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全国招聘数据
用于爬去前程无忧招聘信息，可以爬取 人工智能 python 等十几种职业(Used to climb the future worry-free recruitment information)
- 2019-01-26 12:32:03下载
- 积分：1
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Chapter01
说明： 《PyQt5快速开发与实战》
第一章节程序(PyQt5 Rapid Development and Practice
Chapter I Procedure)
- 2020-06-21 07:40:02下载
- 积分：1
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Air_Pollution_Forcast_Beijing-master
说明： 使用LSTM算法，对北京的空气质量进行预测，得到未来的拟合。(LSTM algorithm is used to predict the air quality in Beijing and get the future fitting.)
- 2019-03-19 09:35:32下载
- 积分：1
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Classifying-plankton
kaggle-浮游生物分类比赛一等奖（采用深度学习算法） -译文，主要包括：
1）介绍
2）预处理和data augmentation
3）network 结构
4）模型训练
5）非监督和半监督方法
6）model averaging
7）汇总（Miscellany）
8）总结(kaggle- plankton classification competition first prize (deep learning algorithm) - translation, including: 1) Introduction 2) pre-processing and data augmentation 3) network structure 4) model training 5) unsupervised and semi-supervised method 6 ) model averaging 7) Summary (Miscellany) 8) summarized)
- 2016-01-21 09:34:28下载
- 积分：1
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Output_analysis
说明： 用于处理LPJ-DGVM模型输出数据，这是一个生态模型，模拟的是植被类型(It is used to process the output data of lpj-dgvm model, which is an ecological model that simulates vegetation types)
- 2020-09-19 09:37:53下载
- 积分：1
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py-faster-rcnn-master
图像检测的算法，Faster R-CNN算法，先对整张图像进行卷积计算，然后通过感兴趣区域池化层(RoI Pooling Layer)将选择性搜索算法推荐出来的候选区域和卷积网络计算出的特征映射图进行融合，得到候选区域对应的特征矢量，这种共享卷积计算的操作极大地减少了卷积计算的次数。而且这些特征矢量的维度统一，方便后续的分类工作。通过感兴趣区域池化层处理卷积特征，并将得到的特征送往两个并行计算任务进行训练，分类和定位回归。通过这些方法和改进的框架，Fast R-CNN 用更短的训练和测试时长，取得了比 R-CNN 更好的效果(Faster R-CNN algorithm first convolutes the whole image, then fuses the candidate regions recommended by the selective search algorithm and the feature mapping maps calculated by the convolution network through the RoI Pooling Layer to get the corresponding feature vectors of the candidate regions, which greatly reduces the number of convolution calculations. Moreover, the dimension of these feature vectors is unified, which facilitates the subsequent classification work. The convolution feature is processed by the pooling layer of the region of interest, and the obtained feature is sent to two parallel computing tasks for training, classification and positioning regression. Through these methods and improved framework, Fast R-CNN uses shorter training and testing time and achieves better results than R-CNN.)
- 2020-12-11 15:39:18下载
- 积分：1
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Proximal_Policy_Optimization
说明： 强化学习可以按照方法学习策略来划分成基于值和基于策略两种。而在深度强化学习领域将深度学习与基于值的Q-Learning算法相结合产生了DQN算法，通过经验回放池与目标网络成功的将深度学习算法引入了强化学习算法。(Reinforcement learning can be divided into value-based learning and strategy based learning according to method learning strategies. In the field of deep reinforcement learning, dqn algorithm is generated by combining deep learning with value-based Q-learning algorithm. Through experience playback pool and target network, deep learning algorithm is successfully introduced into reinforcement learning algorithm.)
- 2019-12-04 10:54:55下载
- 积分：1
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BIMS
通过Python实现的桥梁管理系统 桌面程序，管理桥梁的各类参数。实现登录功能及各种参数管理，权限管理。(bridge infomation system)
- 2018-01-27 00:11:05下载
- 积分：1
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DBSCAN聚类
Python密度聚类
最近在Science上的一篇基于密度的聚类算法《Clustering by fast search and find of density peaks》引起了大家的关注(在我的博文“论文中的机器学习算法——基于密度峰值的聚类算法”中也进行了中文的描述)。于是我就想了解下基于密度的聚类算法，熟悉下基于密度的聚类算法与基于距离的聚类算法，如K-Means算法之间的区别。
基于密度的聚类算法主要的目标是寻找被低密度区域分离的高密度区域。与基于距离的聚类算法不同的是，基于距离的聚类算法的聚类结果是球状的簇，而基于密度的聚类算法可以发现任意形状的聚类，这对于带有噪音点的数据起着重要的作用。(The main goal of the density based clustering algorithm is to find high density regions separated by low density regions. Different from distance based clustering algorithm, the clustering results based on distance clustering algorithm are spherical clusters, and density based clustering algorithm can detect clustering of arbitrary shapes, which plays an important role in data with noisy points.)
- 2018-02-05 10:00:46下载
- 积分：1
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bp神经网络python实现
利用python实现bp神经网络，采用误差逆传播算法训练模型，并在一个toy set上进行了验证
- 2019-11-14下载
- 积分：1
