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Intro. How I Plan to Teach Myself Deep Learning Using Only Free Resources Learning Deep Learning Series Part 1: Videos Learning Deep Learning Part 2: Online Courses Learning Deep Learning Part 3: Github Repos We’re already familiar with the popularity of big data of the past five or so... Read more
Building a Chatbot: analysis & limitations of modern platforms
The TryoLabs R&D department is in the process of releasing a very interesting AI open source toolkit oriented towards image processing, utilizing state of the art Deep Learning technologies and build upon TensorFlow and Sonnet. Come see Javier Rey, Research Engineer and Alan Descoins, CTO from TryoLabs Speak at ODSC... Read more
Deep Learning Research Review Week 2: Reinforcement Learning
This is the 2nd installment of a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summarizing and explaining research papers in specific subfields of deep learning. This week focuses on Reinforcement Learning. Last time was Generative Adversarial Networks ICYMI Introduction to Reinforcement Learning... Read more
Artificial Neural Networks (ANN) Introduction
Training a Computer to Recognize your Handwriting Take a look at the picture below above and try to identify what it is. One should be able to tell that it is a giraffe, despite it being strangely fat. We recognize images and objects instantly, even if these images are... Read more
Stacking models for improved predictions
If you have ever competed in a Kaggle competition, you are probably familiar with the use of combining different predictive models for improved accuracy which will creep your score up in the leader board. While it is widely used, there are only a few resources that I am aware of... Read more
Intro to D3
Abstract: Visualizations are the most important way we can intuitively make sense of our data. And the best way to dig deeper into our data is to make those visualizations interactive. Everyone from the New York Times to Google is using interactive visualizations to tell stories and analyze data.... Read more
Can neural networks solve any problem?
Visualizing the Universal Approximation Theorem At some point in your deep learning journey you probably came across the Universal Approximation Theorem. A feedforward network with a single layer is sufficient to represent any function, but the layer may be infeasibly large and may fail to learn and generalize correctly.... Read more
Learning in Brains and Machines (1): Temporal Differences
We all make mistakes, and as is often said, only then can we learn. Our mistakes allow us to gain insight, and the ability to make better judgements and fewer mistakes in future. In their influential paper, the neuroscientists Robert Rescorla and Allan Wagner put this more succinctly, ‘organisms only learn when... Read more
Introduction What profession did Harvard call the Sexiest Job of the 21st Century? That’s right… the data scientist. Ah yes, the ever mysterious data scientist. So what exactly is the data scientist’s secret sauce, and what does this “sexy” person actually do at work every day? This article is... Read more
 This blog post is on song lyric sentiment. Feel free to fork this code from GitHub. Sentiment Analysis is one of the techniques of NLP (Natural Language Processing). It is part of NLU (Natural Language Understanding). It allows us to classify the sentiment of a text, positive or negative,... Read more