Book: Data Science for the Layman: No Math Added
Want to get started on data science? Our promise: no math added. This book has been written in layman’s terms as a gentle introduction to… Read More »Book: Data Science for the Layman: No Math Added
Want to get started on data science? Our promise: no math added. This book has been written in layman’s terms as a gentle introduction to… Read More »Book: Data Science for the Layman: No Math Added
Guest blog by Ashwin Rao. Ashwin is Vice President, Data Science & Optimization at Target. The tech industry has gone berserk – everyone wants to develop… Read More »Key Machine Learning PreReq: Viewing Linear Algebra through the right lenses
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… Read More »Data Scientists Automated and Unemployed by 2025!
This infographic was produced by Springboard, and it lists a few short online, inexpensive courses along with some university programs, leading to a certificate. The… Read More »18 Data Science Certificates Rated
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… Read More »The [Marketing Data Scientist’s] Search for a Home: Part I
This formula-free summary provides a short overview about how PCA (principal component analysis) works for dimension reduction, that is, to select k features (also called… Read More »Introduction to Principal Component Analysis
Originally posted on Data Science Central This infographic on Shopper Marketing was created by Steve Hashman and his team. Steve is Director at Exponential Solutions (The CUBE) Marketing. … Read More »What Happens in 60-Seconds Online? – Infographics
Summary: What are the real threats of job loss from real and AI enhanced virtual robots? How do we position ourselves and our children to… Read More »Keeping Your Job in the Age of Automation
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… Read More »Handling imbalanced dataset in supervised learning using family of SMOTE algorithm.