Build ML Projects on AWS Master SageMaker

Build ML Projects on AWS Master SageMaker, available at $44.99, has an average rating of 3.13, with 8 lectures, based on 4 reviews, and has 1548 subscribers.

You will learn about Introduction to Amazon SageMaker: Explore the features and capabilities of SageMaker as a machine learning platform. Introduction to Machine Learning: Understand the basics of machine learning, including supervised and unsupervised learning, algorithms, and models. Data Visualization: Explore techniques for visualizing and understanding your data using tools and libraries available in SageMaker. Model Training: Understand how to train machine learning models using SageMaker's infrastructure, including distributed training and hyperparameter tuning. This course is ideal for individuals who are Data Scientists: Data scientists looking to expand their machine learning and data modeling skills with a focus on using AWS SageMaker for developing, training, and deploying machine learning models. or Machine Learning Engineers: Machine learning engineers interested in mastering the tools and techniques within SageMaker to build, test, and deploy machine learning models at scale. or Software Developers: Developers who want to integrate machine learning into their applications and are interested in using SageMaker to streamline model development and deployment. or Business Analysts: Business analysts looking to gain insights from data using machine learning techniques and SageMaker. or AWS Enthusiasts: Those who are already familiar with AWS services and want to explore SageMaker's capabilities. It is particularly useful for Data Scientists: Data scientists looking to expand their machine learning and data modeling skills with a focus on using AWS SageMaker for developing, training, and deploying machine learning models. or Machine Learning Engineers: Machine learning engineers interested in mastering the tools and techniques within SageMaker to build, test, and deploy machine learning models at scale. or Software Developers: Developers who want to integrate machine learning into their applications and are interested in using SageMaker to streamline model development and deployment. or Business Analysts: Business analysts looking to gain insights from data using machine learning techniques and SageMaker. or AWS Enthusiasts: Those who are already familiar with AWS services and want to explore SageMaker's capabilities.

Enroll now: Build ML Projects on AWS Master SageMaker

Summary

Title: Build ML Projects on AWS Master SageMaker

Price: $44.99

Average Rating: 3.13

Number of Lectures: 8

Number of Published Lectures: 8

Number of Curriculum Items: 8

Number of Published Curriculum Objects: 8

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

• Introduction to Amazon SageMaker: Explore the features and capabilities of SageMaker as a machine learning platform.
• Introduction to Machine Learning: Understand the basics of machine learning, including supervised and unsupervised learning, algorithms, and models.
• Data Visualization: Explore techniques for visualizing and understanding your data using tools and libraries available in SageMaker.
• Model Training: Understand how to train machine learning models using SageMaker's infrastructure, including distributed training and hyperparameter tuning.

Who Should Attend

• Data Scientists: Data scientists looking to expand their machine learning and data modeling skills with a focus on using AWS SageMaker for developing, training, and deploying machine learning models.
• Machine Learning Engineers: Machine learning engineers interested in mastering the tools and techniques within SageMaker to build, test, and deploy machine learning models at scale.
• Software Developers: Developers who want to integrate machine learning into their applications and are interested in using SageMaker to streamline model development and deployment.
• Business Analysts: Business analysts looking to gain insights from data using machine learning techniques and SageMaker.
• AWS Enthusiasts: Those who are already familiar with AWS services and want to explore SageMaker's capabilities.

Target Audiences

• Data Scientists: Data scientists looking to expand their machine learning and data modeling skills with a focus on using AWS SageMaker for developing, training, and deploying machine learning models.
• Machine Learning Engineers: Machine learning engineers interested in mastering the tools and techniques within SageMaker to build, test, and deploy machine learning models at scale.
• Software Developers: Developers who want to integrate machine learning into their applications and are interested in using SageMaker to streamline model development and deployment.
• Business Analysts: Business analysts looking to gain insights from data using machine learning techniques and SageMaker.
• AWS Enthusiasts: Those who are already familiar with AWS services and want to explore SageMaker's capabilities.