A Guide for Applying Machine Learning Techniques in Finance
Does it sound familiar to you? In order to get an idea of how to choose a parameter for a given classifier, you have to cross reference to a number of papers or books, wh...
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Image Segmentation using deconvolution layer in Tensorflow
This article was written by Koustuch on CV-Tricks. In this series of post, we shall learn the algorithm for image segmentation and implementation of the same using Ten...
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...
Bridging Data Science and Business Intuition
Target corporation’s massively profitable data science project threw them into the news spotlight a few years back. Their story makes for a valuable case study in brid...
Machine Learning Summarized in One Picture
Here is a nice summary of traditional machine learning methods, from Mathworks. I also decided to add the following picture below, as it illustrates a method that was ve...
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...
The Weak Karate of Six Sigma
Six Sigma is a quantitative approach to problem solving – to solve certain types of problems. At the root of Six Sigma is an improvement methodology that can be des...
Twelve types of Artificial Intelligence (AI) problems
Background – How many cats does it take to identify a Cat? In this article, I cover the 12 types of AI problems i.e. I address the question : in which scenarios should...
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...