DSC Webinar Series: Data Viz: Re-examining what we thought we knew
Instead of well-run experiments and real evidence, many supposed rules are based on opinion, aesthetic judgments, and incomplete or oversimplified studies. In this Data S...
Home » You searched for data science
Search Results for: data science
Dealing With Imbalanced Datasets
Summary: Dealing with imbalanced datasets is an everyday problem. SMOTE, Synthetic Minority Oversampling TEchnique and its variants are techniques for solving this pr...
What type are you? Six Job Categories for Data Scientists
Once dubbed as the sexiest job of the 21st century by The Harvard Business Review, data scientists take pride in having adept technical skills in providing solutions to p...
Are you brave enough to change your Data Habits?
Do you often go with gut feeling rather than data and insights? Is your data stored in separate databases, in different formats with different values? We all have bad ha...
DSC Webinar Series: Case Study: Scaling Data Preparation for Faster Insights
Companies are always looking for ways to improve the way they work with data. The ability to build out a workflow, automate the data blending and preparation, and then an...
Taxonomy of 3D DataViz
Been trying to pull together a taxonomy of 3D data viz. Biggest difference is I think between allocentric (data moves) and egocentric (you move) viewpoints. The differenc...
Big Data Analysis
Big Data is not just the ability to store large amounts of data, more important is what we can do to the data in that large volume, how we use the data with such large vo...
Data Scientists Automated and Unemployed by 2025!
Guest blog post byBill Vorhies Summary: The shortage of data scientists is driving a growing number of developers to fully Automated Predictive Analytic platforms. Some o...
The [Marketing Data Scientist’s] Search for a Home: Part I
A thought provoking series that gives my account of becoming a marketing data scientist hybrid during one of the most chaotic times in the marketing industry, the Big Dat...
Handling imbalanced dataset in supervised learning using family of SMOTE algorithm.
Consider a problem where you are working on a machine learning classification problem. You get an accuracy of 98% and you are very happy. But that happiness doesn’t las...