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Deep Learning Is Easy – Learn Something Harder
Caveat: This post is meant address people who are completely new to deep learning and are planning an entry into this field. The intention is to help them think critically about the complexity of the field, and to help them tell apart things that are trivial from things that are...
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Neural Networks Are Impressively Good at Compression
I’m trying to get into neural networks. There have been a couple big breakthroughs in the field in recent years and suddenly my side project of messing around with programming languages seeme…
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Automatically grading multiple choice exams from photos using Python and OpenCV
Discover how to build a bubble sheet multiple choice scanner and test grader using Optical Mark Recognition (OMR) along with Python, OpenCV, computer vision
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Number plate recognition with Tensorflow
Over the past few weeks I’ve been dabbling with deep learning, in particular convolutional neural networks . One standout paper from recent times is Google’s Multi-digit Number Recognition from Street View . This paper describes a system for extracting house numbers from street view imagery using a single end-to-end…
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A Visual and Interactive Guide to the Basics of Neural Networks
Discussions: Hacker News (63 points, 8 comments), Reddit r/programming (312 points, 37 comments) Translations: Arabic, French, Spanish Update: Part 2 is now live: A Visual And Interactive Look at Basic Neural Network Math Motivation I’m not a machine learning expert. I’m a software engineer by training and I’ve had…
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Image Completion with Deep Learning in TensorFlow
Content-aware fill is a powerful tool designers and photographers use to fill in unwanted or missing parts of images. Image completion and inpainting are closely related technologies used to fill in missing or corrupted parts of images. There are many ways to do content-aware fill, image completion, and inpainting. In…
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Simple questions to help reduce AI hype
AI is a young field full of amazing potential. This mystery and lack of understanding allows for hype to grow unchecked.
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Machine Learning 101: What Is Regularization?
Posts and writings by Datanice
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Bayesian Machine Learning Explained
So you know the Bayes rule. How does it relate to machine learning? It can be quite difficult to grasp how the puzzle pieces fit together - we know …
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How to Code and Understand DeepMind's Neural Stack Machine in Python
A machine learning craftsmanship blog.
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Voice Recognition and Text to Speech in Python
It’s tough for an aspiring Iron Man to work on creating their personal AI assistant on the weekends. Like any other time-pressured inventor without a PhD in computer science and linguistics, …
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Deep Reinforcement Learning: Pong from Pixels
Musings of a Computer Scientist.
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A Basic Introduction to Neural Networks (2007)
Although the mathematics involved with neural networking is not a trivial matter, a user can rather easily gain at least an operational understanding of their structure and function.
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Farewell, Marvin Minsky
Stephen Wolfram describes his friendship and shared interest in computation with the late Marvin Minsky, pioneer of computation and AI.
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Gorgonia: a library like Theano or TensorFlow, mainly written in Go
I released Gorgonia on Thursday. Gorgonia is a library like Theano or TensorFlow, but mainly written in Go. It provides the necessary primitives for creating and executing neural networks and machine learning algorithms. According to cloc, these are the stats…
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Python, Machine Learning, and Language Wars (2015)
This has really been quite a journey for me lately. And regarding the frequently asked question “Why did you choose Python for Machine Learning?” I guess it…
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AI, Apple and Google
As machine learning starts working, how does that change Google, Apple and the smartphone interface? What companies get reshaped around machine learning?
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K-Nearest Neighbors from Scratch
Using JavaScript, we implement the k-Nearest Neighbors algorithm from the bottom up.
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A Simple Explanation of How Image Recognition Works
Update: This article is part of a series. Check out the full series: Part 1, Part 2, Part 3, Part 4, Part 5, Part 6, Part 7 and Part 8! You…
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On Google's self-driving car acident rates
Hot on the heels of my [CES Report](http://ideas.4brad.com/ces-2016-robocar-news) is the release of the latest article from Chris Urmson on [The View from the Front Seat of the Google Car](https://medium.com/@chris_urmson/the-view-from-the-front-seat-of-the-google-self-driving-car-chapter-4-d707b9e925d3#.6okyykxyq)…
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Where will the next major advance towards general purpose AI come from?
Artificial Intelligence (AI) is making progress in great strides, or at least it appears so! Almost no week passes by without some major announcements of new challenges solved by AI technology or new products powered by AI. Indeed many quantifiable factors attest an unprecedented level of activity: capital…
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The Three Cultures of Machine Learning
Everyone should read Leo Breiman's 2001 article, Statistical Modeling: The Two Cultures . (Summary: Traditional statisticians start with a distribution. They try to identify the parameters of the distribution from data that were actually generated from it. Applied statisticians start with data. They have no idea where…
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Tool AIs want to be agent AIs
AIs limited to pure computation (Tool AIs) supporting humans, will be less intelligent, efficient, and economically valuable than more autonomous reinforcement-learning AIs (Agent AIs) who act on their own and meta-learn, because all problems are reinforcement-learning problems.