xiaoerlaigeid / finch

Applied Machine Learning Models (mainly TF, sometimes PyTorch)

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ucl-logo These are the models coded and used by me, organized by where it is applied;

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Installation

The following command clones all the files (>200MB);

git clone https://github.com/zhedongzheng/finch.git

Test scripts can be run, the contents below are used to index the model and its test scripts;

python xxxx_test.py

I have used these well-known libraries across different sections:

Style of My Code

Most models are written in scikit-learn interfaces, with fit() and predict() methods;

Contents

Natural Language Processing

Text Representation

Text Classification

Text Generation

Text Labelling

Text to Text

Image To Text

(To run this section, you need to download COCO dataset first)

  • TensorFlow   |   CNN + RNN     Model     COCO Test   |  

  • TensorFlow   |   CNN + RNN + Attention + Beam-Search     Model     COCO Test   |  

  • TensorFlow   |   Fine-tuning CNN + RNN + Attention + Beam-Search     Model     COCO Test   |  

Computer Vision

OpenCV

Image Classification

Image Generation

Reinforcement Learning

Information Retrieval

Recommendation System

Shallow Structure Models

Linear Model

  • TensorFlow   |   Linear Regression     Model     Test   |  

  • TensorFlow   |   Logistic Regression     Model     Test   |  

  • TensorFlow   |   Support Vector Machine     Model     Test   |  

  • Java   |   Logistic Regression     Model     Test   |  

  • Java   |   Support Vector Machine     Model     Test   |  

Non-Linear Model

Ensemble

  • Python   |   Bagging     Model     Test   |  

  • Python   |   Adaboost     Pseudocode     Model     Test   |  

  • Python   |   Random Forest     Model     Test   |  

Data Science

Time Series

Cloud Computing

Apache Spark

Basics

Database

SQL

About

Applied Machine Learning Models (mainly TF, sometimes PyTorch)


Languages

Language:Jupyter Notebook 85.5%Language:Python 14.1%Language:Java 0.3%Language:Scala 0.1%Language:Shell 0.0%