Deep Learning from first principles in Python, R and Octave – Part 1
This article was written by Tinniam V Ganesh. This is the first in the series of posts, I intend to write on Deep Learning. This post is inspired by the Deep Learning...
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How to build a deep learning model in 15 minutes
This article was written by Montana Low. An open source framework for configuring, building, deploying and maintaining deep learning models in Python. As Instacart h...
Best Artificial Intelligence Technologies to know in 2019
Technology decision-makers are (and also should keep) seeking methods to successfully carry out artificial intelligence innovations into their businesses and, therefore, ...
Fun with maps: Part 1
I love maps. It’s not just a nerdy thing. Map are very helpful visualization tools for a lot of questions from business. Of course, there are number of standard BI tool...
33 Statistical Concepts Explained in Simple English – Part 14
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
30 Statistical Concepts Explained in Simple English – Part 15
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
Data Science 2019 SIAM conference
Since the (non) listed abstract submissions for this year’s conference are presumably from Academia, any preferences for related conferences more accessible and rel...
31 Statistical Concepts Explained in Simple English – Part 9
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlati...
Digital Transformation Horizon 1 to Horizon 3: When Is Innovation Really Innovation?
In the early 2000’s, IBM Deep Blue was on the lookout for its next Grand Challenge. It had achieved an exhilarating win over chess grand master Garry Kasparov in 1997...
Comparing Model Evaluation Techniques Part 1: Statistical Tools & Tests
Evaluating a model is just as important as creating the model in the first place. Even if you use the most statistically sound tools to create your model, the end result ...