Brendan Bennett rldotai

Using IBM Watson Speech to Text API to translate a ProPublica podcast

An example of using the Watson Speech to Text API to translate a podcast from ProPublica: How a Reporter Pierced the Hype Behind Theranos

This is just a simpler demo of the same technique I demonstrate to make automated video supercuts in this repo: https://github.com/dannguyen/watson-word-watcher

The transcription takes just a few minutes (less if you parallelize the requests to IBM) and is free...but it isn't perfect by any means. It doesn't fare super well on proper nouns:

Charles Ornstein's last name is transcribed as Orenstein
John Carreyrou's last name becomes John Kerry Roo

Strictly Frameworks

Mobiledoc - github.com/bustle/mobiledoc-kit - framework to build editors with a standardized JSON structure
ShareDB - github.com/share/sharedb - framework to sync any JSON document using operational transforms, add real-time collaborative editing to anything else
Bangle.dev - github.com/bangle-io/bangle.dev - toolkit built for building editors, based on prosemirror

Abstracted Editors

These use separate document structures instead of HTML, some are more modular libraries than full editors

A comparison of Theano with other deep learning frameworks, highlighting a series of low-level design choices in no particular order.

Overview

Differentiation

Differentiation

Symbolic: Theano, CGT; Automatic: Torch, MXNet

Symbolic and automatic differentiation are often confused or used interchangeably, although their implementations are significantly different.

General Background and Overview

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.
Models and Issues in Data Stream Systems
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
Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
[Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

Hofstadter on Lisp

In the mid-80s, while reading through my roommate's collection of Scientific American back issues, I encountered this introduction to Lisp written by Douglas Hofstadter. I found it very charming at the time, and provide it here (somewhat illegally) for the edification of a new generation of Lispers.

In a testament to the timelessness of Lisp, you can still run all the examples below in emacs if you install these aliases:

(defalias 'plus #'+)
(defalias 'quotient #'/)
(defalias 'times #'*)
(defalias 'difference #'-)

	# depends on Calibre (http://calibre-ebook.com)
	# the CSS snippet prevents images from filling the page
	# adapt margins, page size and font size as needed
	ebook-convert doc.epub doc.pdf \
	--smarten-punctuation \
	--pretty-print \
	--preserve-cover-aspect-ratio \
	--insert-blank-line \
	--margin-top 60 \
	--margin-left 60 \

	# -- coding: utf-8 --
	"""
	An example flask application showing how to upload a file to S3
	while creating a REST API using Flask-Restful.

	Note: This method of uploading files is fine for smaller file sizes,
	but uploads should be queued using something like celery for
	larger ones.
	"""
	from cStringIO import StringIO

	/! normalize.css v2.1.3 \| MIT License \| git.io/normalize /

	/* ==========================================================================
	HTML5 display definitions
	========================================================================== */

	/**
	* Correct `block` display not defined in IE 8/9.
	*/