Author: /u/AutoModerator Welcome to this week’s entering & transitioning thread! This thread is for any questions about getting started, studying, or transitioning into the data […] Read More
Author: Charles Durfee
Computer Science student with a passion for data science and artificial intelligence.
Author: Vincent Granville This book is intended for busy professionals working with data of any kind: engineers, BI analysts, statisticians, operations research, AI and machine […] Read More
Author: Jason Brownlee Generative Adversarial Networks, or GANs, are an architecture for training generative models, such as deep convolutional neural networks for generating images. The […] Read More
Author: Matt Mayo Editor The Yale School of Management seeks applicants in the field of quantitative marketing for a tenure-track faculty position at the rank […] Read More
Author: Matthew Dearing How can organizations and individuals promote Data Literacy? Data literacy is all about critical thinking, so the time-tested method of Socratic questioning […] Read More
Author: Andrea Manero-Bastin This article was written by Marek Galovič. In this article I want to give you an overview of a RNN model I […] Read More
Author: Jason Brownlee Generative Adversarial Networks, or GANs, are challenging to train. This is because the architecture involves both a generator and a discriminator model […] Read More
Author: Machine learning for everyone startup Intersect Labs launches platform for data analysis TechCrunch Machine learning is the holy grail of data analysis, but unfortunately, that […] Read More
Author: Manu J Also: Resources for developers transitioning into data science; Best Data Visualization Techniques for small and large data; Top Data Science and Machine […] Read More
Author: Stephanie Glen A myriad of options exist for classification. In general, there isn’t a single “best” option for every situation. That said, three popular […] Read More