AWS Sagemaker 2018- Fully Managed Machine Learning Service

AWS Sagemaker 2018- Fully Managed Machine Learning Service

Amazon SageMaker is a fully managed machine learning service. With Amazon SageMaker, data scientists and developers can quickly and easily build and train machine learning models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so you don't have to manage servers. It also provides common machine learning algorithms that are optimized to run efficiently against extremely large data in a distributed environment. With native support for bring-your-own-algorithms and frameworks, Amazon SageMaker offers flexible distributed training options that adjust to your specific workflows. Deploy a model into a secure and scalable environment by launching it with a single click from the Amazon SageMaker console. Training and hosting are billed by minutes of usage, with no minimum fees and no upfront commitments.

If you want to learn about Amazon SageMaker, I recommend you to go through this course which will cover in detail-

1. How it works? This course provides an overview of Amazon SageMaker, explains key concepts, and describes the core components involved in building AI solutions with Amazon SageMaker. We recommend that you read this topic in the order presented.

2. This course explains how to set up your account and create your first Amazon SageMaker notebook instance.

3. Try a model training exercise – This course walks you through training your first model. You use training algorithms provided by Amazon SageMaker. 

4. Explore other topics here– Depending on your needs, the following:

   • Submit Python code to train with deep learning frameworks – In Amazon SageMaker, you can use your own TensorFlow or Apache MXNet scripts to train models. 

   • Use Amazon SageMaker directly from Apache Spark 

   • Use Amazon AI to train and/or deploy your own custom algorithms – Package your custom algorithms with Docker so you can train and/or deploy them in Amazon SageMaker. 

   • And a ton, more....is included in this course....

Through this Course, data scientists and developers can quickly & easily build and train machine learning models &deploy

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What you will learn

• Complete understanding of AWS Sagemaker and way to develop a fully Managed Machine learning Service

Rating: 2.85

Level: All Levels

Duration: 4 hours

Instructor: Dr Aashish Dikshit, PHD(Founder of Lakshmish academy)