MLS C00 AWS Certified Machine Learning Specialty Pearson | A112F57128A8A94AEED1BB5E7D7849D3067E6130

MLS C00 AWS Certified Machine Learning Specialty Pearson

Name	MLS-C00 AWS Certified Machine Learning Specialty - Pearson	DOWNLOAD Copy Link
Total Size	10.4 GB
Total Files	53
Last Seen	2024-10-15 23:33
Hash	A112F57128A8A94AEED1BB5E7D7849D3067E6130

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01 - AWS Certified Machine Learning-Specialty (ML-S) - Introduction.mp4	67.9 MB
02 - Learning objectives.mp4	39.9 MB
03 - 1.1 Get an overview of the certification.mp4	190.1 MB
04 - 1.2 Use exam study resources.mp4	95.0 MB
05 - 1.3 Review the exam guide.mp4	347.7 MB
06 - 1.4 Learn the exam strategy.mp4	91.2 MB
07 - 1.5 Learn the best practices of ML on AWS.mp4	114.1 MB
08 - 1.6 Learn the techniques to accelerate hands-on practice.mp4	94.4 MB
09 - 1.7 Understand important ML related services.mp4	733.7 MB
10 - Learning objectives.mp4	37.8 MB
11 - 2.1 Learn data ingestion concepts.mp4	671.8 MB
12 - 2.2 Using data cleaning and preparation.mp4	150.9 MB
13 - 2.3 Learn data storage concepts.mp4	238.5 MB
14 - 2.4 Learn ETL solutions (Extract-Transform-Load).mp4	379.9 MB
15 - 2.5 Understand data batch vs data streaming.mp4	116.1 MB
16 - 2.6 Understand data security.mp4	169.9 MB
17 - 2.7 Learn data backup and recovery concepts.mp4	220.4 MB
18 - Learning objectives.mp4	31.0 MB
19 - 3.1 Understand data visualization - Overview.mp4	227.7 MB
20 - 3.2 Learn Clustering.mp4	167.2 MB
21 - 3.3 Use Summary Statistics.mp4	83.5 MB
22 - 3.4 Implement Heatmap.mp4	56.4 MB
23 - 3.5 Understand Principal Component Analysis (PCA).mp4	96.2 MB
24 - 3.6 Understand data distributions.mp4	96.3 MB
25 - 3.7 Use data normalization techniques.mp4	117.6 MB
26 - Learning objectives.mp4	26.8 MB
27 - 4.1 Understand AWS ML Systems - Overview (Sagemaker, AWS ML, EMR, MXNet).mp4	451.4 MB
28 - 4.2 Use Feature Engineering.mp4	284.4 MB
29 - 4.3 Train a Model.mp4	121.2 MB
30 - 4.4 Evaluate a Model.mp4	152.2 MB
31 - 4.5 Tune a Model.mp4	88.6 MB
32 - 4.6 Understand ML Inference.mp4	161.0 MB
33 - 4.7 Understand Deep Learning on AWS.mp4	306.9 MB
34 - Learning objectives.mp4	35.8 MB
35 - 5.1 Understand ML operations - Overview.mp4	198.7 MB
36 - 5.2 Use Containerization with Machine Learning and Deep Learning.mp4	244.7 MB
37 - 5.3 Implement continuous deployment and delivery for Machine Learning.mp4	185.0 MB
38 - 5.4 Understand A_B Testing production deployment.mp4	72.0 MB
39 - 5.5 Troubleshoot production deployment.mp4	173.2 MB
40 - 5.6 Understand production security.mp4	218.3 MB
41 - 5.7 Understand cost and efficiency of ML systems.mp4	240.3 MB
42 - Learning objectives.mp4	27.2 MB
43 - 6.1 Create Machine Learning Data Pipeline.mp4	294.8 MB
44 - 6.2 Perform Exploratory Data Analysis using AWS Sagemaker.mp4	210.0 MB
45 - 6.3 Create Machine Learning Model using AWS Sagemaker.mp4	237.3 MB
46 - 6.4 Deploy Machine Learning Model using AWS Sagemaker.mp4	298.0 MB
47 - Learning objectives.mp4	30.0 MB
48 - 7.1 Sagemaker Features.mp4	714.6 MB
49 - 7.2 DeepLense Features.mp4	347.9 MB
50 - 7.3 Kinesis Features.mp4	191.7 MB
51 - 7.4 AWS Flavored Python.mp4	168.4 MB
52 - 7.5 Cloud9.mp4	279.4 MB
53 - AWS Certified Machine Learning-Specialty (ML-S) - Summary.mp4	21.8 MB
Total files 53