最新消息:网盘下载利器JDownloader--|--发布资讯--|--解压出错.密码问题

Building Classification Models with TensorFlow

其他教程 killking 0评论
Building Classification Models with TensorFlow
Building Classification Models with TensorFlow
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 3 Hours 16M | 351 MB
Genre: eLearning | Language: English

This course will teach you the finer points of building such models as well the logistic regression, nearest-neighbor methods, and metrics for evaluating classifiers such as accuracy, precision, and recall.

TensorFlow is a great way to implement powerful classification models such as Convolutional Neural Networks and Recurrent Neural Networks. In this coures, Building Classification Models with TensorFlow, you'll learn the finer points of building models with TensorFlow. First, you'll explore the logistic regression in TensorFlow. Next, you'll discover nearest-neighbor methods. Finally, you'll learn the metrics for evaluating classifiers such as accuracy, precision, and recall. Recurrent Neural Networks (RNNs) are a versatile and powerful form of NN that is fast gaining popularity in applications that need to consider context. RNNs are ideal for considering sequences of data - frames in a movie, sentences in a paragraph, or stock returns in a period. Convolutional Neural Networks (CNNs) are a class of deep, feed-forward artificial neural network that has successfully been applied to analyzing visual imagery. CNNs are widely used in image and video recognition. By the end of this course, you'll have a better understanding on how to build classification models with TensorFlow.

Building Classification Models with TensorFlow

Download rapidgator
https://rg.to/file/840c29a6e902bf7407912bc7149fa671/Building_Classification_Models_with_TensorFlow.part1.rar.html
https://rg.to/file/63f5c90b253d4411efa78808a61267bd/Building_Classification_Models_with_TensorFlow.part2.rar.html
https://rg.to/file/f78624c4e1c667342a08df0d73bc70bb/Building_Classification_Models_with_TensorFlow.part3.rar.html
https://rg.to/file/e64dd5951ec5ac18a9a2a51c34a2c56a/Building_Classification_Models_with_TensorFlow.part4.rar.html

Download nitroflare
http://nitroflare.com/view/D2C38B5E3906A22/Building_Classification_Models_with_TensorFlow.part1.rar
http://nitroflare.com/view/E9394536B30912F/Building_Classification_Models_with_TensorFlow.part2.rar
http://nitroflare.com/view/12E1E86FB07AD60/Building_Classification_Models_with_TensorFlow.part3.rar
http://nitroflare.com/view/A054DE731232A69/Building_Classification_Models_with_TensorFlow.part4.rar

Download 百度云
链接: https://pan.baidu.com/s/1c19nJpe 密码: d8u2

您必须 登录 才能发表评论!

网友最新评论 (1)

  1. TensorFlow开发分类模型 本教程将会为你将带来开发如逻辑递归、临近算法以及用于评估如准确度、精度的分类的最佳实践。 Tensorflow是实现强大的分类模型,如卷积神经网络和循环神经网络的绝好方法。在本教程中,你将学习使用Tensorflow的最佳实践。首先,你将学习Tensorflow中的逻辑递归;接下来,你将学习近邻方法;最后,你将学习评估分类精度和准确度的量化指标。RNN是神经网络多样并且强大的形式,在应用方面它得到了快速的流行度。RNN是考虑数据序列时的理想选择,如电影中的帧、段落中的句子或一段时期内股票的回落。CNN是深度、feed-forward神经网络的一个类别,其成功地被用于分析可视化图像。CNN被广泛地英语图像和视频识别。在本教程的最后,你将更好地理解如何使用Tensorflow开发分类模型。
    wilde(特殊组-翻译)4周前 (10-26)