AWS Certified Machine Learning: AI Services & SageMaker Applications

Amazon Web Services    |    Intermediate
  • 12 videos | 49m 4s
  • Includes Assessment
  • Earns a Badge
Rating 4.2 of 33 users Rating 4.2 of 33 users (33)
Integrating AWS AI services and SageMaker with any machine learning (ML) or deep learning project is a great way to enhance its capabilities. Through this course, learn more about the additional AWS AI Services that are ready to use in the form of direct API without the need to train any ML models and dive deeper into more SageMaker functionality. Get familiar with AWS AI services that can be fully integrated into your applications in minutes. This course will also introduce you to some pre-trained algorithms in SageMaker for building high-performance natural language processing (NLP) and computer vision apps using fine-tuning techniques. After completing this course, you'll be able to identify several AI services that can be used as APIs in AWS and describe SageMaker's extensive capabilities in handling text and images. You'll also be a step closer to preparing for the AWS Certified Machine Learning - Specialty certification exam.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Work with amazon rekognition for detecting, analyzing, and comparing faces
    Work with amazon polly for text-to-speech conversion
    Work with amazon transcribe and translate to explore natural language processing (nlp) capabilities
    Work with seq2seq models in sagemaker for natural language processing (nlp)
    Tackle forecasting problems using deepar
  • Work with blazingtext for optimized text classification capabilities
    Work with object2vec general-purpose embeddings used for natural language processing (nlp) tasks
    Work with sagemaker's built-in object detection algorithms
    Work with sagemaker's built-in image classification algorithms
    Work with sagemaker's built-it semantic segmentation algorithms
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 1s
  • 4m 43s
  • Locked
    3.  Working with Amazon Polly
    4m 27s
  • Locked
    4.  Exploring Amazon Transcribe and Translate
    6m 25s
  • Locked
    5.  Working with Seq2seq in SageMaker
    4m 13s
  • Locked
    6.  Working with DeepAR in SageMaker
    4m 29s
  • Locked
    7.  Using BlazingText in SageMaker
    5m 25s
  • Locked
    8.  Working with Object2vec in SageMaker
    4m 4s
  • Locked
    9.  Working with Object Detection in SageMaker
    3m 59s
  • Locked
    10.  Classifying Images in SageMaker
    4m 4s
  • Locked
    11.  Performing Semantic Segmentation in SageMaker
    5m 14s
  • Locked
    12.  Course Summary
    1m 1s

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.

Digital badges are yours to keep, forever.

YOU MIGHT ALSO LIKE

Course AWS Certified Machine Learning: Feature Engineering Overview
Rating 4.0 of 13 users Rating 4.0 of 13 users (13)
Course AWS Developer Associate 2022: CloudFormation
Rating 4.5 of 116 users Rating 4.5 of 116 users (116)
Book Cloud Native AI and Machine Learning on AWS: Use SageMaker for building ML models, Automate MLOps, and Take Advantage of Numerous AWS AI Services

PEOPLE WHO VIEWED THIS ALSO VIEWED THESE

Course AWS Certified Machine Learning: Machine Learning in SageMaker
Rating 4.3 of 134 users Rating 4.3 of 134 users (134)
Course Using R Programming Structures: Object Systems
Rating 4.6 of 9 users Rating 4.6 of 9 users (9)
Course AWS Cloud Practitioner 2019: AWS Access Management
Rating 4.5 of 70 users Rating 4.5 of 70 users (70)