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sktime?—?Python Toolbox for Machine Learning with Time Series

ODSC - Open Data Science

sktime — Python Toolbox for Machine Learning with Time Series Editor’s note: Franz Kiraly is a speaker for ODSC Europe this June. Be sure to check out his talk, “ sktime — Python Toolbox for Machine Learning with Time Series ,” there! Welcome to sktime, the open community and Python framework for all things time series.

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Top 25 AI Tools for Software Development in 2025

Marktechpost

TabNine TabNine is an AI-powered code auto-completion tool developed by Codota, designed to enhance coding efficiency across a variety of Integrated Development Environments (IDEs). Kite Kite is an AI-driven coding assistant specifically designed to accelerate development in Python and JavaScript.

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Machine Learning with MATLAB and Amazon SageMaker

Flipboard

Because we have a model of the system and faults are rare in operation, we can take advantage of simulated data to train our algorithm. Our objective is to demonstrate the combined power of MATLAB and Amazon SageMaker using this fault classification example. Install Python if necessary. classifierModel = fitctree(.

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Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

Flipboard

Overview of solution In this post, we go through the various steps to apply ML-based fuzzy matching to harmonize customer data across two different datasets for auto and property insurance. Run an AWS Glue ETL job to merge the raw property and auto insurance data into one dataset and catalog the merged dataset.

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Hosting ML Models on Amazon SageMaker using Triton: XGBoost, LightGBM, and Treelite Models

AWS Machine Learning Blog

With the ability to solve various problems such as classification and regression, XGBoost has become a popular option that also falls into the category of tree-based models. These models have long been used for solving problems such as classification or regression. One of the most popular models available today is XGBoost.

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Falcon 2 11B is now available on Amazon SageMaker JumpStart

AWS Machine Learning Blog

The Falcon 2 11B model is available on SageMaker JumpStart, a machine learning (ML) hub that provides access to built-in algorithms, FMs, and pre-built ML solutions that you can deploy quickly and get started with ML faster. It’s built on causal decoder-only architecture, making it powerful for auto-regressive tasks.

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Host ML models on Amazon SageMaker using Triton: CV model with PyTorch backend

AWS Machine Learning Blog

One of the primary reasons that customers are choosing a PyTorch framework is its simplicity and the fact that it’s designed and assembled to work with Python. TorchScript is a static subset of Python that captures the structure of a PyTorch model. Triton uses TorchScript for improved performance and flexibility.

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