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@nicholasknight
nicholasknight / adv2notes.md
Last active January 2, 2024 02:39
Kinesis Advantage 2 notes

(NOTE: Current and future versions of this and any other Advantage 2-related things I post will be at https://github.com/nicholasknight/adv2keyboard)

I received my Advantage 2 today. There's no full manual yet, even though keyboards are apparently arriving (hint, hint, Kinesis). The quick start guide leaves out the "power user mode", and there are some other quirks.

Update: A manual has been posted at http://www.kinesis-ergo.com/advantage2-resources/

It includes a dictionary for the key maps, but I know it leaves at least one possible key undocumented: it does not list f14, but I have successfully mapped my scrollock to f14 regardless.

It also mentions a firmware version (1.0.18) that doesn't seem to be available yet, with a new feature (status report playback speed).

Build tensorflow on OSX with NVIDIA CUDA support (GPU acceleration)

These instructions are based on Mistobaan's gist but expanded and updated to work with the latest tensorflow OSX CUDA PR.

Requirements

OS X 10.10 (Yosemite) or newer

@Mistobaan
Mistobaan / tensorflow_cuda_osx.md
Last active July 25, 2023 18:54
How to enable cuda support for tensor flow on Mac OS X (Updated on April:2016 Tensorflow 0.8)

These instructions will explain how to install tensorflow on mac with cuda enabled GPU suport. I assume you know what tensorflow is and why you would want to have a deep learning framework running on your computer.

Prerequisites

Make sure to update your homebrew formulas

brew update
@debasishg
debasishg / gist:8172796
Last active March 15, 2024 15:05
A collection of links for streaming algorithms and data structures

General Background and Overview

  1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  2. Models and Issues in Data Stream Systems
  3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t