I have spent much of my career as a graduate student researcher, and now as a Data Scientist in the industry. One thing I have come to realize is that a vast majority of solutions proposed both in academic research papers and in the workplace are just not meant to … Read moreIndustrial strength Natural Language Processing

Introduction In this series, I’ll explain how to create a chat bot that is capable of detecting sentiment, analyzing images, and finally having the basis of a evolving personality. This is part 1 of that series. The Pieces Ruby Sinatra Google Cloud APIs Line (a chat client) Since I live … Read moreBuilding a Sentiment Detection Bot with Google Cloud, a Chat Client, and Ruby.

Things that could go wrong, and how to diagnose if they did. Oct 24, 2018 In this article, you get to look over my shoulder as I go about debugging a TensorFlow model. I did a lot of dumb things, so please don’t judge. Cheat sheet. The numbers refer to sections … Read moreDebugging a Machine Learning model written in TensorFlow and Keras

Computing the Graph With generate_dataset() and linear_regression(), we are now ready to run the program and begin finding our optimal gradient W and bias b! [line 2, 3] x_batch, y_batch = generate_dataset()x, y, y_pred, loss = linear_regression() In this run() function, we start off by calling generate_dataset() and linear_regression() to get … Read moreA line-by-line layman’s guide to Linear Regression using TensorFlow

The perplexity of a discrete probability distribution is defined as: from https://en.wikipedia.org/wiki/Perplexity where H(p) is the entropy of the distribution p(x) and x is a random variable over all possible events. In the previous post, we derived H(p) from scratch and intuitively showed why entropy is the average number of … Read morePerplexity Intuition (and Derivation)

ALife 2018 conference, © Lana Sinapayen Prompted by a video where people thought a human was actually a hyper-realistic robot, I decided to write about how to spot humanoid robots. Here are a few tips! After spending so much time with Alter the android and various hyper-realistic robots, I know … Read moreTelling Apart AI and Humans: #1 Humans VS Androids

Tools to shape the future In many product announcements from Google, Apple and BMW, more and more data will be overlaid in our physical environments through augmented reality or projection. That means not only will data be visualized more, but the visual reality around us will be turned into data. Data … Read moreThe future of data visualization

There is a huge selection of wines on the market and as for a wine lover it is always a quest to select the best wine. US, France, Spain, Germany and many other wine countries with numerous varieties of wines are easily available in any liquor store. Price can also … Read moreWaiting for Weekends: Some Insights on How to Select the Best Wine

First, a couple of pointers to keep in mind when searching for datasets. According to Carnegie Mellon University: 1.- A high-quality dataset should not be messy, because you do not want to spend a lot of time cleaning data. 2.- A high-quality dataset should not have too many rows or … Read moreThe Best Public Datasets for Machine Learning