Google open-sources SyntaxNet, a natural-language understanding library for TensorFlow

Google open-sources SyntaxNet, a natural-language understanding library for TensorFlow

  • Above: An example of a sentence being parsed by SyntaxNet’s Parsey McParseface from Google.
  • Founded in 1998 by Stanford Ph.D. students Larry Page and Sergey Brin, Google …
  • Research happens throughout Google, exploring techn…

Read the full article, click here.


@VentureBeat: “Google open-sources SyntaxNet, a natural-language understanding library for TensorFlow”


Google today is open-sourcing SyntaxNet, a piece of natural-language understanding (NLU) software that you can use to automatically parse sentences, as part of its TensorFlow open source machine learning library. The release includes code for training new models, as well as a pre-trained model for parsing English-language text.


Google open-sources SyntaxNet, a natural-language understanding library for TensorFlow | VentureBeat | Big Data | by Jordan Novet

Artificial Intelligence – Radio 1 ‘Timeline Album Showcase’ by artificial intelligence

  • 2015/10/30 21:42:43 +0000 Buy Artificial Intelligence – Radio 1 ‘Timeline Album Showcase’
  • http://www.bbc.co.uk/programmes/b06jt2rw Radio 1 – Timeline Showcase (Taster of what to expect) Artificial Intelligence – Fallen feat.
  • Dawn Wall – Metalheadz Artificial Intelligence – Justify feat.

Read the full article, click here.


@dubblasta: “A new favorite: Artificial Intelligence – Radio 1 ‘Timeline Album Showcase’ by @glennai on #SoundCloud”


Stream Artificial Intelligence – Radio 1 ‘Timeline Album Showcase’ by artificial intelligence from desktop or your mobile device


Artificial Intelligence – Radio 1 ‘Timeline Album Showcase’ by artificial intelligence | Free Listening on SoundCloud

Top 10 Machine Learning Algorithms – Data Science Central

Top 10 Machine Learning Algorithms

  • You need to be a member of Data Science Central to add comments!
  • In 2006 , the IEEE Conference on Data Mining identified the top 10 ML algorithms as
  • The algorithms are described in the article What you wont learn in statistics classes .

Read the full article, click here.


@analyticbridge: “Top 10 Machine Learning Algorithms”


This was the subject of a question asked on Quora: What are the top 10 data mining or machine learning algorithms?
Some modern algorithms such as collaborative…


Top 10 Machine Learning Algorithms – Data Science Central

Deep Learning from 30,000 feet

#DeepLearning from 30,000 feet  #MachineLearning #DataScience

  • If you fly in April on Delta, be sure to check Delta Sky Magazine for an article on Deep Learning!
  • It was partly inspired by the way the brain works – some of the Deep Learning pioneers like Geoff Hinton have studied and sought to emulate brain processes.
  • Just like the airplane flight was inspired by birds, but flies very differently, so Deep Learning works quite differently from the brain.

Read the full article, click here.


@MikeTamir: “#DeepLearning from 30,000 feet #MachineLearning #DataScience”


My very-high level overview of Deep Learning for Delta Sky Magazine, including neurons, a conspiracy, games, amazing feats of superhuman ability, and more – appropriate for reading at 30,000 feet.


Deep Learning from 30,000 feet

The Good, Bad, & Ugly of TensorFlow

  • If you are deploying a model to a cloud environment, you want to know that your model can execute on the hardware available to it, without unpredictable interactions with other code that may access the same hardware.
  • For me, holding mental context for a new framework and model I’m building to solve a hard problem is already pretty taxing, so it can be really helpful to inspect a totally different representation of a model; the TensorBoard graph visualization is great for this.
  • For example, the Udacity tutorials and the RNN tutorial using Penn TreeBank data to build a language model are very illustrative, thanks to their simplicity.

Read the full article, click here.


@rasbt: “The Good, Bad, & Ugly of TensorFlow – survey of 6 months rapid evolution (+ tips/hacks & code to fix the ugly stuff)”


//php wp_head(); ?>

!function(){var analytics=window.analytics=window.analytics||[];if(!analytics.initialize)if(analytics.invoked)window.console&&console.error&&console.error(“Segment snippet included twice.”);else{analytics.invoked=!0;analytics.methods=[“trackSubmit”,”trackClick”,”trackLink”,”trackForm”,”pageview”,”identify”,”group”,”track”,”ready”,”alias”,”page”,”once”,”off”,”on”];analytics.factory=function(t){return function(){var e=Array.prototype.slice.call(arguments);e.unshift(t);analytics.push(e);return analytics}};for(var t=0;t li > a.nav-link {
-webkit-transition: all 200ms ease-out;
-moz-transition: all 200ms ease-out;
-o-transition: all 200ms ease-out;
transition: all 200ms ease-out;
font-size: 1em;
margin: 15px 8px;
padding: 0px;
width: 106px;
border: 1px solid white;
border-radius: 3px;
display: inline-block;
color: #A655CB;
border-color: #A655CB;
}

.nav.navbar-nav.navbar-right > li > a.nav-link:hover {
text-decoration: none;
color: #C39EF0;
border-color: #C39EF0;
}

.nav.navbar-nav > li > a.nav-link.active {
color: white;
}

.nav.navbar-nav > li > a.nav-link.active::after {
content: “”;
height: 2px;
background: white;
display: block;
}

#content {
background: white;
}


The Good, Bad, & Ugly of TensorFlow

Applied Artificial Intelligence Conference Tickets, Wed, May 25, 2016 at 8:00 AM

Applied AI Conference by @bootstraplabs - Use AAI20 for 20% off here:

  • Please enter a quantity of 1 or more next to the type or types of tickets you would like to purchase.
  • Sorry, you entered an invalid quantity.
  • Sorry, there are no tickets left for this event.

Read the full article, click here.


@nicolaiwadstrom: “Applied AI Conference by @bootstraplabs – Use AAI20 for 20% off here:”


Eventbrite – hackers.ai presents Applied Artificial Intelligence Conference – Wednesday, May 25, 2016 at Galvanize San Francisco, San Francisco, CA. Find event and ticket information.


Applied Artificial Intelligence Conference Tickets, Wed, May 25, 2016 at 8:00 AM | Eventbrite

Deep Learning: Definition, Resources, Comparison with Machine Learning – Data Science Central

  • Many deep learning practitioners call themselves data scientist, computer scientist, statistician, or sometimes engineer.
  • Deep learning is sometimes referred to as the intersection between machine learning and artificial intelligence.
  • In my opinion, deep learning also tries to automate some data science processes.

Read the full article, click here.


@KirkDBorne: “#DeepLearning: Definition, Resources, and Comparison with #MachineLearning #abdsc #BigData #DataScience”


Deep learning is sometimes referred to as the intersection between machine learning and artificial intelligence. It is about designing algorithms that can make…


Deep Learning: Definition, Resources, Comparison with Machine Learning – Data Science Central