Articles

devices are going to number around 75.44 billion by 2025. The increase in IoT based technology and development support has influenced many fields to start… Read More »IoT for Logistics Industry: How It Promises to Solve Major Problems

The IEEE International Conference on Computer Vision received 4,303 papers and accepted 1,075 for the 2019 summit. Bellow is the best paper award. Source: see paper… Read More »Best 2019 Paper Awards in Computer Vision

Pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. Hexagonal binning with Hexbin:… Read More »Free 2,900-page Manual about Pandas

The title of the eBook is Dive in Deep Learning. Below I list the content of chapter 16, dealing with the math of deep learning.… Read More »Math of Deep Learning: Free Chapter from 832-page eBook

Hello Everyone, I’ve just recently joined this site. Firstly, I would like to share with you all a free and open-sourced tool that I have published… Read More »Introduction and New Open-sourced Tool for Tableau

“It is hard to teach an old dog new tricks.  They’ve only been in business for 155 years.” – Anonymous The Pullman Co (1867), Allied Corp… Read More »Digital Transformation: Preparing your Organization for a World of Constant Change

“Speak Quantum Friend and Enter” . Today, I uploaded to github my new software library called Entanglish (open source, under BSD license). Entanglish is a… Read More »Welcome to Entanglish, a Python library for calculating quantum entanglement

By Soroush Nasiriany, Garrett Thomas, William Wang, Alex Yang. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley. Dated June 24, 2019. This… Read More »Free Book: A Comprehensive Guide to Machine Learning (Berkeley University)

Summary:  99% of our application of NLP has to do with chatbots or translation.  This is a very interesting story about expanding the bounds of… Read More »NLP Picks Bestsellers – A Lesson in Using NLP for Hidden Feature Extraction