机器学习领域下的对抗样本攻击是目前研究的热点，这是伯克利分校的入门教材。

I'm glad you're here. It's about time we talked about machine learning. Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. As a subfield of data science, machine learning enables computers to learn through experience: to make predictions about the future using collected data from the past. And the amount of data to be analyzed is enormous! Current estimates put the daily amount of produced data at 2.5 exabytes (or roughly 1 billion gigabytes). Can you believe it? This would be enough data to fill up 10 million blu-ray discs, or amount to 90 years of HD video. In order to deal with this vast amount of data, companies such as Google, Amazon, Microsoft, and Facebook have been heavily investing in the development of data science platforms that allow us to benefit from machine learning wherever we go—scaling from your mobile phone application all the way to supercomputers connected through the cloud.

正在学习中 可运行的matlab ml算法 程序 。我在下载资源里面没搜到，说明我这是独家啊 希望对大家有用

MIMO的ML检测程序。可以直接使用的函数，有详细的备注解释

Long Short Term Memory Networks for Anomaly Detection in Time Series - LSTM在时序数据中的应用

对于安装tensorflow必须的whl文件，支持python3.6版本

本软件为三星ML-1670清零软件，一次操作，永久使用，终身免清。好用极了。要的快来下载使用吧。

直接运行脚本Simulation_Script_BER即可得到SCMA与ML两种调制解调方式的BER性能比较。

unity和python对接的unity包，里面包括完整的文档和环境，当然在github上也可以下载

在Matlab的平台上,应用QPSK调制,以及3种不同的探测方法,实现并模拟了2x2的MIMO功能.