Visualizing Natural Gas Withdrawals, Consumption and Prices
Contributed by Ben Townson. He enrolled in the NYC Data Science Academy 12-week full time Data Science Bootcamp program taking place between July 5th to September 23rd,...
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Your AI Shrink Will See You Now
Summary: Where do we look to see the most advanced chatbots and the most complete application of AI? Chatbots designed as ‘artificially intelligent psychological co...
Demystifying Artificial Intelligence – Explained in One Picture
This article was written by Swami Chandrasekaran. Click on picture to zoom in. Source: Here. When I wrote my blog post Becoming a Data Scientist— Curriculum via Metrom...
Statistical Tests – When to use Which ?
For a person being from a non-statistical background the most confusing aspect of statistics, are always the fundamental statistical tests, and when to use which. This bl...
Watson – Time to Prune the ML Tree?
Summary: IBM’s Watson QAM (Question Answering Machine), famous for its 2011 Jeopardy win was supposed to bring huge payoffs in healthcare. Instead both IBM and its ...
Can we use deliberate practise for learning to code #AI and #machinelearning
In this post, I explore if ideas of deliberate practise can be applied to teaching coding for Artificial Intelligence / Machine Learning I am exploring these ideas in a...
Learn How to Code and Deploy Machine Learning Models on Spark Structured Streaming
This post is a token of appreciation for the amazing open source community of Data Science, to which I owe a lot of what I have learned. For last few months, I have been ...
How Can You Find The Best Machine Learning Frameworks?
A list of machine learning frameworks has come into the picture for the development and deployment of the AI apps. These frameworks will ditch the entire flow of developm...
Combining CNNs and RNNs – Crazy or Genius?
Summary: There are some interesting use cases where combining CNNs and RNN/LSTMs seems to make sense and a number of researchers pursuing this. However, the latest tren...
17 Cool Problems with a Statistical Flavor
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, ...