zhaodelong Goto Github PK
Name: DZ
Type: User
Name: DZ
Type: User
ASP.NET Core rate limiting middleware
A curated list of awesome GitHub repositories. Inspired by awesome-python, which is inspired by awesome-php.
CCEW Fall 2015 iOS Curriculum
CS5153 Network Security Projects
Implementations of decision tree construction algorithms.
The Web framework for perfectionists with deadlines.
Liberate DJI drones. Height limit, NFZ limit, enable Galileo Satellites + more
A microframework based on Werkzeug, Jinja2 and good intentions
Git Cheat Sheet, the Chinese version by Gevin(flyhigher139)
The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more.
Google Core Libraries for Java 6+
Hand written digit recognition with SVM, Decision Tree and Random Forests
Multi-threaded tool for scanning many hosts for CVE-2014-0160.
Random Forests, AdaBoost , ExtraTrees Algorithms applied
:monkey: Chrome extension for leetcode
Lintcode solution in Java.
Classify handwritten digits using machine learning techniques Yan Liang, Yunzhi Wang and Delong Zhao Project scope For our machine learning project, we propose to build several machine learning classifiers that recognize handwritten digits. Handwritten digit recognition is a classic problem in machine learning studies for many years. We plan to do several experiments using different machine learning algorithms and compare the pattern recognition performance. We hope to create a classifier that has same or better categorization accuracy than record performance from previous studies. Yan will focus on neural network, Delong will focus on the random forests methods, and Yunzhi will focus on SVMs and KNNs. We will also develop a final novel classifier that combines the best models from our different experiments. We hypothesize that the final classifier will archive a categorization accuracy of 0.99. This indicates that the classifier correctly classified all the handwritten digits but 1% of the images. The goal of handwritten digit recognition is to determine what digit is from an image of a single handwritten digit. It can be used to test pattern recognition theories and machine learning algorithms. Preprocessed standard handwritten digit image database has been developed to compare different digit recognizers. In our semester project, we will use modified National Institute of Standards and Technology (MNIST) handwritten digit images dataset from kaggle digit recognizer project. The Kaggle MNIST dataset is freely available and collected 28,000 training images and 42,000 test images. Each image is a preprocessed single black and white digit image with 28 x 28 pixels. Each pixel is an integer value range from 0 to 255 which represent the brightness of the pixel, the higher value meaning darker. Each image also has a label which is the correct digit for the handwritten image. For each input handwritten image, our model will output which digit we predict and evaluate with the correct label. We will use 28,000 training images to train our machine learning model and use 42,000 test images to test the performance. Then we will calculate the percentage of the test images that are correctly classified and compare the performance of different machine learning algorithms.
Machine Learning class notes
Pocsuite 是知道创宇安全研究团队打造的一款基于漏洞与 PoC 的远程漏洞验证框架,Pocsuite is A remote vulnerability test framework developed by Knownsec Security Team.
Python implementation of CART regression tree and random forests
Leetcode in python
Laioffer Project Class
A python SAGE code to show the basic RSA encryption and decription
scikit-learn: machine learning in Python
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.