Name: Jianqiao Mao
Type: User
Company: University of Birmingham
Bio: Jianqiao Mao is a PhD student at University of Birmingham, awarded with studentship from the HDRUK-Alan Turing PhD Programme supported by Wellcome Trust.
Location: Birmingham
Blog: https://mjqtech.blog
Jianqiao Mao's Projects
The AMLS assignment of UCL IMLS
The assignment code of AMLS (2020-2021)
This code is for use within the UCL Electronic Engineering AMLS II module (ELEC0135).
The code of AMLS II assignment(2020-2021)
CausalBootstrapping is an easy-access implementation and extention of causal bootstrapping (CB) technique for causal analysis. With certain input of observational data, causal graph and variable distributions, CB resamples the data by adjusting the variable distributions which follow intended causal effects.
Repository for the workshop, including tutorial material
A enhanced XGBM by considering a loss function with higher order.
GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference
The open-access code of an interpretable machine learning-based method for room temperature prediction in a non-domestic building.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Mechanism learning library is a library to provide an easy approach to ensure the model can capture the causal relationships between the cause and the effect given an observable mediator when some unobservable confounders influencing both the cause and effect. The library is compatible with most existing ML models.
A tool box of commonly used techniques in data science coding.
Coding assignments materials
An Interpretable Machine Learning technique to analyse the contribution of features in the frequency domain. This method is inspired by permutation feature importance analysis but aims to quantify and analyse the time-series predictive model's mechanism from a global perspective.
My undergraduate Final Year Project awarded as the Excellent Bachelor's Project. It develops a vision-based sign language recognition system with multiple machine-learning models, which currently can recognize 10 static and 2 dynamic gesutures in ASL with testing accuracy of 99.68%.
Analyze large data sets collected from a long-range IoT system that uses LoRaWAN networking
This project aims to design a real-time vision-based hand gesture recognition system with machine learning techniques, which potentially makes deaf-and-mute people life easier.