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The most popular blog posts about ai & machine learning on Hacker News. 104 posts.
How does the brain work? While neuroscience provides insights on small-scale processes and overall behavior, we don’t know much for sure about the learning and processing algorithms in between. In this blog post, I will give an introduction to what we know. Let’s take an engineering perspective and play evolution: How…
Right from my undergrad days when I was starting out with machine learning to this date, my admiration for Kaggle continues to grow. In addition to being synonymous with and popularizing data scien…
Photo by Kevin Steinhardt When Azeem asked me to give a talk at CogX, he asked me to focus on just a single point that I wanted the audience to take away. A few years ago my priority would have bee…
Understanding an effective way of sampling from complex distributions with 3d-demonstrations
With the problem of Image Classification is more or less solved by Deep learning, Text Classification is the next new developing theme in deep learning. For those who don’t know, Text classification is a common task in natural language processing, which transforms a sequence of text of indefinite length into a…
One day in the mid-1920s, a Moscow newspaper reporter named Solomon Shereshevsky entered the laboratory of the psychologist Alexander Luria. Shereshevsky's boss at the newspaper had noticed that Shereshevsky never needed to take any notes, but somehow still remembered all he was told, and had suggested he get his…
It was clear when Ouster started developing the OS-1 three years ago that deep learning research for cameras was outpacing lidar research…
Update 28 Feb 2019: I added a new blog post with a slide deck containing the presentation I did for PyData Montreal. Introduction Short intro to Python extension objects in C/C++ Zero-copy PyTorch Tensor to Numpy and vice-versa Tensor Storage Shared Memory DLPack: a hope for the Deep Learning frameworks Babel…
Update: An updated version of this blogpost was published as a (peer-reviewed) Letter to the Editor at Bioinformatics, sans the “sociology” commentary. I just came back from CASP13, the…
Since writing this post back in 2018, I have extended this to a 4-part series on causal inference: * ➡️️ Part 1: Intro to causal inference and do-calculus [https://www.inference.vc/untitled] * Part 2: Illustrating Interventions with a Toy Example…
Deep code search Gu et al., ICSE’18 The problem with searching for code is that the query, e.g. “read an object from xml,” doesn’t look very much like the source code snippets tha…
A common analogy for explaining gradient descent goes like the following: a person is stuck in the mountains during heavy fog, and must navigate their way down. The natural way they will approac......
Today, fast number crunching means parallel programs that run on Graphical Processing Units (GPUs). Thanks to the recent highly publicized deep learning and ...
the first thing i thought when we setup our bee hive was "i wonder how you could count the number of bees coming and going?"
Python Programming tutorials from beginner to advanced on a massive variety of topics. All video and text tutorials are free.
Machine learning algorithms are not like other computer programs. In the usual sort of programming, a human programmer tells the computer exactly what to do. In machine learning, the human programmer merely gives the algorithm the problem to be solved, and through trial-and-error the algorithm has to figure out how to…
Here, I provide an in-depth analysis of GPUs for deep learning/machine learning and explain what is the best GPU for your use-case and budget.
CUDA 10 support has just landed in ClojureCUDA with the latest version 0.6.0.
Debugging with intelligence via probabilistic inference Xu et al., ICSE’18 Xu et al. have built a automated debugger that can take a single failing test execution, and with minimal interactio…
Earlier this month, I had the exciting opportunity to moderate a discussion between Professors Yann LeCun and Christopher Manning, ti...
Musings on navigating the tech bubble with philosophy and self-improvement.
In my previous blog post, I explored some of the early ways of word embeddings and their shortcomings. The purpose of this post is to explo...
(This was originally a sponsor talk given at PyCon 2018. Unfortunately there is no video.)
