Until very recently, most organizations have seen two distinct, non-overlapping work streams when building an AI enabled application: a development path and a data scienc...
Logistic regression (LR) models estimate the probability of a binary response, based on one or more predictor variables. Unlike linear regression models, the dependent va...
This article was written by Hunter Heidenreich. Looking into what a generative adversarial network is to understand how they work. What’s in a Generative Model? Befor...
image source – wikipedia Update Hello all, The first book is posted on data science central here, and the community group is here. Please join the community so you...
In this latest Data Science Central Deep Learning Fundamentals Series webinar, we will cover the fundamentals behind TensorFlow and how to apply them within a convolution...
First days after the celebration of the New Year is the time when looking back we can analyze our actions, promises and draw conclusions whether our predictions and expec...
Originally posted here. From detecting anomalies to understanding what are the key elements in a network, or highlighting communities, graph analytics reveal...
Call it a “Forrest Gump moment;” an instance of being in the right place at the right time for no other reason than just plain luck. A “Forrest Gump moment” is ...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
Imagine it’s 1994 and the dawn of the internet. In many ways, it is. Entrepreneurs are once again laying the rails for a new digital world. And, just like the fi...