An initial overview of knowledge graphs, their main components, and an insight into how fundamental they are to empower intelligent systems.

Sourced through Scoop.it from: www.ambiverse.com

Provides a great overview of knowledge graphs, their components & uses.  Also, references a number of the largest knowledge graphs available.

Of course, lying with statistics has been a thing for a long time, but charts tend to spread far and wide these days. There’s a lot of them. Some don’t tell the truth. Maybe you glance at it and that’s it, but a simple message sticks and builds. Before you know it, Leonardo DiCaprio spins […]

Sourced through Scoop.it from: www.kdnuggets.com

The dirty little secret of automation is that people make it possible.

Sourced through Scoop.it from: hbr.org

Project Jupyter aims to create an ecosystem of open source tools for interactive computation and data analysis, where the direct participation of humans in the computational loop—executing code to understand a problem and iteratively refine their approach—is the primary consideration. Anchoring Jupyter around humans is key to the project; it helps us both narrow our […]

AI is mainstream and its applications are limitless; here is the AI forecast for 2017 from some of the experts in the industry. Source: AI Forecast for 2017

Top Free Data Mining Software: Review of 50 + top data mining freeware including Orange, Weka,Rattle GUI, Apache Mahout, SCaViS, RapidMiner, R, ML-Flex, Databionic ESOM Tools, Natural Language Toolkit, SenticNet API , ELKI , UIMA, KNIME, Chemicalize.org , Vowpal Wabbit, GNU Octave, CMSR Data Miner, Mlpy, MALLET, Shogun, Scikit-learn, LIBSVM, LIBLINEAR, Lattice Miner, Dlib, Jubatus, […]

“propose one possible taxonomy of what a data scientist does, in roughly chronological order: Obtain, Scrub, Explore, Model, and iNterpret” Source: dataists » A Taxonomy of Data Science

These 15 predicted trends will shape the big data and analytics market in 2017.

Sourced through Scoop.it from: www.itworld.com

When it comes to fraud prevention, it is important to recognize that technology alone is insufficient. Fraud managers with years of experience fighting fraud can never be replaced by a machine, but a combination of the two entities can produce far better results. People dedicate their lives to committing fraud with the help of technology; […]