WenyiWU's starred repositories

IMC-2024

This is the solution we provided for the "Image Matching Challenge 2024 - Hexathlon" Kaggle competition.

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SToAT

SToAT: Open Statistical Toolkits

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the-algorithm

Source code for Twitter's Recommendation Algorithm

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LAVIS

LAVIS - A One-stop Library for Language-Vision Intelligence

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AI-PhD-S24

Mono repo for the PhD course AI for Business Research (DSME 6635, S24)

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Emotions-recognition-from-audio-signal

Emotions recognition from audio signal using OpenSmile, PCA and set of classifiers from Scikit-learn library

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deep_learning_based_causal_inference_for_combinatorial_experiments

codes for the paper Deep Learning Based Casual Inference for Combinatorial Experiments

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doubleml-for-py

DoubleML - Double Machine Learning in Python

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featurewiz

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

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recommendation

Recommendation System using ML and DL

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chatgpt-prompts-for-academic-writing

This list of writing prompts covers a range of topics and tasks, including brainstorming research ideas, improving language and style, conducting literature reviews, and developing research plans.

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awesome-causality-data

A data index for learning causality.

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Blog-Posts

Code and notebooks for my Medium blog posts

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nonlinear-causal

nl-causal: nonlinear causal inference based on IV regression in Python

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PySensemakr

Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr

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liblinear-sc-reading

LIBLINEAR理论与源码解读(已完结)

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SyntheticControlMethods

A Python package for causal inference using Synthetic Controls

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cem

cem is a lightweight library for performing coarsened exact matching (CEM). CEM is a modern matching technique useful for causal inference on observational data.

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CUHK-STAT3009

Recommender systems in Python

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full-blockchain-solidity-course-py

Ultimate Solidity, Blockchain, and Smart Contract - Beginner to Expert Full Course | Python Edition

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Recommender-System-on-MovieLens-dataset

Knowledge-based, Content-based and Collaborative Recommender systems are built on MovieLens dataset with 100,000 movie ratings. These Recommender systems were built using Pandas operations and by fitting KNN, SVD & deep learning models which use NLP techniques and NN architecture to suggest movies for the users based on similar users and for queries specific to genre, user, movie, rating, popularity.

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Machine-Learning-Collection

A resource for learning about Machine learning & Deep Learning

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pytorch-goodies

PyTorch Boilerplate For Research

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SegLossOdyssey

A collection of loss functions for medical image segmentation

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pytorch-segmentation

:art: Semantic segmentation models, datasets and losses implemented in PyTorch.

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codesnippets

Code Snippets Repository for all my Content

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