AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01)

Name: AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01) Training Course
Brand: DumpsQueen
SKU: AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01)
Price: 14.99 USD
Availability: InStock
Rating: 5.0 (116 reviews)

Best Seller 106 Lectures 9h 8m

Prepare for your Amazon AWS examination with our training course. The AWS-Certified-Machine-Learning-Specialty-MLS-C01 course contains a complete batch of videos that will provide you with profound and thorough knowledge related to Amazon AWS certification exam. Pass the Amazon AWS AWS-Certified-Machine-Learning-Specialty-MLS-C01 test with flying colors.

$14.99$24.99

Curriculum For This Course

1. Introduction

1 lectures 6m

1. Course Introduction: What to Expect 6m

2. Data Engineering

22 lectures 1h 24m

1. Section Intro: Data Engineering 1m
2. Amazon S3 - Overview 5m
3. Amazon S3 - Storage Tiers & Lifecycle Rules 4m
4. Amazon S3 Security 8m
5. Kinesis Data Streams & Kinesis Data Firehose 9m
6. Lab 1.1 - Kinesis Data Firehose 6m
7. Kinesis Data Analytics 4m
8. Lab 1.2 - Kinesis Data Analytics 7m
9. Kinesis Video Streams 3m
10. Kinesis ML Summary 1m
11. Glue Data Catalog & Crawlers 3m
12. Lab 1.3 - Glue Data Catalog 4m
13. Glue ETL 2m
14. Lab 1.4 - Glue ETL 6m
15. Lab 1.5 - Athena 1m
16. Lab 1 - Cleanup 2m
17. AWS Data Stores in Machine Learning 3m
18. AWS Data Pipelines 3m
19. AWS Batch 2m
20. AWS DMS - Database Migration Services 2m
21. AWS Step Functions 3m
22. Full Data Engineering Pipelines 5m

3. Exploratory Data Analysis

21 lectures 2h 27m

1. Section Intro: Data Analysis 1m
2. Python in Data Science and Machine Learning 12m
3. Example: Preparing Data for Machine Learning in a Jupyter Notebook. 10m
4. Types of Data 5m
5. Data Distributions 6m
6. Time Series: Trends and Seasonality 4m
7. Introduction to Amazon Athena 5m
8. Overview of Amazon Quicksight 6m
9. Types of Visualizations, and When to Use Them. 5m
10. Elastic MapReduce (EMR) and Hadoop Overview 7m
11. Apache Spark on EMR 10m
12. EMR Notebooks, Security, and Instance Types 4m
13. Feature Engineering and the Curse of Dimensionality 7m
14. Imputing Missing Data 8m
15. Dealing with Unbalanced Data 6m
16. Handling Outliers 9m
17. Binning, Transforming, Encoding, Scaling, and Shuffling 8m
18. Amazon SageMaker Ground Truth and Label Generation 4m
19. Lab: Preparing Data for TF-IDF with Spark and EMR, Part 1 6m
20. Lab: Preparing Data for TF-IDF with Spark and EMR, Part 2 10m
21. Lab: Preparing Data for TF-IDF with Spark and EMR, Part 3 14m

4. Modeling

45 lectures 3h 46m

1. Section Intro: Modeling 2m
2. Introduction to Deep Learning 9m
3. Convolutional Neural Networks 12m
4. Recurrent Neural Networks 11m
5. Deep Learning on EC2 and EMR 2m
6. Tuning Neural Networks 5m
7. Regularization Techniques for Neural Networks (Dropout, Early Stopping) 7m
8. Grief with Gradients: The Vanishing Gradient problem 4m
9. L1 and L2 Regularization 3m
10. The Confusion Matrix 6m
11. Precision, Recall, F1, AUC, and more 7m
12. Ensemble Methods: Bagging and Boosting 4m
13. Introducing Amazon SageMaker 8m
14. Linear Learner in SageMaker 5m
15. XGBoost in SageMaker 3m
16. Seq2Seq in SageMaker 5m
17. DeepAR in SageMaker 4m
18. BlazingText in SageMaker 5m
19. Object2Vec in SageMaker 5m
20. Object Detection in SageMaker 4m
21. Image Classification in SageMaker 4m
22. Semantic Segmentation in SageMaker 4m
23. Random Cut Forest in SageMaker 3m
24. Neural Topic Model in SageMaker 3m
25. Latent Dirichlet Allocation (LDA) in SageMaker 3m
26. K-Nearest-Neighbors (KNN) in SageMaker 3m
27. K-Means Clustering in SageMaker 5m
28. Principal Component Analysis (PCA) in SageMaker 3m
29. Factorization Machines in SageMaker 4m
30. IP Insights in SageMaker 3m
31. Reinforcement Learning in SageMaker 12m
32. Automatic Model Tuning 6m
33. Apache Spark with SageMaker 3m
34. Amazon Comprehend 6m
35. Amazon Translate 2m
36. Amazon Transcribe 4m
37. Amazon Polly 6m
38. Amazon Rekognition 7m
39. Amazon Forecast 2m
40. Amazon Lex 3m
41. The Best of the Rest: Other High-Level AWS Machine Learning Services 3m
42. Putting them All Together 2m
43. Lab: Tuning a Convolutional Neural Network on EC2, Part 1 9m
44. Lab: Tuning a Convolutional Neural Network on EC2, Part 2 9m
45. Lab: Tuning a Convolutional Neural Network on EC2, Part 3 6m

5. ML Implementation and Operations

11 lectures 1h 4m

1. Section Intro: Machine Learning Implementation and Operations 1m
2. SageMaker's Inner Details and Production Variants 11m
3. SageMaker On the Edge: SageMaker Neo and IoT Greengrass 4m
4. SageMaker Security: Encryption at Rest and In Transit 5m
5. SageMaker Security: VPC's, IAM, Logging, and Monitoring 4m
6. SageMaker Resource Management: Instance Types and Spot Training 4m
7. SageMaker Resource Management: Elastic Inference, Automatic Scaling, AZ's 5m
8. SageMaker Inference Pipelines 2m
9. Lab: Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 1 5m
10. Lab: Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 2 11m
11. Lab: Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 3 12m

6. Wrapping Up

6 lectures 21m

1. Section Intro: Wrapping Up 1m
2. More Preparation Resources 6m
3. Test-Taking Strategies, and What to Expect 10m
4. You Made It! 1m
5. Save 50% on your AWS Exam Cost! 2m
6. Get an Extra 30 Minutes on your AWS Exam - Non Native English Speakers only 1m

AWS Certified Machine Learning - Specialty: AWS Certified Machine Learning - Specialty (MLS-C01)

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