搜索资源列表
protobuf-2.6.1.tar
- protocolbuffer(以下简称PB)是google 的一种数据交换的格式，它独立于语言，独立于平台。google 提供了多种语言的实现：java、c#、c++、go 和 python，每一种实现都包含了相应语言的编译器以及库文件。由于它是一种二进制的格式，比使用 xml 进行数据交换快许多。可以把它用于分布式应用之间的数据通信或者异构环境下的数据交换。作为一种效率和兼容性都很优秀的二进制数(Protocolbuffer (her
wps-back
- 采用tensorflow的深度学习框架，采用opencv，采用时间戳，和特征抓取，自动抓取图片特征，然后存储(Using tensorflow's deep learning fr a mework, opencv, timestamp, and feature capture are used to automatically capture image features, and then store them)
MachineLearning-master
- 垃圾邮件处理，贝叶斯算法，Python，机器学习，深度学习。(Spam processing, Bayesian algorithm, Python, machine learning, deep learning.)
1_notmnist
- 爬取数据、整理并打包成pickle文件、用于机器学习亦或者深度学习、适合TensorFlow开发者使用。(Crawling data, sorting and packaging into pickle files)
莫烦tf练习
- tensorflow深度学习，莫烦入门教程代码(Tensorflow deep learning)
VGG-16
- fds 实现深度学习的vgg网络，图像识别，机器学习的等等(fds adf fdsa fdsw gfdsae vfdsgasw fd)
Machine Learning Mastery with Python
- 各种机器学习算法的Python优雅实现，尤其是深度学习部分，应用到了TensorFlow(Python elegant implementation of various machine learning algorithms)
test1
- 神经网络，深度学习上非常经典的例子-RNN循环神经网络，使用mnist数据集，代码简单易懂，学习方便(Neural network, deep learning is a very classic example -RNN circular neural network, the use of mnist data sets, the code is easy to understand, easy to learn)
Tensorflow 实战Google深度学习框架
- TensorFlow的一些样例代码。Tensor（张量）意味着N维数组，Flow（流）意味着基于数据流图的计算，TensorFlow为张量从流图的一端流动到另一端计算过程。TensorFlow是将复杂的数据结构传输至人工智能神经网中进行分析和处理过程的系统。(Tensor (Zhang Liang) means N dimension array. Flow (flow) means computation based on data
Python Deep Learning - Valentino Zocca
- 能够为我们的学习打下很好的基础，有利于我们学习深度学习(We can lay a good foundation for our study and help us to learn in depth.)
pycuda-2017.1.1.tar
- 矩阵相乘的并行运算的算法，运算效率可以轻松提高近100倍。是进行人工智能研究及深度学习先关研究的必备并行算法。(The algorithm of parallel operation of matrix multiplication can easily increase the operation efficiency by nearly 100 times. It is a necessary parallel algorithm
cnn_checkers_game-master
- 用Python写的深度学习CNN的英国跳棋，用tenserflow训练，很有参考价值(Learning CNN's British checkers with the depth of Python, trained with tenserflow, is of great reference value)
numpy
- 图像处理，理论研究，深度学习，机器学习，python(Image processing, theoretical research, depth learning, machine learning, Python)
Deep+Learning+with+Python+2017
- 如何使用python实现深度学习，是外文电子书籍，书里的内容较容易上手(How to use Python to realize deep learning)
qlearning4k-master
- qlearning4k是强化学习Python深度学习lib库Keras插件。它简单，是快速成型的理想选择。(Qlearning4k is a reinforcement learning add-on for the python deep learning library Keras. Its simple, and is ideal for rapid prototyping.)
alexnet
- alexnet网络结构，基于python语言下的tensorflow框架(The network structure of alexnet)
cartpole-dqn
- 利用deep q learning 的算法学习玩open ai gym里的cartpole游戏(Using deep Q learning algorithm to learn cartpole games in open AI gym)
Tools-deeplearning
- 用于深度学习训练的使用小工具，能够帮助数据生产分类(The use of small tools for deep learning training can help data production and classification)
Python-Tensorflow-Face-master
- Python人脸识别实现，可以打开摄像头进行多人人脸识别，需要一定的深度学习基础(Python face recognition implementation, you can open the camera for multi person face recognition, you need a certain depth of learning foundation.)
Object Detection
- 采用Python语言，在pycharm运行平台下，实现对特定图片中特定物体的检测与提取。(Python language is used to realize the detection and extraction of specific objects in specific pictures on the platform of pycharm.)