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Hands-On Labs: MLS-CO1: AWS Certified Machine Learning Specialty- Based On Real World Case Studies

جلد کتاب Hands-On Labs: MLS-CO1: AWS Certified Machine Learning Specialty-  Based On Real World Case Studies

معرفی کتاب «Hands-On Labs: MLS-CO1: AWS Certified Machine Learning Specialty- Based On Real World Case Studies» نوشتهٔ Eugene C. Toy، John T. Patlan، Mark T. Warner، Gabriel M. Aisenberg و Specialist, IP، منتشرشده توسط نشر 2022 در سال 2022. این کتاب در فرمت pdf، زبان انگلیسی ارائه شده است.

his latest AWS Certified Machine Learning Specialty (MLS-C01) Hands-on Labs Prep Specialization consists of domains that will act as a bedrock of all the required knowledge to prepare you for the MLS-C01 certification exam and for a career in the cloud. This is a highly practical, intensive, yet comprehensive book that will teach you to become an AWS Machine Learning expert. The book is for anyone who would like to master the art of AWS Machine Learning fundamentals. It is a perfect resource to pass the AWS Certified Machine Learning Specialty (MLS-C01) exam on the first attempt. The latest edition includes: - Hand-on practice labs. - Case Studies This exam measures your ability to describe the following concepts: -Data Engineering -Exploratory Data Analysis -Modeling -Machine Learning implementation and Operations Course Introduction (MLS-C01) Lab 01: Use Amazon Rekognition Lab 02: Creating a Lambda Function Lab 03: Build A Serverless Webpage with API Gateway and AWS Lambda Lab 04: Streaming Data Collection Lab 05: Performing Real-Time Data Analysis with Kinesis Lab 06: Data Analysis & Visualization Lab 07: Modeling Lab 08: Introducing Jupyter Notebooks (AWS SageMaker) Lab 09: Algorithms Lab 10: Understanding CloudFormation Template Anatomy Lab 11: Creating a TensorFlow Image Classifier in AWS SageMaker Lab 12: Creating an MXNet Image Classifier in AWS SageMaker Lab 13: Creating a scikit-learn Random Forest Classifier in AWS SageMaker Lab 14: Evaluation and Optimization Lab 15: Categorizing Uploaded Data Using AWS Step Functions Lab 16: Coordinating AI Services with Step Functions
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