Name: Andrew Wan
Type: User
Company: Beihang University
Bio: A Ph.D student;
Research on intelligent software engineering;
Interest in machine learning deep learning techniques.
Location: Beihang University, Beijing, 100191, China
Andrew Wan's Projects
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
The classical papers and codes about generative adversarial nets
将深度神经网络中的一些模型 进行统一的图示,便于大家对模型的理解
Codes related to activities on AV including articles, hackathons and discussions.
A curated list of automated machine learning papers, articles, tutorials, slides and projects
A curated list of awesome Deep Learning tutorials, projects and communities.
Empirical Study of Transformers for Source Code & A Simple Approach for Handling Out-of-Vocabulary Identifiers in Deep Learning for Source Code
My codes on Machine Learning
This project conducts an empirical study to estimate the hardness of over 33,000 instances, employing a set of measures to characterize the inherent difficulty of instances and the characteristics of defect datasets.
This repo contain the syllabus of the Hugging Face Deep Reinforcement Learning Class.
Notes, Codes, and Tutorials for the Deep Learning Course at ChinaHadoop
【深度强化学习社区】一个资料与学习内容最全的服务平台
Feature implementation on white-box DL systems testing framework for Software Engineering Senior Design class
A Systematic Literature Review of Deep Learning in Software Engineering
`dslinter` is a pylint plugin for linting data science and machine learning code. We support the following Python libraries: TensorFlow, PyTorch, Scikit-Learn, Pandas, NumPy and SciPy.
TensorFlow tutorials and best practices.
OReilly Hands On Machine Learning with Scikit Learn and TensorFlow (Sklearn与TensorFlow机器学习实用指南)
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Lightweight Assessment of Test-Case Effectiveness using Source-Code-Quality Indicators
Models and examples built with TensorFlow
Python Implementation of Reinforcement Learning: An Introduction
SmellML is a tool that combines different code smelling tools for python into a nice, compact, push button tool.
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Example TensorFlow codes and Caicloud TensorFlow as a Service dev environment.