10 Compelling Machine Learning Dissertations from Ph.D. Students
As a data scientist, an integral part of my work in the field revolves around keeping current with research coming out of academia. I frequently scour arXiv.org for late-breaking papers that show trends and fertile areas of research. Other sources of valuable research developments are in the form of... Read more
What is iPaaS and Why Should Your Business Care?
AI, cloud computing, and massive data. It’s getting beyond the capability of most companies and organizations to host and manage the type of infrastructure needed to build and deploy models. Integration Platform as a Service (iPaaS) could be the answer to in house computing and security issues. Cloud integration... Read more
Top 10 Big Data Blunders, Part 2
In the first part of the series, Dr. Stonebraker outlined five ways to know for sure companies are making mistakes in their big data plans and adoptions. He focused a lot on the missed opportunity businesses would have in not hiring the best talent and embracing the move to... Read more
Using Auto-sklearn for More Efficient Model Training
Applying a machine learning algorithm to any number of data-related tasks can be an enormous time saver, but the variable factors associated with creating an algorithm can be daunting. One must consider a variety of design-related decisions, and the risks surrounding the creation of an accurate architecture can make... Read more
Python or R—Or Both?
I was analytically betwixt and between a few weeks ago. Most of my Jupyter Notebook work is done in either Python or R. Indeed, I like to self-demonstrate the power of each platform by recoding R work in Python and vice-versa. I must have a dozen active notebooks, some... Read more
Building Data Science Teams: What Do You Need to Know?
Building a data science team from scratch involves more than just a list of requirements scraped from HR. Your data science team needs to solve problems and provide real business value, necessities that are difficult to describe in the traditional job posting. At ODSC East 2019, Haftan Eckholdt, chief... Read more
3 Unique Ways to Get a Job in Data Science
All too often, job seekers focus too much on building their skill sets without thinking about the softer skills of how to get a job in data science in the first place. It doesn’t matter how good of a data scientist you are – you won’t get a job... Read more
Trends in AI: Towards Learning Systems That Require Less Annotation
There’s a lot of hype surrounding AI. Unfortunately, a lot of it is hyperbolic warnings about how we’ll lose our humanity and the machines will be smarter than we are. Just about every field and institution is preparing for an AI revolution. There’s even a brand new Minister of... Read more
Building a Custom Convolutional Neural Network in Keras
In this article, we’ll walk through building a convolutional neural network (CNN) to classify images without relying on pre-trained models. There are a number of popular pre-trained models (e.g. Inception, VGG16, ResNet50) out there that are helpful for overcoming sampling deficiencies; they have already been trained on many images... Read more
Adversarial Attacks on Deep Neural Networks
Our deep neural networks are powerful machines, but what we don’t understand can hurt us. As sophisticated as they are, they’re highly vulnerable to small attacks that can radically change their outputs. As we go deeper into the capabilities of our networks, we must examine how these networks really... Read more