Case Study: TensorFlow in Medicine - Retinal Imaging (TensorFlow Dev Summit 2017)
Diabetic retinopathy is the fastest growing cause of blindness. Learn from Lily Peng how TensorFlow was trained to analyze retinal fundus images to diagnose this condition. She describes the project steps: from acquiring a dataset, training a deep network, and evaluating of the results.
Feb 15,2017
What are Future Jobs and Work in Era of Artificial Intelligence(AI)?
From Accenture and Skinome
May 19,2017
AI Learns to Synthesize Pictures of Animals | Two Minute Papers
Károly Zsolnai-Fehér has another marvelous production.

The Rise of Artificial Intelligence through Deep Learning | Yoshua Bengio | TEDxMontreal
A revolution in AI is occurring thanks to progress in deep learning. How far are we towards the goal of achieving human-level AI? What are some of the main challenges ahead?
May 17,2017
TensorFlow Tutorial #03-B Layers API
Magnus Erik Hvass Pedersen Has produced a new video.
How to use the Layers API to simplify the implementation of a Convolutional Neural Network in TensorFlow. This is used for recognizing handwritten digits from the MNIST data-set.

GTC 2017: Nvidia gpu technology conference Tesla V100 Volta
This is a recording of the GTC 2017 livestream.
May 10,2017
(From TED 2013) Andrew McAfee What will future jobs look like?
Note: Although this is from 2013, the talk is even more applicable now in 2017. Economist Andrew McAfee suggests that, yes, probably, droids will take our jobs -- or at least the kinds of jobs we know now. In this far-seeing talk, he thinks through what future jobs might look like, and how to educate coming generations to hold them.

Differentiable Neural Computer Siraj Raval Live May 10 2017
The Differentiable Neural Computer is an awesome model that DeepMind recently released. It's a memory augmented network that can perform meta-learning (learning to learn). We'll go over it's architecture details and implement it ourselves in Tensorflow.
May 10,2017
How to Learn from Little Data - Intro to Deep Learning #17v
Siraj Raval has a new video. One-shot learning! In this last weekly video of the course, i'll explain how memory augmented neural networks can help achieve one-shot classification for a small labeled image dataset. We'll also go over the architecture of it's inspiration (the neural turing machine).
May5,2017
TensorFlow Tutorial #16 Reinforcement Learning
Magnus Erik Hvass Pedersen has a new video.

How to implement Reinforcement Learning in TensorFlow. This is a version of Q-Learning that is somewhat different from the original DQN implementation by Google DeepMind. Demonstrated on the Atari game Breakout. April 24,2017
The incredible inventions of intuitive AI | Maurice Conti
The title isn't overstated. This video is seminal.
April 21,2017
From Cold Fusion TV - A.I. is Progressing Faster Than You Think!
Cold Fusion TV has a new video which follows-up on a piece done in 2016.
April 21,2017
How to Generate Video - Intro to Deep Learning #15
Siraj Raval Hit another home run with this video on GANs.

Generative Adversarial Networks. It's time. We're going to use a Deep Convolutional GAN to generate images of the alien language from the movie arrival that we can then stitch together to animate into video. I'll go over the architecture of a GAN and then we'll implement one ourselves! April 20,2017
Algorithmic bias,Joy Buolamwini
Algorithmic bias like human bias can result in exclusionary experiences and discriminatory practices. Find out how below.
April 16,2017
How to Generate Images - Intro to Deep Learning #14
Siraj's latest video is his words: We're going to build a variational autoencoder capable of generating novel images after being trained on a collection of images.
April 14,2017
TensorFlow Dev Summit 2017
The 2017 TesnorFlow Summit was held in February. The Summit's 18 talks are archived and available on YouTube.
April,16,2017
Shape2vec: Understanding 3D Shapes With AI
New Two Minute Papers: Shape2vec: Understanding 3D Shapes With AI
March 23,2017
Stable Neural Style Transfer | Two Minute Papers
March 16,2017
Breaking DeepMind's Game AI System | Two Minute Papers
March 16,2017
Feb 19 2017   A new vide titled AI Builds 3D Models From Images With a Twist has been posted by Two Minute Papers aka Károly Zsolnai-Fehér'

Feb 17,2017    Siraj @sirajraval has also published a video titled How to Make an Image Classifier - Intro to Deep Learning #6

A new Two Minute Papers is available titled Fast Photorealistic Fur and Hair. Károly Zsolnai-Fehér'== excellent NN content

Siraj @sirajraval has a new video (in a seris of over 50) titled Deep Learning math concepts . Siraj == ultra energy


We want to mention four sources that will be mentioned often.


First is Károly Zsolnai-Fehér who has some absolutely excellent videos. What follows is a great starting point.

9 Cool Deep Learning Applications | Two Minute Papers is another one of 130 videos most of which touch on Neural Networks. Here is a full list of Two Minute Videos. we've sent my robot out and have downloaded all 130 video and the SRT transcript files. One of our goals is to cross index all of the good Neural Net content.


Siraj Raval is another source of Neural Network video series. 'High energy' is an understatement. He presents topics with examples which have open source code available for study and experimentation. Big pluses when you want to elevate your understanding.


Hvass Laboratories on YouTube and http://www.hvass-labs.org/ is another series we've found to be an excellent source for study and experimentation. He describes and provides open source examples.


Next in the roster of good Neural Network video series Deep Learning TV by Jagannath Rajagopal.


Neural Net Weekly is on the air. For just over one month, we have been spending evenings looking with amazement at what is happening. The potential for impact, disruption and consequence outstrips the web's beginning. So when we found that the domain name was available, we wanted to try document our learning travels. Neural Net Weekly will attempt to capture the week in neural networks. We will announce the best curated content for learning and experimenting with artificial networks. Keeping up with just this segment of neural networks will be a big task. We will use collective curation to achieve these goals. The video Understand collective curation in under 90 seconds helps to describe the modus operandi.

Monday, 29-May-2017 17:00:04 UTC