Features

• The Machine & Deep Learning Compendium Open Book, by Ori Cohen
• Easy SQL in Native Python, by Matthew Mayo
• Introduction to Automated Machine Learning, by Kevin Vu
• How to be a Data Scientist without a STEM degree, by Terence Shin
• What Is The Real Difference Between Data Engineers and Data Scientists?, by Springboard

 Products, Services

• How to label time series efficiently – and boost your AI, by Visplore
• DATAcated Expo, Oct 5, Live-streamed,
  Explore new AI / Data Science Tech, by DATAcated
• Free virtual event: Big Data and AI Toronto, by Corp Agency

 Tutorials, Overviews

• How to Find Weaknesses in your Machine Learning Models, by Michael Berk
• 5 Must Try Awesome Python Data Visualization Libraries, by Roja Achary
• Paradoxes in Data Science, by Pier Paolo Ippolito
• Introducing TensorFlow Similarity, by Matthew Mayo
• Don’t Touch a Dataset Without Asking These 10 Questions, by Sandeep Uttamchandani
• How to get Python PCAP Certification: Roadmap, Resources, Tips For Success, Based On My Experience, by Mehul Singh
• Adventures in MLOps with Github Actions, Iterative.ai, Label Studio and NBDEV, by Soellinger & Kunz
• Data Engineering Technologies 2021, by Tech Ninja
• If You Can Write Functions, You Can Use Dask, by Hugo Shi
• 15 Must-Know Python String Methods, by Soner Yıldırım

 Opinions

• What 2 years of self-teaching data science taught me, by Vishnu U

 Top Stories

• Top Stories, Sep 13-19: Data Scientists Without Data Engineering Skills Will Face the Harsh Truth; The Machine & Deep Learning Compendium Open Book, by KDnuggets
• KDnuggets Top Blogs Rewards for August 2021, by Gregory Piatetsky

 Jobs

• See our recent jobs in AI, Analytics, Data Science, Machine Learning
• You can post a free short entry on KDnuggets jobs page for an industry or academic job related to AI, Big Data, Data Science, or Machine Learning, email – see details at kdnuggets.com/jobs

 Image of the week

From Introduction to Automated Machine Learning