Visual Introduction to PyTorch
3 days ago
- #PyTorch
- #Machine Learning
- #Neural Networks
- PyTorch is a popular open-source deep learning framework developed by Meta AI, now part of the Linux Foundation.
- Tensors in PyTorch are specialized data containers for numerical data, similar to arrays but with additional functionalities.
- PyTorch offers various tensor initialization functions like torch.rand(), torch.randn(), torch.ones(), etc., each serving different purposes.
- Data in machine learning must be numerical; non-numerical data like words or images must be converted to numerical representations.
- PyTorch provides over 100 pre-defined tensor operations, including basic arithmetic, aggregations, and activation functions.
- Autograd in PyTorch automatically computes gradients, essential for training neural networks via backpropagation.
- A simple neural network model was built to predict house prices, demonstrating data preparation, model training, and evaluation.
- The model's performance was evaluated using metrics like MAE and MAPE, highlighting the importance of feature quality in machine learning.