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Top Low-Code and No-Code Platforms for Data Science in 2023

ODSC - Open Data Science

H2O AutoML: A powerful tool for automating much of the more tedious and time-consuming aspects of machine learning, H2O AutoML provides the user(s) with a set of algorithms and tools to automate the entirety of the machine learning workflow. Auto-ViML : Like PyCaret, Auto-ViML is an open-source machine learning library in Python.

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Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence

AWS Machine Learning Blog

Operational excellence in IDP means applying the principles of robust software development and maintaining a high-quality customer experience to the field of document processing, while consistently meeting or surpassing service level agreements (SLAs). This post focuses on the Operational Excellence pillar of the IDP solution.

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Accelerate time to business insights with the Amazon SageMaker Data Wrangler direct connection to Snowflake

AWS Machine Learning Blog

Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code. Enter a name for your endpoint.

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Time series forecasting with Amazon SageMaker AutoML

AWS Machine Learning Blog

In this blog post, we explore a comprehensive approach to time series forecasting using the Amazon SageMaker AutoMLV2 Software Development Kit (SDK). SageMaker AutoMLV2 is part of the SageMaker Autopilot suite, which automates the end-to-end machine learning workflow from data preparation to model deployment.

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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning Blog

It also helps achieve data, project, and team isolation while supporting software development lifecycle best practices. It’s a binary classification problem where the goal is to predict whether a customer is a credit risk. After you have completed the data preparation step, it’s time to train the classification model.

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Is your model good? A deep dive into Amazon SageMaker Canvas advanced metrics

AWS Machine Learning Blog

In this post, we show how a business analyst can evaluate and understand a classification churn model created with SageMaker Canvas using the Advanced metrics tab. Cost-sensitive classification – In some applications, the cost of misclassification for different classes can be different.

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Operationalizing knowledge for data-centric AI

Snorkel AI

This is a platform that supports this new data-centric development loop. It’s this fast, iterative process that begins to look more like software development (no code, or via code) rather than what ML often looks like today, which is waiting weeks or months manually labeling datasets for every single turn of the crank.