Amazon Web Services Machine Learning Essential Training

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Lynn Langit

3:07:23

193 View

01 - Introduction

01 - Welcome.mp4

01:12

02 - About using cloud services.mp4

02:07

02 - 1. Machine Learning on AWS

01 - AWS Machine Learning concepts.mp4

03:49

02 - Business scenarios for machine learning.mp4

04:25

03 - Which algorithm should I use.mp4

06:13

04 - AWS AI servers vs. platforms.mp4

02:38

05 - AWS AI platforms vs. frameworks.mp4

03:17

06 - A classifier in action Amazon Macie.mp4

04:12

03 - 2. Machine Learning API Services

01 - Setup for AWS machine learning APIs.mp4

07:21

02 - Predict using AWS Comprehend for NLP.mp4

04:55

03 - Predict using AWS Polly text-to-speech.mp4

04:35

04 - Predict using AWS Lex for chatbots.mp4

06:17

05 - Predict using AWS Rekognition for images.mp4

06:40

06 - Predict using AWS Rekognition for video.mp4

02:43

07 - Predict using Transcribe and Translate.mp4

03:10

04 - 3. Machine Learning Platforms

01 - Understanding ML platforms.mp4

03:53

02 - Understanding and using AWS Machine Learning.mp4

09:15

03 - Understanding SageMaker.mp4

03:54

04 - Create Jupyter notebooks with SageMaker.mp4

06:12

05 - Get data with SageMaker notebook.mp4

06:25

06 - Train model with SageMaker job.mp4

03:06

07 - Deploy and host model with SageMaker model.mp4

02:31

08 - Use model from SageMaker endpoint.mp4

04:07

09 - Selecting algorithm for model training.mp4

05:36

10 - Advanced use of SageMaker.mp4

02:37

05 - 4. Machine Learning Virtual Servers

01 - Understanding ML virtual servers.mp4

04:07

02 - Understanding deep learning.mp4

02:36

03 - Work with Gluon for MXNet in SageMaker.mp4

05:14

04 - Work with MXNet in SageMaker.mp4

09:01

05 - Databricks on AWS.mp4

07:02

06 - Work with MXNet in Databricks.mp4

09:02

07 - Set up the AWS Deep Learning AMIs.mp4

06:38

08 - Work with the AWS Deep Learning AMI.mp4

04:16

09 - Work with EMR for machine learning.mp4

08:40

06 - 5. Machine Learning Architectures

01 - AWS ML APIs for conversational apps.mp4

02:39

02 - AWS ML service for IoT apps.mp4

02:12

03 - Spark ML and Databricks AWS for real-time apps.mp4

02:16

04 - VariantSpark and EMR for genomic research.mp4

04:04

05 - Best practices for algorithms and architectures.mp4

07:16

07 - Conclusion

01 - Next steps.mp4

01:10

Description

Amazon Web Services (AWS) offers a wealth of services and tools that help data scientists leverage machine learning to craft better, more intelligent solutions. In this course, learn about patterns, services, processes, and best practices for designing and implementing machine learning using AWS. Instructor Lynn Langit takes a look at general machine learning concepts, including key machine learning algorithm types. She also examines available service types, such as AWS Machine Learning, Lex, Polly, and Rekognition, which you can use to predict image and video labels. Plus, she steps through how to work with platforms like AWS SageMaker, which includes hosted Jupyter notebooks.

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Machine Learning

Amazon AWS

Lynn Langit

Instructor's Courses

Cloud Architect working with remote dev teams world-wide to build cloud solutions. Author of 30 LinkedIn Learning Cloud/Data courses with over 5 million student views. https://www.linkedin.com/learning/instructors/lynn-langit

Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.