Amazon Sagemaker: a Hands-on Introduction
Amazon Sagemaker Is a Managed Machine Learning Service (Mlaas). Sagemaker Lets You Quickly Build and Train Machine Learning Models and Deploy Them Directly...
Amazon SageMaker is a managed machine learning service (MLaaS). SageMaker lets you quickly build and train machine learning models and deploy them directly into a hosted environment. In this blog post, we’ll cover how to get started and run SageMaker with examples.
One thing you will find with most of the examples written by Amazon for SageMaker is they are too complicated. Most are geared toward working with handwriting analysis etc. So here we make a new example, based upon something simpler: a spreadsheet with just 50 rows and 6 columns.
Still, SageMaker is far more complicated than Amazon Machine Learning, which we wrote about here and here. This is because SageMaker is not a plug-n-play SaaS product. You do not simply upload data and then run an algorithm and wait for the results.
Instead SageMaker is a hosted Jupyter Notebook (aka iPython) product. Plus they have taken parts of Google TensorFlow and scikit-learn ML frameworks and written the SageMaker API on top of that. This greatly simplifies TensorFlow programming.
SageMaker provides a cloud where you can run training jobs, large or small. As we show below, it automatically spins up Docker containers and runs your training model across as many CPUs, GPUs, and memory that you need. So it lets you write and run ML models without having to provision EC2 virtual machines yourself to do that. It does the container orchestration for you.
What you Need to Know
In order to follow this code example, you need to understand Jupyter Notebooks and Python.
Jupyter is like a web page Python interpreter. It lets you write code and execute it in place. And it lets you draw tables and graphs. With it you can write programs, hide the code, and then let other users see the results.
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Pricing
SageMaker is not free. Amazon charges you by the second. In writing this paper Amazon billed me $19.45. If I had used it within the first two months of signing up with Amazon it would have been free.
Alexander Ross has covered the video game industry for a decade, writing deep dives on game design, esports tournaments, VR developments, and gaming culture.
