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论文解读Attention Is All You Need

1 minute read

Published:

Google提出的语言模型Transformer,抛弃了传统的CNN和RNN,整个网络结构完全是由Attention机制组成。

机器学习中的样本量问题

1 minute read

Published:

在机器学习业务中经常需要评估模型的效果。例如在流量划分实验A/B Test中,我们需要确定需要多少流量可以得出统计结论是模型A好还是模型B好。一个显而易见的结论是流量越多越好,但是流量切分试验做得越久,也就意味着更多损失。所以我们需要确定样本量来对流量实验进行统计检验。

机器学习业务评估统计方法

5 minute read

Published:

工业界机器学习模型常需围绕业务展开,除了机器学习本身的模型评估指标外(如LogLoss、AUC、KL等),还需要针对业务目标进行相关统计信息评估,完成针对部分流量样本上线模型后的效果分析。例如,一个模型上线后因灰度测试考虑往往先分配较少流量,当讨论测试结果是否显著用以衡量新模型有效性时,就需要使用统计评估方法。本文汇总一些常用统计方法,用于分析统计量之间的关系。

Deep Reinforcement Learning: Pong from Pixels学习笔记

less than 1 minute read

Published:

Deep Reinforcement Learning: Pong from Pixels是一篇很好的强化学习入门博文。其中详细介绍了DRL一种常用的方法:Policy Gradient。原文链接:http://karpathy.github.io/2016/05/31/rl/

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CST207 Design and Analysis of Algorithms

Undergraduate course of computer science and technology, Xiamen University Malaysia, 2020-04

This course covers introduction to algorithms, asymptotic analysis, analyzing algorithms, probabilistic analysis, recursive algorithm, divide-and-conquer algorithms, dynamic programming, greedy algorithms, NP-complete theory, backtracking, branch-and-bound, searching problems and approximation algorithms.

SWE404 Big Data Analytics

Undergraduate course of software engineering, Xiamen University Malaysia, 2020-04

We look at the details of the big data tools Hadoop, Spark and related tools that provide SQL-like access to unstructured data. Some more advanced techniques such as Spark Streaming and MLlib will also be introduced. Based on Python, we use PySpark as the main programming tool to implement big data applications. We also introduce some machine learning techniques such as classification, regresion, clustering and collaborative filtering and how to implement them to real applications using PySpark and MLlib API.

深度学习

计算机科学系研究生课程, 厦门大学, 2020-09

Coming Soon…

离散数学

计算机科学系本科生课程, 厦门大学, 2020-09

Coming Soon…