A decade ago, machine learning was simply a concept but today it has changed the way we interact with technology. Devices are becoming smarter, faster and better, with Machine Learning at the helm.
Document worth reading： “Taxonomy of Big Data： A Survey”
The Big Data is the most popular paradigm nowadays and it has almost no untouched area. For instance, science, engineering, economics, business, social science, and government. The Big Data are used to boost up the organization performance using massive amount of dataset. The Data are assets of the organization, and these data gives revenue to the organizations. Therefore, the Big Data is spawning everywhere to enhance the organizations’ revenue. Thus, many new technologies emerging based on Big Data. In this paper, we present the taxonomy of Big Data. Besides, we present in-depth insight on the Big Data paradigm. Taxonomy of Big Data: A Survey
Top November Stories： The Most in Demand Skills for Data Scientists; What is the Best Python IDE for Data Science?
Intuit： Staff Data Scientist [Mountain View, CA]
At: Intuit
Location: Mountain View, CAWeb: intuit.comPosition: Staff Data Scientist
Machine Learning & AI Main Developments in 2018 and Key Trends for 2019
At KDnuggets, we try to keep our finger on the pulse of main events and developments in industry, academia, and technology. We also do our best to look forward to key trends on the horizon.
Day 11 – little helper trim
We at STATWORX work a lot with R and we often use the same little helper functions within our projects. These functions ease our daily work life by reducing repetitive code parts or by creating overviews of our projects. At first, there was no plan to make a package, but soon I realised, that it will be much easier to share and improve those functions, if they are within a package. Up till the 24th December I will present one function each day from helfRlein. So, on the 11th day of Christmas my true love gave to me…
Introduction to Named Entity Recognition
By Suvro Banerjee, Machine Learning Engineer @ Juniper Networks
Learning Machine Learning vs Learning Data Science
By Terran Melconian, enterpreneur and consultant, and Trevor Bass, edX
Let Automation Carry You from BI to AI in 2019
By now it’s clear that businesses that execute on artificial intelligence (AI) successfully are the ones that will move from doing one-off analysis, and even one-off models, to being able to deftly manage hundreds (maybe even thousands) of models in production. And it should also be clear that the only avenue to that kind of scale is automation.
Le Monde puzzle [#1075]
A new Le Monde mathematical puzzle in the digit category: