Outliers is one of those issues we come across almost every day in a machine learning modelling. Wikipedia defines outliers as “an observation point that… Read More »Is it ‘always’ necessary to treat outliers in a machine learning model?
P – Value In this blog we will discuss the important functionality of p – value in statistical experiments. Why p – value is the… Read More »Significance of p-value
Myth #1: You can only do research in an academic setting. Not true. There are plenty of research labs owned by big and small companies… Read More »5 Myths About PhD Data Scientists
Sales prediction is an important part of modern business intelligence. First approaches one can apply to predict sales time series are such conventional methods of… Read More »Modern Approaches for Sales Predictive Analytics
Myth #1: You can only do research in an academic setting. Not true. There are plenty of research labs owned by big and small companies… Read More »5 Myths About PhD Data Scientists
Data Scientists 4.0 The 4th Industrial Revolution was publicly announced in 2011 at the Hannover Fair (1). Since then, many resources have been appeared around… Read More »Data Scientists 4.0
Although cognitive computing, which is many a times referred to as AI or Artificial Intelligence, is not a new concept, the hype surrounding it and… Read More »Cognitive computing: Moving From Hype to Deployment
Quite recently we’ve built event analytics for our team and thought to share this experience with you in this post . Many of “out-of-the-box” analytics solutions… Read More »Event Analytics: How to Define User Sessions with SQL
We’ve compiled a list of the hottest events and conferences from the world of Data Science, Machine Learning and Artificial Intelligence happening in 2018. Below… Read More »Data Science, Machine Learning, and AI Conferences and Events 2018
I have completed the following through courses at coursera: R-Programming, Getting and cleaning data – John Hopkins University Introduction to SQL – University of Michigan… Read More »Need guidance: beginner data/business analyst
