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目前全网最全面的2023年信息系统项目管理师（软考高级）备考资源库。仅供个人学习，请勿用于商业

a-dual-stage-attention-based-recurrent-neural-network-for-time-series-prediction

cnn_finetune

Fine-tune CNN in Keras

contrad

Code for the paper "Training GANs with Stronger Augmentations via Contrastive Discriminator" (ICLR 2021)

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

dag-gans

Data Augmentation optimized for GAN

eemd-lstm-do-prediction

EEMD(集合经验模态分解)、LSTM(长短时记忆网络)、time series prediction(时间序列预测)、DO（dissolved oxygen,溶解氧）、Deep Learning

emd-alstm-multi-factor-stock-profit-prediction

Multi-Factor Stock Profit Prediction Using EMD-ALSTM

experiments_with_python

experiments with python

finrl-library

A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance, NeurIPS 2020 DRL workshop.

futures-data

上海期货市场2010年到2019年金属期货价格数据

futures-data-mtal

上海期货市场数据金属期货价格数据

geoman

Tensorflow Implement of GeoMAN, IJCAI-18

it_book

本项目收藏这些年来看过或者听过的一些不错的常用的上千本书籍，没准你想找的书就在这里呢，包含了互联网行业大多数书籍和面试经验题目等等。有人工智能系列（常用深度学习框架TensorFlow、pytorch、keras。NLP、机器学习，深度学习等等），大数据系列(Spark,Hadoop,Scala,kafka等)，程序员必修系列（C、C++、java、数据结构、linux，设计模式、数据库等等）

java-notes

一份面向Java初学者和初级工程师的知识点总结和面试题解析，着重关注面试中最常见的知识点。

javaguide

「Java学习+面试指南」一份涵盖大部分Java程序员所需要掌握的核心知识。准备 Java 面试，首选 JavaGuide！

learn_dl

Deep learning algorithms source code for beginners

lstm-attention

A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series

market-gen

Generate time series data with Transformer model

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

opencv3-intro-book-src

:blue_book:《OpenCV3编程入门》书本配套源码 |《Introduction to OpenCV3 Programming》Book Source Code

organ

Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models

predrnn-pp

Code release for "PredRNN++: Towards A Resolution of the Deep-in-Time Dilemma in Spatiotemporal Predictive Learning" (ICML 2018)

python-100-days

Python - 100天从新手到大师

software-designer

软考中级教程-软件设计师

spatiotemporal-attention-networks

Spatiotemporal Attention Networks for Wind Power Forecasting

ssmcrud

IDEA，SSM框架写的员工增删改查

stock-prediction-models

Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations

stock-price-prediction-using-gan

In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.

tcn

Sequence modeling benchmarks and temporal convolutional networks