搜索资源列表
MNIST(tensorflow)
- 基于tensorflow的手写识别，训练后可以识别手写数字-Based on tensorflow handwriting recognition, training can identify handwritten numbers
AlexNet
- 基于AlexNet模型的手写数字识别，用Tensorflow实现，可直接运行，准确率达到98 以上-Model based AlexNet handwritten digit recognition, implemented Tensorflow, can be run directly, the accuracy rate of more than 98
CNN
- 用卷积神经网络实现的手写数字识别（minst）,可直接运行，识别率较高。用Tensorflow实现-Handwritten digital recognition (minst) with convolution neural network can be run directly and the recognition rate is high. Implemented with Tensorflow
ann
- 用简单神经网络(CNN)实现的手写数字识别(minst),可直接运行，用的是Tensorflow框架，通过该例程可以掌握Tensorflow基本用法-With a simple neural network (CNN) to achieve the handwritten numeral recognition (minst), can be run directly, using the Tensorflow framework, through the routine can master
NLP
- Tensorflow框架下的手写数字识别-In recognition of handwritten numerals frame Tensorflow
dnn
- 用TensorFlow搭建神经网络，识别手写数字(building the neural network by using TensorFlow to identify mnist dataset)
tensorflow.tar
- tensorflow入门教程，识别手写数字demo(Tensorflow tutorial, recognition of handwritten digital demo)
mnist
- 深度学习时间手写数字识别，使用python和tensorflow实现(Handwritten numerals recognition in depth learning time)
5-4 tensorboard visualization
- tensorflow手写数字识别学习，根据样本进行计算(learn TensorFlow with mnist)
mnistA
- 手写识别，基于tensorflow的代码，包含数据源等，供学习，代码为官方源代码(Handwriting recognition, tensorflow based code, including data sources, etc. for learning, the code is official source code)
tensorboard
- tensorflow手写数字识别，提高识别的准确率(Tensorflow handwritten numeral recognition, improve the accuracy of recognition.)
张哲_017034910051_03
- 基于tensorflow的手写数字识别，MLP和CNN对比(the compare between MLP and CNN in Handwriting recognition.)
基于Tensorflow的CNN数字识别
- 本文实现了基于minist的手写数字识别，基于TensorFlow的python语言，程序有详细的注释，以及手把手教你怎么搭建CNN(This article implements the handwritten numeral recognition based on minist, the python language based on TensorFlow, the program has detailed annotations, and hands-on instructions o
Tensorflow CNN
- 卷积神经网络识别手写数字，放在jupyter直接跑，99%识别率，已经和Tensorboard联通好了(Convolutional neural network recognizes handwritten numerals and runs directly on jupyter. The recognition rate is 99%. It has been connected with Tensorboard.)
深度学习基础
- 了解深度学习基本原理 掌握TensorFlow基本概念和应用 掌握tensorboard基本应用 掌握PaddlePaddle基本应用(Understand the fundamentals of deep learning Master the basic concept and application of tensorflow Master the basic application of tensorboard Master the basic application of