Public Transport Tracking

Basecamp - ESP32 library to simplify the basics of IoT projects Written by Merlin Schumacher (mls@ct.de) for c't magazin für computer technik Licensed under GPLv3. See LICENSE for details.

A gentle introduction to elm

Haven is for people who need a way to protect their personal spaces and possessions without compromising their own privacy. It is an Android application that leverages on-device sensors to provide monitoring and protection of physical spaces. Haven turns any Android phone into a motion, sound, vibration and light detector, watching for unexpected guests and unwanted intruders. We designed Haven for investigative journalists, human rights defenders, and people at risk of forced disappearance to create a new kind of herd immunity. By combining the array of sensors found in any smartphone, with the world’s most secure communications technologies, like Signal and Tor, Haven prevents the worst kind of people from silencing citizens without getting caught in the act.

Curious why Functional Programming is on the Rise?
Do you wish there was a better option than JavaScript?
Would you like to learn Elm or Functional Programming in general, but short on time?

Git is hard: screwing up is easy, and figuring out how to fix your mistakes is fucking impossible. Git documentation has this chicken and egg problem where you can't search for how to get yourself out of a mess, unless you already know the name of the thing you need to know about in order to fix your problem.

So here are some bad situations I've gotten myself into, and how I eventually got myself out of them in plain english*.

Elasticsearch For Beginners: Indexing your Gmail Inbox
What's this all about?

I recently looked at my Gmail inbox and noticed that I have well over 50k emails, taking up about 12GB of space but there is no good way to tell what emails take up space, who sent them to, who emails me, etc

Goal of this tutorial is to load an entire Gmail inbox into Elasticsearch using bulk indexing and then start querying the cluster to get a better picture of what's going on.

Probablistic filters are high-speed, space-efficient data structures that support set-membership tests with a one-sided error. These filters can claim that a given entry is definitely not represented in a set of entries, or might be represented in the set. That is, negative responses are conclusive, whereas positive responses incur a small false positive probability (FPP).

The trade-off for this one-sided error is space-efficiency. Cuckoo Filters and Bloom Filters require approximately 7 bits per entry at 3% FPP, regardless of the size of the entries. This makes them useful for applictations where the volume of original data makes traditional storage impractical.

Bloom filters have been in use since the 1970s and are well understood. Implementations are widely available. Variants exist that support deletion and counting, though with expanded storage requirements.

Cuckoo filters were described in Cuckoo Filter: Practically Better Than Bloom, a paper by researchers at CMU in 2014. Cuckoo filters improve on Bloom filters by supporting deletion, limited counting, and bounded FPP with similar storage efficiency as a standard Bloom filter.

Below is side-by-side simulation of the inner workings of Cuckoo and Bloom filters.

Turi Create simplifies the development of custom machine learning models.

Quantum Development Kit

An AngularJS 1.x WebSocket service for connecting client applications to servers.

Project DeepSpeech is an open source Speech-To-Text engine. It uses a model trained by machine learning techniques, based on Baidu's Deep Speech research paper. Project DeepSpeech uses Google's TensorFlow project to make the implementation easier.

Flight rules for git

Natural language processing

container-diff: Diff your Docker containers

The Yocto Project is an open source collaboration project that provides templates, tools and methods to help you create custom Linux-based systems for embedded products regardless of the hardware architecture. It was founded in 2010 as a collaboration among many hardware manufacturers, open-source operating systems vendors, and electronics companies to bring some order to the chaos of embedded Linux development.