官术网_书友最值得收藏!

Back to deep learning

Many of the concepts in the previous section apply to deep learning because deep learning is simply neural networks with two or more hidden layers. To demonstrate this, let's look at the following code in R that loads the mxnet deep learning library and calls the help command on the function in that library that trains a deep learning model. Even though we have not trained any models using this library yet, we have already seen many of the parameters in this function:

library(mxnet)
?mx.model.FeedForward.create
If you get errors saying the mxnet package is unavailable, see Chapter 1Getting Started with Deep Learning, for installation instructions. However, we are not running any mxnet code in this chapter, we only want to display the help page for a function. So feel free to just  continue reading and you can install the package later when we use it in the next chapter.

This brings up the help page for the FeedForward function in the mxnet library, which is the forward-propagation/model train function. mxnet and most deep learning libraries do not have a specific backward-propagation function, they handle this implicitly:

mx.model.FeedForward.create(symbol, X, y = NULL, ctx = NULL,
begin.round = 1, num.round = 10, optimizer = "sgd",
initializer = mx.init.uniform(0.01), eval.data = NULL,
eval.metric = NULL, epoch.end.callback = NULL,
batch.end.callback = NULL, array.batch.size = 128
...)

We will see more of this function in subsequent chapters; for now we will just look at the parameters.

主站蜘蛛池模板: 洛阳市| 上饶市| 遂宁市| 张家口市| 旅游| 日土县| 宝兴县| 莱芜市| 海淀区| 湘乡市| 牙克石市| 安福县| 贺兰县| 夹江县| 景宁| 泸溪县| 平顺县| 洛宁县| 哈巴河县| 寿光市| 遂溪县| 乳山市| 原阳县| 玛纳斯县| 揭阳市| 墨江| 手机| 桂平市| 普安县| 大竹县| 大丰市| 化德县| 页游| 大新县| 淄博市| 东辽县| 志丹县| 四会市| 张家口市| 南岸区| 鄄城县|