Workplace Flexibility is the New Norm
A lot has changed since last year due to the pandemic. Many of us started working from home, and the world experienced a rapid workplace transformation. Organizations an...
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Web development trends for 2021 and the latest web technology stack
Standards in web development can change faster than they can implement. To stay one step ahead, it is essential to keep an eye on the prevailing trend...
DSC Podcast Series: NVIDIA-Powered Data Science Solutions
This latest Data Science Central podcast covers how Data Science essentially spans every industry, discusses a day in the life of a data scientist working on CPUs vs. GPU...
DSC Weekly Digest 26 April 2021
Connectedness and NFTs One of the more fascinating things about data, especially as you gather more and more of it together, is the extent to which information is connect...
What is Liskov’s Substitution Principle?
In this article, we will explore the Liskovs substitution principle, one of the SOLID principles and how to implement it in a Pythonic way. The SOLID principles entai...
Question Answering based on Knowledge Graphs
Why Question-Answering Engines? The search only for documents is outdated. Users who have already adopted a question-answering (QA) approach with their personal devices, ...
Mitigating Emerging Cyber Security Threats Using Artificial Intelligence
Last week, I taught a cybersecurity course at the University of Oxford case. I created a case study for my class based on an excellent recent paper: Deep Learning-Based A...
Why you should put Fixed Point Strategies in Your Toolbox
Fixed point strategies can approximate infinite depth. The methods are easy to train/implement. This essential set of tools can model and analyze a wide range of DS probl...
Fixed Point Strategies
Fixed point strategies give a unifying framework to analyze, model, and solve a wide range of problems. The methods are easy to train/implement, yet can approximate ...
Honey I Shrunk the Model: Why Big Machine Learning Models Must Go Small
Bigger is not always better for machine learning. Yet, deep learning models and the datasets on which theyre trained keep expanding, as researchers race to outdo one ...