This week on KDnuggets: More Resources for Women in AI, Data Science, and Machine Learning; Speeding up Scikit-Learn Model Training; Dask and Pandas: No Such Thing as Too Much Data; 9 Skills You Need to Become a Data Engineer; 8 Women in AI Who Are Striving to Humanize the World; and much, much more.
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FeaturesMore Resources for Women in AI, Data Science, and Machine Learning, by Gregory Piatetsky
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Speeding up Scikit-Learn Model Training, by Michael Galarnyk
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Dask and Pandas: No Such Thing as Too Much Data, by Stephanie Kirmer
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9 Skills You Need to Become a Data Engineer, by Dorian Martin
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8 Women in AI Who Are Striving to Humanize the World, by Liudmyla Taranenko
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Products, ServicesA Solid Investment: Banking on Talent Development., by SAS
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Start a career in Computer Science with Penn’s Master in Computer Science and Information Technology, by Coursera
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Tutorials, OverviewsUnderstanding NoSQL Document Databases, by Alex Williams
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Beautiful decision tree visualizations with dtreeviz, by Eryk Lewinson
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11 Essential Code Blocks for Complete EDA (Exploratory Data Analysis), by Susan Maina
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Bayesian Hyperparameter Optimization with tune-sklearn in PyCaret, by Antoni Baum
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Reducing the High Cost of Training NLP Models With SRU++, by Tao Lei, PhD
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Evaluating Object Detection Models Using Mean Average Precision, by Ahmed Gad
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15 common mistakes data scientists make in Python (and how to fix them), by Gerold Csendes
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Getting Started with Distributed Machine Learning with PyTorch and Ray, by Galarnyk, Liaw & Nishihara
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Opinions4 Machine Learning Concepts I Wish I Knew When I Built My First Model, by Terence Shin
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Is It Too Late to Learn AI?, by Frederik Bussler
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Top StoriesTop Stories, Mar 1-7: Top YouTube Channels for Data Science
#kdnuggets 2021 issues #ai #dask #data engineer #data science #machine learning #modeling #pandas #scikit-learn #training #women
