Intro – Training a neural network to play a game with TensorFlow and Open AI

This tutorial mini series is focused on training a neural network to play the Open AI environment called CartPole.

 
The idea of CartPole is that there is a pole standing up on top of a cart. The goal is to balance this pole by wiggling/moving the cart from side to side to keep the pole balanced upright.

Sample code: https://pythonprogramming.net/openai-…
https://twitter.com/sentdex
https://www.facebook.com/pythonprogra…
https://plus.google.com/+sentdex

Facebooktwittergoogle_plusredditpinterestlinkedintumblrmail

How to Prevent an AI Apocalypse

I traveled to Amsterdam for a week to speak at The Next Web Conference on AI Safety. While roaming the streets of the city, I decided to take some shots and formulate a video on the same topic for you guys. In the battle of good vs evil, it’s up to our community to ensure good wins. I’ll resume the coding videos next week when I get back to San Francisco.


Please Subscribe! And like. And comment. That’s what keeps me going.

I’ll post a link to the talk once it’s up, here’s an article in the mean time:
https://thenextweb.com/artificial-int…

More Learning resources:
https://futureoflife.org/ai-safety-re…
https://iamtrask.github.io/2017/03/17…
https://blog.openai.com/concrete-ai-s…
https://intelligence.org/why-ai-safety/
https://80000hours.org/career-reviews…
https://foundational-research.org/fil…

Join us in the Wizards Slack channel:
http://wizards.herokuapp.com/

And please support me on Patreon: https://www.patreon.com/user?u=3191693

 

Facebooktwittergoogle_plusredditpinterestlinkedintumblrmail

How to Make an Evolutionary Tetris AI

Let’s use an evolutionary algorithm to improve a Tetris AI! We’ll be coding this in Javascript (gasp) because I want to try something different. Through the process of selection, crossover, and mutation our AI will eventually be able to reach the high score of 500 in record time.


Code for this video:
https://github.com/llSourcell/How_to_…

Please Subscribe! And like. And comment. That’s what keeps me going.

More Learning resources:
https://www.youtube.com/watch?v=L–Ix…
https://luckytoilet.wordpress.com/201…
https://codemyroad.wordpress.com/2013…
http://www.cs.uml.edu/ecg/uploads/AIf…
http://cs229.stanford.edu/proj2015/23…

Join us in the Wizards Slack channel:
http://wizards.herokuapp.com/

And please support me on Patreon:
https://www.patreon.com/user?u=3191693

Facebooktwittergoogle_plusredditpinterestlinkedintumblrmail

How to Generate Images – Intro to Deep Learning

We’re going to build a variational autoencoder capable of generating novel images after being trained on a collection of images. We’ll be using handwritten digit images as training data. Then we’ll both generate new digits and plot out the learned embeddings. And I introduce Bayesian theory for the first time in this series 🙂


Code for this video:
https://github.com/llSourcell/how_to_…

Mike’s Winning Code:
https://github.com/xkortex/how_to_win…

SG’s Runner up Code:
https://github.com/esha-sg/Intro-Deep…

Please subscribe! And like. And comment. That’s what keeps me going.

2 things
-The embedding visualization at the end would be more spread out if i trained it for more epochs (50 is recommended) but i just used 5.
-The code in the video doesn’t fully implement the reparameterization trick (to save space) but check the GitHub repo for details on that.

More Learning resources:
https://jaan.io/what-is-variational-a…
http://kvfrans.com/variational-autoen…
http://blog.fastforwardlabs.com/2016/…
http://blog.fastforwardlabs.com/2016/…
http://blog.evjang.com/2016/11/tutori…
https://jmetzen.github.io/2015-11-27/…

Join us in the Wizards Slack channel:
http://wizards.herokuapp.com/

And please support me on Patreon:
https://www.patreon.com/user?u=3191693

Facebooktwittergoogle_plusredditpinterestlinkedintumblrmail

How to Make a Language Translator – Intro to Deep Learning

Let’s build our own language translator using Tensorflow! We’ll go over several translation methods and talk about how Google Translate is able to achieve state of the art performance.

Code for this video:
https://github.com/llSourcell/How_to_…

Ryan’s Winning Code:
https://github.com/rtlee9/recipe-summ…

Sarah’s Runner-up Code:
https://github.com/scollins83/teal_deer

More Learning Resources:
https://medium.com/@ageitgey/machine-…
https://www.tensorflow.org/tutorials/…
https://devblogs.nvidia.com/parallelf…
https://www.youtube.com/watch?v=vxibD…
http://neural-monkey.readthedocs.io/e…
http://blog.systransoft.com/how-does-…
http://www.wildml.com/2016/01/attenti…
https://blog.altoros.com/enabling-mul…
https://www.quora.com/How-can-I-build…
https://blog.heuritech.com/2016/01/20…
https://smerity.com/articles/2016/goo…

Please Subscribe! And like. And comment. That’s what keeps me going.

Join us in the Wizards Slack channel:
http://wizards.herokuapp.com/

And please support me on Patreon:
https://www.patreon.com/user?u=3191693

Facebooktwittergoogle_plusredditpinterestlinkedintumblrmail

Why Is Deep Learning Hot Right Now?

Deep learning is the fastest-growing field in artificial intelligence (AI), helping computers make sense of infinite amounts of data in the form of images, sound, and text. Using multiple levels of neural networks, computers now have the capacity to see, learn, and react to complex situations as well or better than humans. Today’s deep learning solutions rely almost exclusively on NVIDIA GPU-accelerated computing to train and speed up challenging applications such as image, handwriting, and voice identification.

Learn more at http://www.nvidia.com/object/deep-lea…

Facebooktwittergoogle_plusredditpinterestlinkedintumblrmail