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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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Build a Search Engine: Semantic Search System Using OpenSearch

PyImageSearch

Text-to-Vector Conversion (Sentence Transformer Model) Inside OpenSearch, the neural search module passes the query text to a pre-trained Sentence Transformer model (from Hugging Face or another ML framework). Implement and analyze search results using Python scripts. Construct and execute a neural search query in OpenSearch.

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Generate financial industry-specific insights using generative AI and in-context fine-tuning

AWS Machine Learning Blog

In entered the Big Data space in 2013 and continues to explore that area. He is actively working on projects in the ML space and has presented at numerous conferences including Strata and GlueCon. He works with strategic customers who are using AI/ML to solve complex business problems. Arghya Banerjee is a Sr.

SQL 122
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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.

ML 98
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16 Companies Leading the Way in AI and Data Science

ODSC - Open Data Science

To deliver on their commitment to enhancing human ingenuity, SAS’s ML toolkit focuses on automation and more to provide smarter decision-making. Plotly In the time since it was founded in 2013, Plotly has released a variety of products including Plotly.py, which, along with Plotly.r,

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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning. Clay Elmore is an AI/ML Specialist Solutions Architect at AWS.

Database 157
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How to Predict Harmful Algal Blooms Using LightGBM and Satellite Imagery

DrivenData Labs

agg ( min_date = ( "date" , min ), max_date = ( "date" , max )) Out[8]: min_date max_date split test 2013-01-08 2021-12-29 train 2013-01-04 2021-12-14 In [9]: # what years are in the data? The severity levels are: severity Density range (cells per mL) 1 10,000,00)" , } } ). python train_gbm_model.py

ML 130