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Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas

AWS Machine Learning Blog

Conventional ML development cycles take weeks to many months and requires sparse data science understanding and ML development skills. Business analysts’ ideas to use ML models often sit in prolonged backlogs because of data engineering and data science team’s bandwidth and data preparation activities.

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Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning Blog

Several activities are performed in this phase, such as creating the model, data preparation, model training, evaluation, and model registration. We walk through an example notebook to demonstrate how you can use this unification during the model development data science lifecycle. factors_affecting_model_efficiency="No.",

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Revolutionize your ML workflow: 5 drag and drop tools for streamlining your pipeline

Data Science Dojo

These tools are designed to be user-friendly and do not require any coding skills, making it easier for data scientists to build models quickly and efficiently. Explore the top 10 machine learning demos and discover cutting-edge techniques that will take your skills to the next level.

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State of Machine Learning Survey Results Part Two

ODSC - Open Data Science

Machine learning practitioners are often working with data at the beginning and during the full stack of things, so they see a lot of workflow/pipeline development, data wrangling, and data preparation. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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6 AI tools revolutionizing data analysis: Unleashing the best in business

Data Science Dojo

Explore the top 10 machine learning demos and discover cutting-edge techniques that will take your skills to the next level. Case studies highlighting its effectiveness Scikit-learn has been used in a variety of successful data analysis projects. It is open-source, so it is free to use and modify.

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15 Fan-Favorite Speakers & Instructors Returning for ODSC East 2025

ODSC - Open Data Science

Allen Downey, PhD, Principal Data Scientist at PyMCLabs Allen is the author of several booksincluding Think Python, Think Bayes, and Probably Overthinking Itand a blog about data science and Bayesian statistics. in computer science from the University of California, Berkeley; and Bachelors and Masters degrees fromMIT.

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Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning Blog

As attendees circulate through the GAIZ, subject matter experts and Generative AI Innovation Center strategists will be on-hand to share insights, answer questions, present customer stories from an extensive catalog of reference demos, and provide personalized guidance for moving generative AI applications into production.

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