Deep data science is a branch of data science that has little if any overlap with closely related fields such as machine learning, computer science, operations research,...
This is a quick, short and concise tutorial on how to impute missing data. Previously, we have published an extensive tutorial on imputing missing values with MICE packa...
Source for picture: click here Python Theano is a python library for defining and evaluating mathematical expressions with numerical arrays. Keras is a minimalist, hig...
1 Background Data science is first and foremost a talent-based discipline and capability. Platforms, tools and IT infrastructure play an important but s...
In an earlier blog, “Need for DYNAMICAL Machine Learning: Bayesian exact recursive estimation”, I introduced the need for Dynamical ML as we now enter the “Walk�...
Machine Learning today tends to be “open-loop” – collect tons of data offline, process them in batches and generate insights for eventual action. There is an emergi...
Bernard Marr is a best-selling business author, keynote speaker and consultant in big data, analytics and enterprise performance. As the founder and CEO of the Advanced P...
The Data-Driven Weekly is kicking off 2016 by exploring how big data and analytics is powering data-driven business in different industries. First off is the world of agr...
Guest blog post by Christopher Dole and other contributors, originally posted here. Created by SoothSayerAnalytics. Deep Learning is one of the most revolutionary an...
Guest blog post by Martijn Theuwissen, co-founder at DataCamp. Other R resources can be found here, and R Source code for various problems can be found here. A data sc...
We are in the process of writing and adding new material (compact eBooks) exclusively available to our members, and written in simple English, by world leading experts in AI, data science, and machine learning.