xiaoerlaigeid / finch Goto Github PK

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

Keep updating ... ...

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:

• tensorflow >= 1.3
• pytorch >= 0.20
• mxnet >= 0.11
• scikit-learn
• openai-gym
• nltk
• opencv 3

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

• Natural Language Processing
  • Text Representation
  • Text Classification
  • Text Generation
  • Text Labelling
  • Text to Text
  • Image to Text
• Computer Vision
  • OpenCV
  • Image Classification
  • Image Generation
• Reinforcement Learning
• Information Retrieval
  • Recommendation System
• Shallow Structure Models
  • Linear Model
  • Non-Linear Model
  • Ensemble
• Data Science
  • Time Series
• Cloud Computing
  • Apache Spark
• Database
  • SQL

• Python   |   LSA   |   Model for Visualization     Test     Result   |   Model for Concepts     Test     Result   |  

• Python   |   TF-IDF     Model     Test     Result   |  

• TensorFlow   |   Word Embedding - Skip-Gram     Model     Test   |  

• TensorFlow   |   Word Embedding - CBOW     Model     Test   |  

• Python   |   TF-IDF + LR     Model     IMDB Test   |  

• TensorFlow   |   CNN     Model     IMDB Test   |  

• TensorFlow   |   Multi-kernel CNN     Model     IMDB Test     Result   |  

• TensorFlow   |   LSTM     Model     IMDB Test   |  

• TensorFlow   |   CNN-LSTM     Model     IMDB Test   |  

• TensorFlow   |   LSTM + Attention     Model     IMDB Test   |   Model (via tf.estimator)     IMDB Test   |  

• PyTorch   |   CNN     Model     IMDB Test   |  

• PyTorch   |   LSTM     Model     IMDB Test   |  

• PyTorch   |   CNN-LSTM     Model     IMDB Test   |  

• PyTorch   |   LSTM + Attention     Model     IMDB Test   |  

• MXNet   |   CNN     Model     IMDB Test   |  

• Python   |   2nd order Markov     Model     Robert Frost Test   |  

• TensorFlow   |   CNN-Highway-RNN     Paper     Model     PTB Test   |  

• TensorFlow   |   Char-RNN     Model   |   English Test     Chinese Test   |   Model (Beam-Search)     English Test   |  

• PyTorch   |   Char-RNN     Model   |   English Test     Chinese Test   |  

• MXNet   |   Char-RNN     Model   |   English Test     Chinese Test   |  

• TensorFlow   |   LSTM     Model   |   POS Tagging Test   |   Chinese Segmentation Test   |  

• TensorFlow   |   BiLSTM     Model   |   POS Tagging Test   |   Chinese Segmentation Test   |  

• TensorFlow   |   BiLSTM + CRF     Model   |   POS Tagging Test   |   Chinese Segmentation Test   |  

• PyTorch   |   LSTM     Model   |   POS Tagging Test   |   Chinese Segmentation Test   |  

• PyTorch   |   BiLSTM     Model   |   POS Tagging Test   |   Chinese Segmentation Test   |  

• TensorFlow   |   Seq2Seq     Model     Sorting Test   |   Model (via tf.estimator)     Sorting Test   |  

• TensorFlow   |   Seq2Seq + Attention     Model     Sorting Test   |  

• TensorFlow   |   Seq2Seq + BiLSTM Encoder     Model     Sorting Test   |  

• TensorFlow   |   Seq2Seq + Beam-Search     Model     Sorting Test   |  

• TensorFlow   |   Seq2Seq + BiLSTM Encoder + Attention + Beam-Search     Model     Sorting Test   |  

• TensorFlow   |   Varational Recurrent Autoencoder   |  

• PyTorch   |   Seq2Seq     Model     Sorting Test   |  

• PyTorch   |   Seq2Seq + Attention     Model     Sorting Test   |  

• PyTorch   |   Seq2Seq + BiLSTM Encoder     Model     Sorting Test   |  

(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   |  

• OP   |   Resize

• OP   |   Rotations

• Segmentation   |   Contours

• Segmentation   |   Sorting Contours

• Segmentation   |   Line detection

• Segmentation   |   Circle detection

• Segmentation   |   Blob detection

• Detection   |   Face & Eye Detection Using Cascade Classifier

• Detection   |   Walker & Car Detection Using Cascade Classifier

• Bayesian Inference   |   Pixel Classification

• TensorFlow   |   MLP     Model     MNIST Test     CIFAR10 Test   |  

• TensorFlow   |   CNN     Model     MNIST Test     CIFAR10 Test   |  

• TensorFlow   |   CNN     Model (via tf.estimator)     MNIST Test   |  

• TensorFlow   |   RNN     Model     MNIST Test     CIFAR10 Test   |  

• TensorFlow   |   RNN     Model (via tf.estimator)     MNIST Test   |  

• PyTorch   |   MLP     Model     MNIST Test     CIFAR10 Test   |  

• PyTorch   |   CNN     Model     MNIST Test     CIFAR10 Test   |  

• PyTorch   |   RNN     Model     MNIST Test     CIFAR10 Test   |  

• MXNet   |   CNN     Model     MNIST Test     CIFAR10 Test   |  

• MXNet   |   RNN     Model     MNIST Test     CIFAR10 Test   |  

• Autoencoder

  • TensorFlow   |   Stacked Autoencoder (weights-tied)     Model     MNIST Test   |  

  • TensorFlow   |   Denoising Autoencoder     Model     MNIST Test   |  

  • TensorFlow   |   Sparse Autoencoder     Model     MNIST Test   |  

  • TensorFlow   |   Variational Autoencoder     Model     MNIST Test   |  

  • TensorFlow   |   Conv2D Autoencoder (weights-tied)     Model     MNIST Test     CIFAR10 Test   |  

  • PyTorch   |   Stacked Autoencoder (weights-tied)     Model     MNIST Test   |  

  • PyTorch   |   Denoising Autoencoder     Model     MNIST Test   |  

  • PyTorch   |   Sparse Autoencoder     Model     MNIST Test   |  

  • PyTorch   |   Variational Autoencoder     Model     MNIST Test   |  

  • PyTorch   |   Conv2D Autoencoder (weights-tied)     Model     MNIST Test     CIFAR10 Test   |  

• Generative Adversarial Network

  • TensorFlow   |   DCGAN     Model     MNIST Test     Result   |   Conditional Model     MNIST Test   |  

  • PyTorch   |   DCGAN     Model     MNIST Test   |  

  • MXNet   |   DCGAN     Model     MNIST Test   |  

• Python   |   Q-Learning     Model     CartPole Test   |  

• Python   |   Sarsa     Model     CartPole Test   |  

• TensorFlow   |   Policy Gradient     Model     CartPole Test   |  

• PyTorch   |   Policy Gradient     Model     CartPole Test   |  

• Python   |   Apriori     Model     MovieLens Test   |  

• Python   |   Collborative Filtering   |   MovieLens     User-based Model     Test   |  

• TensorFlow   |   Matrix Factorization     Model     MovieLens Test   |  

• 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   |  

• TensorFlow   |   K Nearest Neighbors     Model     MNIST Test   |  

• TensorFlow   |   K-Means     Model     MNIST Test   |  

• TensorFlow   |   Random Forest     Model     MNIST Test   |  

• Python   |   Bagging     Model     Test   |  

• Python   |   Adaboost     Pseudocode     Model     Test   |  

• Python   |   Random Forest     Model     Test   |  

• TensorFlow   |   RNN     Model     Test     Preview   |  

• PyTorch   |   RNN     Model     Test   |  

• MXNet   |   RNN     Model     Test   |  

• Counting   |   Scala API     Python API   |  

• Averaging   |   Scala API     Python API   |  

• Minimum   |   Scala API     Python API   |  

• Word Count   |   Scala API     Python API   |  

• Basics