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amazon sagemaker

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Getting Started with SageMaker Ground Truth Private Workforce


Before we begin, let’s quickly talk about what Amazon SageMaker is and what it is used for. If this is your first time learning about Amazon SageMaker, it is the machine learning platform of AWS that helps solve the different requirements of data scientists, developers, and machine learning practitioners.  It has several features and capabilities that assist in the different stages of the machine learning process. In this tutorial, we will focus on SageMaker Ground Truth and how it helps data science teams get access to clean labeled datasets.  When performing machine learning experiments, getting access to labeled datasets is [...]

Getting Started with SageMaker Ground Truth Private Workforce2021-11-28T10:18:04+00:00

Scalable Data Processing and Transformation using SageMaker Processing (Part 2 of 2)


In this 2-part tutorial, we will focus on SageMaker Processing and how we can use it to solve our data processing needs. Our overall goal is to demonstrate how to use SageMaker Processing to help us perform Min-Max scaling on a dataset in its own dedicated and easily scalable environment.  If you are looking for Part 1, you can find it here. As mentioned in Part I, we have divided this tutorial into 4 sections: [1] Synthetic Data Generation (found in PART I) [2] Using MinMaxScaler without the managed infrastructure support of SageMaker Processing (found in PART I) [3] Using [...]

Scalable Data Processing and Transformation using SageMaker Processing (Part 2 of 2)2021-11-04T11:28:14+00:00

Amazon SageMaker


Bookmarks Concepts Optimization Monitoring Pricing Note Validate Your Knowledge A fully managed service that allows data scientists and developers to easily build, train, and deploy machine learning models at scale. Provides built-in algorithms that you can immediately use for model training. Also supports custom algorithms through docker containers. One-click model deployment. Concepts Hyperparameters It refers to a set of variables that controls how a model is trained. You can think of them as “volume knobs” that you can tune to acquire your model’s objective. Automatic Model Tuning Finds the best version [...]

Amazon SageMaker2021-05-07T11:23:59+00:00

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