Category: Data Science

Author: Gregory Piatetsky Also: Deep Neural Networks and the Jennifer Aniston Neuron; Don’t Democratize Data Science. Go to Source

Author: Sharmistha Chatterjee Scaling AI with Dynamic Inference Paths in Neural Networks Introduction IBM Research, with the help of the University of Texas Austin and […] Read More

Author: Matt Mayo Editor In comparison with the other open source machine learning libraries, PyCaret is an alternate low-code library that can be used to […] Read More

Author: Sandipan Dey This is the 2nd part of the article on a few applications of Fourier Series in solving differential equations. All the problems […] Read More

Author: Matt Mayo Editor Also: 5 Ways to Detect #Outliers That Every #DataScientist Should Know #Python Code; The State of AI and Machine Learning 2020 […] Read More

Author: Stephanie Glen The following graphic is based on Sam Priddy’s excellent DSC/Tableau Webinar How to Accelerate and Scale Your Data Science Workflows. Sam covered many […] Read More

Author: Jesus Rodriguez Uber machine learning runtime Michelangelo has been in operation for a few years. What has the Uber team learned? Go to Source

Author: Matt Mayo Editor The major advantage of focusing on AI-based methods is that they tackle each of the challenges faced by farmers from seed […] Read More

Author: Vincent Granville Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for […] Read More

Author: Matt Mayo Editor A step-by-step beginner’s guide to containerize and deploy ML pipeline serverless on AWS Fargate. Go to Source