A Look Into ODSC Europe 2020 Focus Areas
This September, the ODSC Europe 2020 Virtual Conference will be focusing on the topics that are trending in data science in 2020 and into 2021. Although you might have heard about some of these focus areas a lot over the last year or so, they are constantly evolving and... Read more
Modeling Classification Trees
Decision trees (DTs) are one of the most popular algorithms in machine learning: they are easy to visualize, highly interpretable, super flexible, and can be applied to both classification and regression problems. DTs predict the value of a target variable by learning simple decision rules inferred from the data... Read more
How to Convince Your Boss to Attend ODSC Europe 2020
Everyone practicing in the field of data science is faced with the same dilemma: how to stay on top of projects and stay current in a field that seems to change rapidly every six months. Getting out of the office can help you focus on building new skills, building... Read more
Enhancing Discovery in Data Science Through Novelty in Machine Learning
Note: Kirk will present two training sessions at the ODSC Europe 2020 Virtual Conference. One will focus on “Solving the Data Scientist’s Dilemma: the Cold-Start Problem with 10+ Machine Learning Examples” and the other will look at “Atypical Applications of Typical Machine Learning Algorithms.” I have always appreciated the... Read more
Machine Learning: Active Failures and Latent Conditions
Machine learning and AI applications are advancing in increasingly critical domains such as medicine, aviation, banking, finances, and more.  These applications not only are shaping the way in which industries are operating, but also how people are interacting and using their platforms/technologies. That said, it is of fundamental importance... Read more
Smoothing Data in SQL
A problem found throughout the world of data is how to distinguish signal from noise. When dealing with data that comes in a sequence, such as time-series data (the most familiar example but by no means the only example), a frequent method of dealing with the problem is to... Read more
Deep Learning with TensorFlow 2 & PyTorch
Deep Learning with TensorFlow 2 & PyTorch I’m greatly honored to be leading the charge on ODSC’s exciting new AI+ Training platform, which brings ODSC’s world-leading ability to provide professional training to data scientists into the digital realm while nevertheless retaining an intimate and engaging experience for attendees.  My... Read more
Using the ‘What-If Tool’ to Investigate Machine Learning Models
In this era of explainable and interpretable Machine Learning, one merely cannot be content with simply training the model and obtaining predictions from it. To be able to really make an impact and obtain good results, we should also be able to probe and investigate our models. Apart from... Read more
Cameras’ biggest recent advancements have come from AI, not sensors and lenses. Over the past couple of years, technology has enabled staggering advances in photography. AI is transforming both the way we shoot photos and how we edit them. As ‘computer vision’ becomes an important part of other new... Read more
Country-Wise Visual Analysis of Music Taste Using Spotify’s API & Seaborn in Python
I recently started using Spotify and was amazed by the sophisticated technology that drives Spotify’s recommendation system based on collaborative filtering and NLP. In this project, I investigated country-specific music preferences. Data Acquisition: I scrapped the data from Spotify’s weekly regional chart’. It is a weekly list of top... Read more