官术网_书友最值得收藏!

Deep learning frameworks for R

There are a number of R packages available for neural networks, but few options for deep learning. When the first edition of this book came out, it used the deep learning functions in h2o (https://www.h2o.ai/). This is an excellent, general machine learning framework written in Java, and has an API that allows you to use it from R. I recommend you look at it, especially for large datasets. However, most deep learning practitioners had a preference preferred other deep learning libraries, such as TensorFlow, CNTK, and MXNet, which were not supported in R when the first edition of this book was written. Today, there is a good choice of deep learning libraries that are supported in R—MXNet and Keras. Keras is actually a frontend abstraction for other deep learning libraries, and can use TensorFlow in the background. We will use MXNet, Keras, and TensorFlow in this book.

主站蜘蛛池模板: 南江县| 洪洞县| 香格里拉县| 大悟县| 青州市| 乌兰察布市| 康乐县| 梅州市| 郎溪县| 观塘区| 长宁县| 云和县| 宜良县| 天柱县| 涟水县| 新泰市| 云南省| 星座| 靖江市| 越西县| 墨脱县| 新营市| 额济纳旗| 河源市| 雷州市| 隆安县| 堆龙德庆县| 澳门| 天峨县| 蓝山县| 仪陇县| 日照市| 余姚市| 乌拉特中旗| 西华县| 彭泽县| 射阳县| 嵩明县| 三门县| 仁怀市| 黄浦区|