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Amazon SageMaker In Machine Learning

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Amazon SageMaker

What is a Amazon SageMaker?

Amazon SageMaker helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML.

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Amazon SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps, improving data science team productivity by up to 10x. SageMaker Studio gives you complete access, control, and visibility into each step required to build, train, and deploy models. You can quickly upload data, create new notebooks, train and tune models, move back and forth between steps to adjust experiments, compare results, and deploy models to production all in one place, making you much more productive.

Features Of SageMaker

It Includes:

  • Linear learner,

  • A supervised method for classification and regression

  • Factorization machines for classification and regression.

  • Used In XGBoost For ML Algorighms

  • Image classification based on ResNet, 

  • Seq2seq is a supervised algorithm for predicting sequences

  • K-means is an unsupervised learning method for clustering tasks

  • Principal component analysis used for dimensionality reduction

  • Latent Dirichlet allocation is an unsupervised method used for finding categories in documents

SageMaker Tools

It Includes:

  • Amazon SageMaker

  • Amazon SageMaker Autopilot

  • Amazon SageMaker Ground Truth

  • Amazon SageMaker Data Wrangler

  • Amazon SageMaker Feature Store

  • Amazon SageMaker Clarify

  • Amazon SageMaker Debugger

  • Amazon SageMaker Model Monitor

  • Distributed training libraries

  • Amazon SageMaker Pipelines

  • Amazon SageMaker Edge Manager

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