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    Jupyter Notebook
  • Created almost 3 years ago
  • Updated over 2 years ago

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Repository Details

In this repository I've saved the files and functions required for an automatic conversion of SBML models into Bond Graphs (BGs)

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Tune_Optimize_backpropagation

Tuning the back propagation by changing the batch size, learning rate, and optimizer.
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BondGraphTools_Sample_Circuits

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Modularity_Branching_Vessel_Functions

Changes have been made to split the whole function into sub-functions
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EGFR_MAPK

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flatmapToCellmlAndJson

A Jupyter Notebook to generate a CellML file for the selected structures in the Generic Cell Flatmap
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RNN-stock-price-predict

Using an RNN network to predict the stock price based on a given trend.
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LSTM_Forecasting_Loads

Using LSTM to find the patterns in data and forecast the future data
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Annotated_BG_CellML_Modules_Merging_SemGen

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Modularity_Branching_Vessel

A function for connecting any number of "branching vessels" together via BondGraphTools
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Modularity_Reactions

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17

DCmotor

The antenna drive system
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LSTM_Embedding_spam_classification

Using Embedding & LSTM to classify texts to spam/ham.
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Deep_learning_Tune_Optimize

Setting up a configuration function to tune & optimize the Neural Networks.
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static_website_Jlab

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Cardiac_AP_3_channels

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Overfitting_Fix_ANN

Manage overfitting in neural networks by Regularization & Dropout
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Regresion_DecisionTree

Using Decision Trees for regression.
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Jupyter_website

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Na_K_ATPase_pump

Na+/K+ ATPase Pump model originally created by Michael Pan in CellML format. The equivalent BGT model is provided in this repository
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Niloofar-Sh

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Classification_DecisionTree

Using Decision Trees for classification.
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Data_labeling_Snorkel

Using Snorkel in Python to label a dataset of text messages as "Ham" or "Spam".
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Tune_Optimise_ANN_root_cause_analysis

Setting up a configuration function to tune & optimize the Neural Networks.
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