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awesome-algorithm

Leetcode 题解 (跟随思路一步一步撸出代码) 及经典算法实现

cnn_finetune

Fine-tune CNN in Keras

cnn_models

train with all main stream cnn models

deep-learning-with-keras-notebooks

Jupyter notebooks for using & learning Keras

deeplearning

深度学习入门教程&&优秀文章&&Deep Learning Tutorial

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

forest-fire-detection-through-uav-imagery-using-cnns

Wildfire is a natural disaster, causing irreparable damage to local ecosystem. Sudden and uncontrollable wildfires can be a real threat to residents’ lives. Statistics from National Interagency Fire Center (NIFC) in the USA show that the burned area doubled from 1990 to 2015 in the USA. Recent wildfires in northern California (reported by CNN) have already resulted in more than 40 deaths and 50 missing. More than 200,000 local residents have been evacuated under emergency. The wildfires occur 220,000 times per year globally, the annual burned area is over 6 million hectares. Accurate and early detection of wildfire is therefore of great importance. Fire detection task is crucial for people safety. Several fire detection systems were developed to prevent damages caused by fire. One can find different technical solutions. Most of them are sensors based and are also generally limited to indoors. They detect the presence of particles generated by smoke and fire by ionization, which requires a close proximity to the fire. Consequently, they cannot be used in large covered area. Moreover, they cannot provide information about initial fire location, direction of smoke propagation, size of the fire, growth rate of the fire, etc. To get over such limitations video fire detection systems are used

hands_on_ml_with_sklearn_and_tf

OReilly Hands On Machine Learning with Scikit Learn and TensorFlow (Sklearn与TensorFlow机器学习实用指南)

hello-world

just is test

javainterview

【Java面试+Java后端技术学习指南】：一份通向理想互联网公司的面试指南，包括 Java，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、分布式、数据库（MySQL、Redis）、Java 项目实战等

kaggle

Kaggle 项目实战（教程） = 文档 + 代码 + 视频

kaggle-dogs-vs-cats

keras

Deep Learning for humans

leetcode

LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

machine_learning

This is a library of machine learning. I designed it to learn more about machine learning.

mall-tiny

mall-tiny是一款基于SpringBoot+MyBatis-Plus的快速开发脚手架，拥有完整的权限管理功能，可对接Vue前端，开箱即用。

ml-in-action-code-and-note

:chart_with_upwards_trend:Machine Learning code in Python3.x. Some notes about the practices please click here:（personal notes, for reference only）

python_data_analysis_and_mining_action

《python数据分析与挖掘实战》的代码笔记

ruoyi-vue-pro

🔥 官方推荐 🔥 RuoYi-Vue 全新 Pro 版本，优化重构所有功能。基于 Spring Boot + MyBatis Plus + Vue & Element 实现的后台管理系统 + 微信小程序，支持 RBAC 动态权限、数据权限、SaaS 多租户、Activiti + Flowable 工作流、三方登录、支付、短信、商城等功能。你的 ⭐️ Star ⭐️，是作者生发的动力！

shopping-management-system

该项目为多个小项目的集合（持续更新中...）。内容类似淘宝、京东等网购管理系统以及图书管理、超市管理等系统。目的在于便于Java初级爱好者在学习完某一部分Java知识后有一个合适的项目锻炼、运用所学知识，完善知识体系。适用人群：Java基础到入门的爱好者。

technology-talk

汇总java生态圈常用技术框架、开源中间件，系统架构、数据库、大公司架构案例、常用三方类库、项目管理、线上问题排查、个人成长、思考等知识

tensorflow-examples

TensorFlow Tutorial and Examples for Beginners with Latest APIs

tensorflow-tutorial

Example TensorFlow codes and Caicloud TensorFlow as a Service dev environment.