rcnn行人检测

作者是Sebastian Raschka，密歇根州立大学的博士生，他在计算生物学领域提出了几种新的计算方法，还被科技博客Analytics Vidhya评为GitHub上最具影响力的数据科学家。他有一整年都使用Python进行编程的经验，同时还多次参加数据科学应用与机器学习领域的研讨会。在数据科学、机器学习以及Python等领域他拥有丰富的演讲和写作经验，本书可使得不具备机器学习背景的人设计出由数据驱动的解决方案。(The author, Sebastian Raschka, a PhD student at Michigan State University, has come up with several new computational methods in computational biology and has been named the most influential data scientist on GitHub by Analytics Vidhya, a technology blog. He has a year of programming experience using Python, and has attended many seminars in data science applications and machine learning. He has extensive lecture and writing experience in data science, machine learning, and Python, and this book enables people who do not have a machine learning background to design data-driven solutions.)

说明：  这是书籍《深度学习与图像处理》源代码，有一定参考价值。(This is the source code of the book "Deep Learning and Image Processing", which has certain reference value.)

说明：  基于LSTM的时间序列预测-原理-python代码(Prediction of time series based on LSTM - principles -python code)

说明：  采用gabor算法，灰度共生矩阵、灰度梯度共生矩阵提取图像纹理信息(Using Gabor algorithm, gray level co-occurrence matrix and gray level gradient co-occurrence matrix to extract image texture information)

生成正态分布的随机数，并生成toeplitz矩阵，对随机数进行后处理，输出0-1均匀分布的随机数

knn手写数字识别，tensorflow教程(Knn Handwritten Number Recognition)

说明：  template for flask applications

说明：  How to use python to make games

pdf文件通过python fitz 第三方库 转化成jpg或者png图片文件。(Pdf files are converted into JPG or PNG image files through Python Fitz third-party library.)

说明：  deep+learning深度学习人工智能资料(deep+learning Deep learning of AI materials)