任务11

说明：  基于卷积神经网络和互联网新闻文本的股票趋势预测代码(Stock trend prediction code based on convolutional neural network and Internet news text)

说明：  基于马尔科夫链的非侵入式负荷分解，可实现仅依据智能电表数据对电器用电曲线的提取。(The non-intrusive load decomposition based on Markov chain can realize the extraction of electrical power consumption curves based on smart meter data only.)

帮助安装python，同时了解python的基本界面，以及有关anaconda的知识(to help install python)

说明：  中文语言理解测评基准，包括代表性的数据集、基准(预训练)模型、语料库、排行榜。 我们会选择一系列有一定代表性的任务对应的数据集，做为我们测试基准的数据集。这些数据集会覆盖不同的任务、数据量、任务难度。(Language Understanding Evaluation benchmark for Chinese: datasets, baselines, pre-trained models, corpus and leaderboard)

一个简单的通过按钮弹出新窗口的例子，使用PyQt5&Python3编写。重点是QDialog。(A simple example of popping up a new window through a button is written in PyQt5 & Python 3. The emphasis is on QDialog.)

说明：  cnn深度学习框架，实现手写字符识别。适用于新手学习(CNN deep learning framework for handwritten character recognition)

说明：  trubo code with sova algoritm in matlab

说明：  这是一本很好的适合初学者学习一个的umat子程序帮助文件(This is a very good help file for beginners to learn one umat subprogram)

深度融合网络 Python-ELM：基于Python的极限学习机以及深度极限学习机(Deep fusion network Python-ELM: Python based extreme learning machine and deep extreme learning machine.)

说明：  隐马尔科夫实现，包含forward-hmm, Viterbi-hmm, Baum-Welch-hmm(Hidden Markov implementation, including forward-hmm, Viterbi-hmm, Baum-Welch-hmm)