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利用遗传算法求解柔性车间调度问题，采用Python编程实现(Using Genetic Algorithm to Solve Flexible Workshop Scheduling Problem)

说明：  卷积神经网络的经典结构Xception的Keras实现(Keras implementation of xception, a classical structure of convolutional neural networks)

利用高德API爬取行政区域边界，生成csv文件。利用高德API爬取行政区域边界，生成csv文件。利用高德API爬取行政区域边界，生成csv文件。利用高德API爬取行政区域边界，生成csv文件。

利用地图图像的像素点与真实世界对应，进行路径规划，曲线使用三阶贝塞尔曲线生成(Using the correspondence between the pixels of the map and the real world, the path planning is carried out, and the curve is generated by the three order Bessel curve.)

说明：  实现人脸检测，基于opencv实现人脸检测(Realize face detection, and realize face detection based on OpenCV)

深度学习的中文版本，里面详细介绍了深度学习的各种算法，其中还有一些用到的基础内容，例如矩阵和向量的范数(Chinese version of the depth of learning, which detailed the depth of learning algorithms, some of which used the basics, such as vector and matrix norm)

小型文本文档的编译程序，可供初级学习Python语言的伙伴，作参考联系使用，仅供参考，(Compilers for small text documents can be used as reference links for beginner Python language learners only.)

python django项目源码学生管理

Python是一种面向对象、解释型计算机程序设计语言，其应用领域非常广泛，包括数据分析、自然语言处理、机器学习、科学计算以及推荐系统构建等。 本书用Python语言来讲解算法的分析和设计。本书主要关注经典的算法，但同时会为读者理解基本算法问题和解决问题打下很好的基础。(Python is an object-oriented, interpretive computer programming language. It has a wide range of applications, including data analysis, natural language processing, machine learning, scientific computing and recommendation system construction. This book uses Python language to explain the analysis and design of algorithms. This book focuses on classical algorithms, but at the same time it will lay a good foundation for readers to understand basic algorithms and solve problems. The book consists of 11 chapters. The tree, graph, counting problem, inductive recursion, traversal, decomposition and merging, greedy algorithm, complex dependency, Dijkstra algorithm, matching and cutting problem, difficult problem and its dilution are introduced. The book has exercises and reference materials at the end of each chapter, which provides readers with more convenience for self-examination and further stu)

说明：  循环神经网络LSTM可以预测时间序列数据，根据历史时刻的信息预测未来时刻的信息(the recurrent neural network is very useful to predict data in the future)