jccmoing-bit Goto Github PK

bilibilitask

哔哩哔哩(B站)自动完成每日任务，投币，点赞，直播签到，自动兑换银瓜子为硬币，自动送出即将过期礼物，漫画App签到。

bokeh

Interactive Data Visualization in the browser, from Python

bthub

Bthub最新地址发布页

cma-web

气象数据综合展示平台

corr_prediction_arima_lstm_hybrid

Applied an ARIMA-LSTM hybrid model to predict future price correlation coefficients of two assets

data-competition-topsolution

Data competition Top Solution 数据竞赛top解决方案开源整理

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

earthengine-api

Python and JavaScript bindings for calling the Earth Engine API.

eat_pyspark_in_10_days

pyspark🍒🥭 is delicious，just eat it!😋😋

eat_pytorch_in_20_days

Pytorch🍊🍉 is delicious, just eat it! 😋😋

eat_tensorflow2_in_30_days

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

faster-rcnn-pytorch

这是一个faster-rcnn的pytorch实现的库，可以利用voc数据集格式的数据进行训练。

geemap

A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and folium

joyful-pandas

Pandas中文教程

keras-tutorials

lhy_machine_learning

李宏毅2021春季机器学习课程课件及作业

lite-hrnet

This is an official pytorch implementation of Lite-HRNet: A Lightweight High-Resolution Network.

mifs

Parallelized Mutual Information based Feature Selection module.

nndl.github.io

《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning

predictive-maintenance-using-lstm

Example of Multiple Multivariate Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras.

pydataroad

open source for wechat-official-account (ID: PyDataLab)

pyecharts

🎨 Python Echarts Plotting Library

pymeteo

用Python处理我遇到的气象数据

pymrmr

Python3 binding to mRMR Feature Selection algorithm (currently not maintained)

python-machine-learning-book-3rd-edition

The "Python Machine Learning (3rd edition)" book code repository

qgis

QGIS is a free, open source, cross platform (lin/win/mac) geographical information system (GIS)

roaddamagegan

sarima-lstm

建立SARIMA-LSTM混合模型预测时间序列问题。以PM2.5值为例，使用UCI公开的自2013年1月17日至2015年12月31日五大城市PM2.5小时检测数据，将数据按时间段划分，使用SARIMA过滤其线性趋势，再对过滤后的残差使用LSTM进行预测，最后对预测结果进行检验和分析。

satellite-image-deep-learning

Resources for deep learning with satellite & aerial imagery

smart_construction

Head Person Helmet Detection on Construction Sites，基于目标检测工地安全帽和禁入危险区域识别系统，🚀😆附 YOLOv5 训练自己的数据集超详细教程🚀😆2021.3新增可视化界面❗❗