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Mitchell-Mirano/sorix

🏡 Sorix
📚 Learn
Examples
API Reference

Sorix

Mitchell-Mirano/sorix

🏡 Sorix
📚 Learn
📚 Learn
- Basics
  Basics
- Data Handling
  Data Handling
  - Dataset and DataLoader
- Layers
  Layers
  - Linear
  - BatchNorm1d
  - ReLU
  - Sigmoid
  - Tanh
  - Dropout
  - Module
- Loss
  Loss
- Optimizers
  Optimizers
  - SGD
  - SGDMomentum
  - RMSprop
  - Adam
  - Optimizer Comparison
  - Optimizer
- Preprocessing
  Preprocessing
- Model Selection
  Model Selection
  - Train-Test Split
- Metrics
  Metrics
  - Regression Metrics
  - Classification Metrics
Examples
Examples
- Preprocessing
- Linear Regression
- Logistic Regression
- Clustering
  Clustering
  - K-Means
    K-Means
    
    Iris Dataset
    
    Random Dataset + GPU
- Neural Network
  Neural Network
  - Regression
  - Classification
    Classification
    
    Classification Binary
    
    Classification Multiclass
    
    Iris Dataset
    
    MNIST Dataset
- Benchmarks
  Benchmarks
  - MNIST Benchmark Parity: Sorix vs. TensorFlow vs. PyTorch
- PDE
  PDE
  - Physics-Informed Neural Networks (PINNs)
API Reference
API Reference
- _version
- autograd
- clustering
  clustering
  - k_means
- cuda
  cuda
  - cuda
- cupy
  cupy
  - cupy
- metrics
  metrics
  - metrics
- model_selection
  model_selection
  - train_test
- nn
  nn
  - init
  - layers
  - loss
  - net
- optim
  optim
  - optim
- preprocessing
  preprocessing
- tensor
- utils
  utils
  - data
    
    data
    
    dataloader
    
    dataset
  - math
  - utils

Table of contents

nn

🏡 Sorix
API Reference
nn

Index

sorix.nn ¶

Neural network components including layers, containers, and loss functions.

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