An Introduction to Natural Language Processing (NLP)
Everything we express (either verbally or in written) carries huge amounts of information. The topic we choose, our tone, our selection of words, everything adds some type of information that can be interpreted and value can be extracted from it. In theory, we can understand and even predict human... Read more
NLP is Changing More Than Just Business: Applications of NLP in History, Art, and Higher Ed
Natural language processing (NLP) is affecting more than just your chatbot experience. It has broad-reaching applications in any field where data is king. Here’s a hint: that’s every field. You may not expect NLP to transform fields outside business and finance, but considering how much data humans have produced... Read more
The Difference Between Data Scientists and Data Engineers
A couple of years ago, I was contracted to design a complete online data science program for a university. After some early discussions and planning meetings, it became quite clear that the administrators didn’t have a clear understanding of the difference between data scientists and data engineers. I knew... Read more
The Beginners Guide for Video Processing with OpenCV
Computer vision is a huge part of the data science/AI domain. Sometimes, computer vision engineers have to deal with videos. Here, we aim to shed light on video processing – using Python, of course. This might be obvious for some, but nevertheless, video streaming is not a continuous process,... Read more
Top-Rated Development Tools for Machine Learning
Machine learning is a part of artificial intelligence. This is a developed idea where systems learn from data, find patterns, and make decisions without human intervention. The sole objective is to allow computers to learn automatically without human help and adjust its actions properly. Some of these systems are... Read more
Confidence Intervals for Data Scientists
Confidence interval is a basic statistical concept commonly employed by data scientists. Without a formal background in statistics, however, some data scientists tend to scratch their heads with respect to their understanding of what’s really going on with this notion. In this article, we’ll review the basics of confidence... Read more
Quansight: Connecting the Open Source Coder Community and Industry Together
Below is an interview with Travis Oliphant of Quansight, a platform designed to connect the open source coder community and companies all in the name of open data.   1) Tell me about your background. What brought you to where you are today? I studied math and electrical engineering... Read more
5 ODSC Talks to Teach You Machine Learning Today
The internet provides an abundance of content to teach you how to implement machine learning algorithms. Are you overwhelmed and unsure where to begin? These videos of top-rated Open Data Science Conference talks are a great introduction to the topic and offer a great starting point to launch into... Read more
6 Reasons Why Data Science Projects Fail
In this article, I will dig deep into my years of experience as a tech journalist and practicing data scientist and reflect on numerous conversations I’ve had with companies about their data science projects in order to identify what I’ve seen as the top reasons why many projects fail.... Read more
Deep Learning Finds Fake News with 97% Accuracy
In his article published on opendatascience.com in 2017, George McIntire describes an experiment building a “fake news” classifier using a document-vector model and Naive Bayes approach. He reports an 88% accuracy when classifying a “fake news” dataset which he assembled from various sources. This of course immediately made me wonder if deep neural networks (DNNs)... Read more