.5 MB |
| 14 - 2.4 Learn ETL solutions (Extract-Transform-Load).mp4 | 362.3 MB |
| 15 - 2.5 Understand data batch vs data streaming.mp4 | 110.7 MB |
| 16 - 2.6 Understand data security.mp4 | 162 MB |
| 17 - 2.7 Learn data backup and recovery concepts.mp4 | 210.2 MB |
| 18 - Learning objectives.mp4 | 29.6 MB |
| 19 - 3.1 Understand data visualization - Overview.mp4 | 217.1 MB |
| 20 - 3.2 Learn Clustering.mp4 | 159.5 MB |
| 21 - 3.3 Use Summary Statistics.mp4 | 79.6 MB |
| 22 - 3.4 Implement Heatmap.mp4 | 53.8 MB |
| 23 - 3.5 Understand Principal Component Analysis (PCA).mp4 | 91.8 MB |
| 24 - 3.6 Understand data distributions.mp4 | 91.9 MB |
| 25 - 3.7 Use data normalization techniques.mp4 | 112.2 MB |
| 26 - Learning objectives.mp4 | 25.6 MB |
| 27 - 4.1 Understand AWS ML Systems - Overview (Sagemaker, AWS ML, EMR, MXNet).mp4 | 430.4 MB |
| 28 - 4.2 Use Feature Engineering.mp4 | 271.2 MB |
| 29 - 4.3 Train a Model.mp4 | 115.6 MB |
| 30 - 4.4 Evaluate a Model.mp4 | 145.2 MB |
| 31 - 4.5 Tune a Model.mp4 | 84.5 MB |
| 32 - 4.6 Understand ML Inference.mp4 | 153.6 MB |
| 33 - 4.7 Understand Deep Learning on AWS.mp4 | 292.7 MB |
| 34 - Learning objectives.mp4 | 34.1 MB |
| 35 - 5.1 Understand ML operations - Overview.mp4 | 189.5 MB |
| 36 - 5.2 Use Containerization with Machine Learning and Deep Learning.mp4 | 233.4 MB |
| 37 - 5.3 Implement continuous deployment and delivery for Machine Learning.mp4 | 176.4 MB |
| 38 - 5.4 Understand A_B Testing production deployment.mp4 | 68.6 MB |
| 39 - 5.5 Troubleshoot production deployment.mp4 | 165.2 MB |
| 40 - 5.6 Understand production security.mp4 | 208.2 MB |
| 41 - 5.7 Understand cost and efficiency of ML systems.mp4 | 229.2 MB |
| 42 - Learning objectives.mp4 | 25.9 MB |
| 43 - 6.1 Create Machine Learning Data Pipeline.mp4 | 281.2 MB |
| 44 - 6.2 Perform Exploratory Data Analysis using AWS Sagemaker.mp4 | 200.2 MB |
| 45 - 6.3 Create Machine Learning Model using AWS Sagemaker.mp4 | 226.3 MB |
| 46 - 6.4 Deploy Machine Learning Model using AWS Sagemaker.mp4 | 284.2 MB |
| 47 - Learning objectives.mp4 | 28.6 MB |
| 48 - 7.1 Sagemaker Features.mp4 | 681.5 MB |
| 49 - 7.2 DeepLense Features.mp4 | 331.8 MB |
| 50 - 7.3 Kinesis Features.mp4 | 182.8 MB |
| 51 - 7.4 AWS Flavored Python.mp4 | 160.6 MB |
| 52 - 7.5 Cloud9.mp4 | 266.5 MB |
| 53 - AWS Certified Machine Learning-Specialty (ML-S) - Summary.mp4 | 20.8 MB |