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andrewngmachinelearning

androidlinechart

折线图,仿余额宝折线图,金融理财类收益率

bank1

银行系统

banksystem016

SE银行管理系统项目

blog

SpringBoot + Mybatis + thymeleaf 搭建的个人博客 http://www.54tianzhisheng.cn/

camels

Catchment Attributes and Meteorology for Large-sample Studies

crf

keras implementation of conditional random field

drcf

Rainfall forecasting is a very important problem in the field of hydrology and meteorology. Especially, short-term rainfall forecasting is closely related to resident's daily life. For example, forecasting the situation of stagnant water on the road, providing weather guidance for the flight, and providing short-term heavy rainfall warning in the city.However, existing solutions achieve low prediction accuracy for short-term rainfall forecasting. Numerical forecasting models can achieve overall accuracy but always perform worth in some short-term conditions. Data-driven approaches always neglect the influences of physical factors in upstream or downstream regions, which lead to the forecasting accuracy fluctuates in different areas. Rainfall forecasting is affected by many factors, such as high-altitude physical factors and surface factors.High-altitude physical factors play important roles in the movement of rainfall system. Surface factors on the Earth also cause different rainfall. Difference surface factors represent different factors between region and surrounding area. Therefore, it is very reasonable to forecast rainfall by studying the relations between high-altitude physical factors, surface factors and rainfall. In this project, a Dynamic Regional Combined short-term rainfall forecasting model (DRCF) using Multi-Layer Perceptron (MLP) is proposed. The input of the model includes five high-altitude factors and seven different surface factors. In summary, we have addressed a series of techniques challenges in this work, and the central contributions are summarized as follows: 1.Principle Component Analysis (PCA) is used to determined the input of of MPL and a special greedy algorithm is proposed to determine the suitable structure of MLP. 2.The relation between forecasting area and surrounding area is established using MPL. Based on the relation, a dynamic regional combined rainfall forecasting model is proposed. The strategy of dynamically adjusting area is also enhanced to effectively improve prediction accuracy. 3.The model is finally validated by a large number of meteorological site data, including 56 sites, and these sites are distributed in all parts of China.

ealstm_regional_modeling

Accompanying code for our HESS paper "Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets"

fate

An Industrial Grade Federated Learning Framework

federated-learning

federated learning

federated-metalearning-risk-prediction-ehr

Meta-Learning for Risk Prediction with Limited Patient Electronic Health Records Using PySyft and SyferText

federated-transfer-learning-for-eeg

This is the code of the paper "Federated Transfer Learning for EEG Signal Classification" published in IEEE EMBS 2020 (42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society in conjunction with the 43rd Annual Conference of the Canadian Medical and Biological Engineering Society July 20-24, 2020 via the EMBS Virtual Academy)

fedfomo

fedhydro

The source code of the FedHydro framework

fedml

A Research-oriented Federated Learning Library. Supporting distributed computing, mobile/IoT on-device training, and standalone simulation. Best Paper Award at NeurIPS 2020 Federated Learning workshop. Join our Slack Community:(https://join.slack.com/t/fedml/shared_invite/zt-havwx1ee-a1xfOUrATNfc9DFqU~r34w)

few-shot-regression-meta-learning

Few Shot Regression of Periodic and Basic Polynomial Functions using MAML and Reptile Method

fl

联邦学习预测节点流量

fl-ml

This repo contains source code for federated learning combined with meta-learning.

flink-recommandsystem-demo

:helicopter::rocket:基于Flink实现的商品实时推荐系统。flink统计商品热度，放入redis缓存，分析日志信息，将画像标签和实时记录放入Hbase。在用户发起推荐请求后，根据用户画像重排序热度榜，并结合协同过滤和标签两个推荐模块为新生成的榜单的每一个产品添加关联产品，最后返回新的用户列表。

flow-forecast

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

fsl_ts

few shot learning (MAML) for time series prediction

h5_questionnaire

H5问卷调查模板

hands-on-meta-learning-with-python

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

imoney

iMoney 金融项目

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）

leetcodeanimation

Demonstrate all the questions on LeetCode in the form of animation.（用动画的形式呈现解LeetCode题目的思路）

lstm

Minimal, clean example of lstm neural network training in python, for learning purposes.

lstm-federated-machine-learning

lstm_jhmpaper