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Link Examples

It is recommended to use after updating to the latest version(0.10.4).
​Spiral Pattern Classification​
Classification of 2D spiral-distributed data using Pytorch framework
Notebook Example : Spiral Pattern Classification​
spiral_classification.ipynb
777KB
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​Iris Data EDA and Modelling​
Basic exploratory data analysis (EDA) and modelling of iris data using Scikit-Learn library
Notebook Example : Iris Data EDA and Modelling​
iris_data_eda_and_modeling.ipynb
102KB
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​Titanic Data EDA and Modelling​
Various EDA and ensemble modelling of titanic data using Scikit-Learn library
Notebook Example : Titanic Data EDA and Modelling​
titanic_data_eda_and_modeling.ipynb
414KB
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​Image Generation using Variational Autoencoder​
MNIST image generation test with variational autoencoder (VAE) using Pytorch framework
Notebook Example : Image Generation using Variational Autoencoder​
image_generation_using_variational_autoencoder.ipynb
286KB
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​Image Restoration using Denoising Autoencoder​
Restoring corrupted MNIST images with denoising autoencoder using Pytorch framework
Notebook Example : Image Restoration using Denoising Autoencoder​
image_restoration_using_denoising_autoencoder.ipynb
510KB
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​MNIST Image Classification using CNN​
Classification of MNIST images with convolutional neural network (CNN) and fully-connected network (FCN) being compared using Pytorch framework
Notebook Example : MNIST Image Classification using CNN​
mnist_image_classification_using_cnn.ipynb
152KB
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​Using XGBoost for scikit-learn datasets​
Modelling of diabetes data for regression, classificaion, cross-validation, and hyperparameter searching using Scikit-Learn and XGBoost library
Notebook Example : Using XGBoost for scikit-learn datasets​
using-xgboost-for-scikit-learn-datasets.ipynb
18KB
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​Text Data Classification using RNN​
Text classification with RNN using Pytorch library
Notebook Example : Text Data Classification using RNN​
text_data_classification_using_rrn.ipynb
102KB
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​Deep Q-Network Reinforcement Learning for CartPole Environment​
​Deep Q-Network Reignforcement Learning (RL) for CartPole environment using Pytorch and OpenAI-Gym frameworks
Notebook Example : Deep Q-Network Reinforcement Learning for CartPole Environment​
deep q-network reinforcement learning for cartpole environment.ipynb
166KB
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Last modified 10mo ago

Link Examples

​Spiral Pattern Classification​

​Iris Data EDA and Modelling​

​Titanic Data EDA and Modelling​

​Image Generation using Variational Autoencoder​

​Image Restoration using Denoising Autoencoder​

​MNIST Image Classification using CNN​

​Using XGBoost for scikit-learn datasets​

​Text Data Classification using RNN​

​Deep Q-Network Reinforcement Learning for CartPole Environment​

Spiral Pattern Classification

Iris Data EDA and Modelling

Titanic Data EDA and Modelling

Image Generation using Variational Autoencoder

Image Restoration using Denoising Autoencoder

MNIST Image Classification using CNN

Using XGBoost for scikit-learn datasets

Text Data Classification using RNN

Deep Q-Network Reinforcement Learning for CartPole Environment