AWS – SageMaker For Data Scientists – AI school | Immersive teaching

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AWS – SageMaker For Data Scientists

Categories AWS

About Course

As a data scientist, there are several topics related to Amazon SageMaker that you might find interesting and relevant.

Course Curriculum

Intro on AI/ML & AWS sign up
Amazon SageMaker is a fully managed machine learning service provided by Amazon Web Services (AWS). It is designed to help data scientists and developers build, train, and deploy machine learning models at scale. With SageMaker, you can easily create, train, and deploy machine learning models without the need to manage the underlying infrastructure.

introductions etc, Intro to the course, expectations

00:31
Artificial Intelligence (AI) Vs. Machine Learning (ML) Vs. Deep Learning (DL)

00:00
Machine Learning: The Big Picture

00:00
ML – history, Types of ML

00:00
Key Ingredients to Build Machine Learning Models

00:00
Goals of MLOps, MLOps view of ML workflow

00:00
differences between DevOps and MLOps

00:00
AWS Signup and AWS Management Console Tour

00:00

Key AI/ML Components in AWS

Popular Amazon models
Amazon Web Services (AWS) provides a rich set of services and tools for implementing artificial intelligence (AI) and machine learning (ML) solutions.

IAM & access mgmt
Amazon Identity and Access Management (IAM) is a service provided by Amazon Web Services (AWS) that enables you to manage user access and permissions to AWS resources. IAM allows you to create and manage user accounts, assign fine-grained permissions, and control access to AWS services and resources.

Amazon S3
Amazon Simple Storage Service (S3) is a highly scalable and durable object storage service provided by Amazon Web Services (AWS). It is designed to store and retrieve any amount of data from anywhere on the web. S3 offers a simple interface to store and retrieve data, making it a popular choice for storing a wide range of data types, including documents, images, videos, backups, logs, and more.

Introductions to Amazon Sagemaker
Amazon SageMaker is a fully managed machine learning service provided by Amazon Web Services (AWS). It is designed to simplify the process of building, training, and deploying machine learning models at scale. SageMaker provides a comprehensive set of tools and services that enable data scientists and developers to focus on the core tasks of developing and refining models, without the need to manage the underlying infrastructure.

Prepare data – (Data Wrangler)

Prepare data – Generate and label unstructured data

Prepare data – Store, share, and manage model features

Build Models – SageMaker Studio notebooks
Amazon SageMaker provides all the tools and libraries you need to build ML models, the process of iteratively trying different algorithms and evaluating their accuracy to find the best one for your use case.

Build models – SageMaker notebook instance

Train and tune the model – Fully managed infrastructure at scale

Train and tune the model – High-performance distributed training

Train and tune the model – Built-in tools for the highest accuracy and lowest cost

Train and tune the model – Built-in tools for interactivity and monitoring

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