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7 of The Coolest Machine Learning Topics of 2021 at ODSC West

KDnuggets

At our upcoming event this November 16th-18th in San Francisco, ODSC West 2021 will feature a plethora of talks, workshops, and training sessions on machine learning topics, deep learning, NLP, MLOps, and so on.

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Write about what you learn. It pushes you to understand topics better.

Hacker News

Write about what you learn. It pushes you to understand topics better. Sometimes the gaps in our knowledge only become clear when explaining things to others.

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A Collection Of Free Data Science Courses From Harvard, Stanford, MIT, Cornell, and Berkeley

KDnuggets

Learn everything about data science by exploring our curated collection of free courses from top universities, covering essential topics from math and programming to machine learning, and mastering the nine steps to become a job-ready data scientist.

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Scaling Data Quality with Computer Vision on Spatial Data

insideBIGDATA

In this contributed article, editorial consultant Jelani Harper discusses a number of hot topics today: computer vision, data quality, and spatial data. Computer vision is an extremely viable facet of advanced machine learning for the enterprise. Its utility for data quality is evinced from some high profile use cases.

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The Definitive Guide to Embedded Analytics

The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic. It will show you what embedded analytics are and how they can help your company. It will show you how to select the right solution and what investments are required for success.

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#insideBIGDATApodcast: Three Metrics for Measuring Enterprise AI Success

insideBIGDATA

Welcome to the insideBIGDATA series of podcast presentations, a curated collection of topics relevant to our global audience. Topics include big data, data science, machine learning, AI, and deep learning. Today's guest is Supreet Kaur, Assistant Vice President at Morgan Stanley.

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Book Review: Tree-based Methods for Statistical Learning in R

insideBIGDATA

It’s a wonderful learning resource for tree-based techniques in statistical learning, one that’s become my go-to text when I find the need to do a deep dive into various ML topic areas for my work. Here’s a new title that is a “must have” for any data scientist who uses the R language.