Interview with Flowcast CTO: AI / Machine Learning in Fintech
Flowcast’s Co-founder and CTO, Winnie Cheng was recently interviewed by Sandhya Krishanmurthy, COO of the FinTech School, for the latter’s FinTech Core 101 course. Th...
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How to evaluate Data Science models ?
In today’s Digital age, insights received from data science are extremely important to deliver the best customer experience. Data Scientists use various techniques...
Linear Regression in Tensorflow
Tensorflow is an open source machine learning (ML) library from Google. It has particularly became popular because of the support for Deep Learning. Apart from that it...
8 Deep Data Science Articles
Deep data science is a branch of data science that has little if any overlap with closely related fields such as machine learning, computer science, operations research,...
Mary Meeker, Analytics, and the Future of the Internet
Summary: In this review of Mary Meeker’s annual Internet Trends report for 2016 we’ll look for the advanced analytics that makes these trends possible. It’s that...
Kcore Data Science Influencers: Top 10
Kcore Analytics is a website that developed an end-to-end framework to find the Influencers in complex social networks like Twitter. The big innovation in their approach...
Logistic Regression and Maximum Entropy explained with examples and code
Logistic Regression is one of the most powerful classification methods within machine learning and can be used for a wide variety of tasks. Think of pre-policing or pr...
Outlier Detection with Parametric and Non-Parametric methods
Dealing with Outliers is like searching a needle in a haystack This is a guest repost by Jacob Joseph. An Outlier is an observation or point that is distant from other ob...
Introduction to Machine Learning / Data Mining
Machine Learning? Data Mining? Well, there is a little bit difference between machine learning and data mining although I don’t see any difference between them. See...
Scikit-Learn Tutorial Series
Kaggle released a series with tutorials in their blog. I recommend to anyone who is starting or want to learn more about the tool. Intro to machine learning with scikit-l...