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Visualization techniques for different data sets
Visualizations are awesome.
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Building a State of the Art Bacterial Classifier with Fast.ai and Paperspace
In this post, we’re going to be demonstrating how to to build a state of the art Bacterial Classification model on Gradient using the Fast.ai machine learning library.
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Kyoto Tycoon in 2019
I've been interested in using Kyoto Tycoon for some time. Kyoto Tycoon, successor to Tokyo Tyrant , is a key/value database with a number of desirable features:
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Lesson Learned from Queries over 1.3T Rows of Data
Explore how our customers use TiDB to handle their mission-critical workloads.
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The difference between isolation levels and consistency levels
(Editor's note: This post is cross-posted on Fauna's blog, where Daniel Abadi serves as an adviser . Fauna is is a serverless, cloud data...
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Trends in the San Francisco (mostly dog?) poop crisis
Oscar Wilde once said, “it’s an odd thing but anyone who disappears is said to be in San Francisco.” Indeed, with the weather, view, and diversity, San Francisco is one of the most beautiful cities in the U.S. But then, every city has a dark side, and San Francisco is no exception. San Francisco, as […]
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“My Car does not start when I buy Vanilla Ice Cream” (2015)
Did you ever imagine that an “Ice Cream” could shake the entire General Motors? In 2010, the Pontiac Division of General Motors received a very funny complaint from one of its customers. It was so weird & bizarre that it took the entire General Motors by storm. However, on reading the entire Case, this definitely
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Announcing Yugabyte DB 2.0 GA: High-Performance Distributed SQL
YugabyteDB 2.0 released. Read to learn about production-ready YSQL, performance benchmarks, Jepsen results, and Beta feature previews
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Jepsen: YugaByte DB 1.3.1
2019-09-05: YugaByte’s blog post states YugaByte DB “passes Jepsen tests”. We feel obligated to state that YugaByte DB’s Jepsen test suite does not pass, though it may in the future. Race conditions in YugaByte DB’s schema system can cause correctness errors. For example, inserting rows into a freshly-created table…
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Object-recognition dataset stumped the world’s best computer vision models
When computer vision detectors are turned loose in the real world, their performance noticeably drops. In an effort to close this performance gap, a team of MIT and IBM researchers set out to create a very different kind of object-recognition dataset called ObjectNet.
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Dynamo vs. Cassandra: Systems Design of NoSQL Databases (2018)
A comparison of ideas behind Dynamo and Cassandra
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Mergeable replicated data types – Part I
Mergeable replicated data types Kaki et al., OOPSLA’19 This paper was published at OOPSLA, but perhaps it’s amongst the distributed systems community that I expect there to be the greatest in…
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Optimizing Magic Pocket for cold storage
Dash knows your context, your team, and your work, so your team can stay organized, easily find and share knowledge, and keep projects secure, all from one place.
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Layers in Software: From Data to Value
Then Back in the 2000s, we wrote applications in layers. Presentation layer, client, data transfer, API, business logic, data access, database. We maintained strict separation bet ween these layers…
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Stock Option Pricing Inference
I’m a stock market enthusiast 📈, so lately I have spent my spare time on the topic of stock option pricing, and I was curious to find out whether or not I could build a script that accurately reflected real market option prices. It turns out I came close, and learned a lot along the way, which I share in this article.
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Math versus Dirty Data
At Google, our organization designs, owns, and maintains a number of optimization models that automate the planning of Google’s datacenter growth and health. As is pretty standard in supply chain optimization and planning, these models are often integer linear programs. It’s a core competency of operations research…
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Nonnegative matrix factorization
The why and how of nonnegative matrix factorization Gillis, arXiv 2014 from: ‘Regularization, Optimization, Kernels, and Support Vector Machines.’ Last week we looked at the paper ‘Beyond news cont…
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Ebtrees: Elastic Binary Trees (2011)
Administrivia This article was initially posted on Wikipedia in 2008, which explains why it's written at the 3rd person and looks familiar...
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ZFS on Linux still has annoying issues with ARC size
You're probably reading this page because you've attempted to access some part of my blog (Wandering Thoughts) or CSpace , the wiki thing it's part of. Unfortunately you're using a browser version that my anti-crawler precautions consider suspicious, most often because it's too old (most often this applies to versions…
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Cracking open the black box of automated machine learning
ATMSeer is an interactive visualization tool for users to see and control algorithms and hyperparameters of machine-learning (AutoML) systems. The work was developed by researchers in the MIT Laboratory for Information and Decision Systems (LIDS), Hong Kong University of Science and Technology (HKUST), and Zhejiang…
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Building a CRUD App with Datomic Cloud Ions
Software engineer, etc etc
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Amundsen – Lyft’s data discovery and metadata engine
In order to increase productivity of data scientists and research scientists at Lyft, we developed a data discovery application built on…
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Using machine learning to estimate lost demand in a fulfillment chain
How Instacart uses Machine Learning to spot lost demand in its fulfillment chain