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SimpleZzz's Projects

alfred icon alfred

alfred-py: A deep learning utility library for visualization and sensor fusion purpose

awesome-java-books icon awesome-java-books

Java开发者技术书籍大全 - Java入门书籍,Java基础及进阶书籍,框架与中间件,架构设计,设计模式,数学与算法,JVM周边语言,项目管理&领导力&流程,职业素养与个人成长,格局与视野,面试参考书等。

basic_cnns_tensorflow2 icon basic_cnns_tensorflow2

A tensorflow2 implementation of some basic CNNs(MobileNetV1/V2/V3, EfficientNet, ResNeXt, InceptionV4, InceptionResNetV1/V2, SENet, SqueezeNet, DenseNet, ShuffleNetV2, ResNet).

cifar10-tensorflow icon cifar10-tensorflow

cifar10数据集上进行图片分类,基于tensorflow框架,旨在探究不同的改进策略对分类准确率的影响,如何一步步得提高准确率

cs-book icon cs-book

计算机类常用电子书整理,并且附带下载链接,包括Java,Python,Linux,Go,C,C++,数据结构与算法,人工智能,计算机基础,面试,设计模式,数据库,前端等书籍

fucking-algorithm icon fucking-algorithm

刷算法全靠套路,认准 labuladong 就够了!English version supported! Crack LeetCode, not only how, but also why.

garbage_classify icon garbage_classify

最严垃圾分类政策自7月1日颁布,如何进行垃圾分类已经成为居民生活的灵魂拷问。但是,没关系!AI在垃圾分类的应用可以成为居民的得力助手。本次垃圾分类挑战杯,目的在于构建基于深度学习技术的图像分类模型,实现垃圾图片类别的精准识别,大赛参考深圳垃圾分类标准,按可回收物、厨余垃圾、有害垃圾和其他垃圾四项分类。

imageprocessing100wen icon imageprocessing100wen

「画像処理100本ノック」中文版本!为图像处理初学者设计的 100 个问题。

interview_internal_reference icon interview_internal_reference

2019年最新总结,阿里,腾讯,百度,美团,头条等技术面试题目,以及答案,专家出题人分析汇总。

java-summarize icon java-summarize

:books:Java核心知识点整理(包括Java基础、JVM、数据库、计算机网络、算法、操作系统、设计模式、系统设计、框架原理)

javafamily icon javafamily

【Java面试+Java学习指南】 一份涵盖大部分Java程序员所需要掌握的核心知识。

nndl.github.io icon nndl.github.io

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

nobelium icon nobelium

A static blog build on top of Notion and NextJS, deployed on Vercel.

notionnext icon notionnext

使用 NextJS + Notion API 实现的,支持多种部署方案的静态博客,无需服务器、零门槛搭建网站,为Notion和所有创作者设计。 (A static blog built with NextJS and Notion API, supporting multiple deployment options. No server required, zero threshold to set up a website. Designed for Notion and all creators.)

rocalphago icon rocalphago

An independent, student-led replication of DeepMind's 2016 Nature publication, "Mastering the game of Go with deep neural networks and tree search" (Nature 529, 484-489, 28 Jan 2016), details of which can be found on their website https://deepmind.com/publications.html.

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