loading reading lists ...
');
function adjustReadingListIcon(isInReadingList){
$readingListToggle.toggleClass("fa-plus", !isInReadingList);
$readingListToggle.toggleClass("fa-check", isInReadingList);
var tooltipMessage = isInReadingList ? "edit in reading lists" : "add to reading list";
$readingListToggle.attr("title", tooltipMessage);
$readingListToggle.attr("data-original-title", tooltipMessage);
}
$.ajax({
url: "/readingList/isInReadingList",
data: {
productId: 976
}
}).done(function (data) {
adjustReadingListIcon(data && data.hasProductInReadingList);
}).catch(function(e){
console.log(e);
adjustReadingListIcon(false);
});
$readingListToggle.on("click", function(){
if(codePromise == null){ showToast() }
loadCode().then(function(store){
store.requestReadingListSpecificationForProduct({
id: window.readingListsServerVars.externalId,
manningId: window.readingListsServerVars.productId,
title: window.readingListsServerVars.title
});
ReadingLists.ReactDOM.render(
ReadingLists.React.createElement(ReadingLists.ManningOnlineReadingListModal, {
store: store,
}),
document.getElementById("reading-lists-modal")
);
}).catch(function(e){
console.log("Error loading code reading list code");
});
});
var codePromise
var readingListStore
function loadCode(){
if(codePromise) { return codePromise }
return codePromise = new Promise(function (resolve, reject){
$.getScript(window.readingListsServerVars.libraryLocation).done(function(){
hideToast()
readingListStore = new ReadingLists.ReadingListStore(
new ReadingLists.ReadingListProvider(
new ReadingLists.ReadingListWebProvider(
ReadingLists.SourceApp.marketplace,
getDeploymentType()
)
)
);
readingListStore.onReadingListChange(handleChange);
readingListStore.onReadingListModalChange(handleChange);
resolve(readingListStore);
}).catch(function(){
hideToast();
console.log("Error downloading reading lists source");
$readingListToggle.css("display", "none");
reject();
});
});
}
function handleChange(){
if(readingListStore != null) {
adjustReadingListIcon(readingListStore.isInAtLeastOneReadingList({
id: window.readingListsServerVars.externalId,
manningId: window.readingListsServerVars.productId
}));
}
}
var $readingListToast = $("#reading-list-toast");
function showToast(){
$readingListToast.css("display", "flex");
setTimeout(function(){
$readingListToast.addClass("shown");
}, 16);
}
function hideToast(){
$readingListToast.removeClass("shown");
setTimeout(function(){
$readingListToast.css("display", "none");
}, 150);
}
function getDeploymentType(){
switch(window.readingListsServerVars.deploymentType){
case "development":
case "test":
return ReadingLists.DeploymentType.dev;
case "qa":
return ReadingLists.DeploymentType.qa;
case "production":
return ReadingLists.DeploymentType.prod;
case "docker":
return ReadingLists.DeploymentType.docker;
default:
console.error("Unknown deployment environment, defaulting to production");
return ReadingLists.DeploymentType.prod;
}
}
});
}
});
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Look inside
Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game.
about the technology
The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning–based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot!
about the book
Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you’ll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You’ll enjoy watching your bot master the game of Go, and along the way, you’ll discover how to apply your new deep learning skills to a wide range of other scenarios!
what's inside
- Build and teach a self-improving game AI
- Enhance classical game AI systems with deep learning
- Implement neural networks for deep learning
about the reader
All you need are basic Python skills and high school–level math. No deep learning experience required.
about the authors
Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo.
We interviewed Kevin as a part of our Six Questions series. Check it out here.
Using the game of Go as a way to teach machine learning is inspired and inspiring. Highly recommended!
Brilliant introduction to the most exciting technology of our time.
Great Pythonic code that is a pleasure to read.
Deep Learning and the Game of Go ebook for free
