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Practical Machine Learning with Aws

Practical Machine Learning with Aws

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About the Book

Part-I - Introduction to Amazon Web Services (100 Pages)
Chapter 1: AWS Concepts and TechnologiesIntroduction to services like S3, EC2, Identity Access Management, Roles, Load Balancer, Cloud Formation, etc.
Chapter 2: AWS Billing and PricingUnderstanding AWS pricing, billing, group and tagging, etc.
Chapter 3: AWS Cloud SecurityDescription about AWS compliance and artifacts, AWS Shield, Cloudwatch, Cloud Trail, etc.
Part-II - Machine Learning in AWS (300 Pages)
Chapter 4: Data Collection and Preparation
Concepts include AWS data stores, migration and helper tools. It also includes pre-processing concepts like encoding, feature engineering, missing values removal, etc.
Chapter 5: Data Modelling and AlgorithmsIn this section, we will talk about all the algorithms that AWS supports, including regression, clustering, classification, image, and text analytics, etc. We will then look at Sagemaker service and how to make models using it.
Chapter 6: Data Analysis and VisualizationThis chapter talks about the relationship between variables, data distributions, the composition of data, etc.
Chapter 7: Model Evaluation and OptimizationThis chapter talks about the monitoring of training jobs, evaluating the model accuracy, and fine-tuning models.
Chapter 8: Implementation and OperationIn this chapter, we'll look at the deployment of models, security, and monitoring.
Chapter 9: Building a Machine Learning WorkflowIn this chapter, we'll look at the machine learning workflow in AWS .
Part-IV - Projects (100 Pages)
Chapter 10: Project - Building skills with Alexa
Chapter 11: Project - Time series forecasting using Amazon forecast
Chapter 12: Project - Modelling and deployment using XGBoost in Sagemaker
Chapter 13: Text classification using Amazon comprehend and textract
Chapter 14: Building a complete project pipeline


About the Author: Himanshu Singh is Technology Lead and Senior NLP Engineer at Legato Healthcare (an Anthem Company). He has seven years of experience in the AI industry, primarily in computer vision and natural language processing. He has authored three books on machine learning. He has an MBA from Narsee Monjee Institute of Management Studies, and a postgraduate diploma in Applied Statistics.


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Product Details
  • ISBN-13: 9781484262214
  • Publisher: Apress
  • Publisher Imprint: Apress
  • Height: 254 mm
  • No of Pages: 241
  • Spine Width: 14 mm
  • Weight: 508 gr
  • ISBN-10: 1484262212
  • Publisher Date: 24 Nov 2020
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Sub Title: Process, Build, Deploy, and Productionize Your Models Using Aws
  • Width: 178 mm


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