PyTorch is an open-source machine-learning library, mostly used for computer vision and natural language processing in Python. It was developed by Facebook AI (Artificial Intelligence) Research Lab. It is software released under the Modified BSD License.

So, if you looking for a place you can get started with PyTorch. This is the place where you can get a complete PyTorch guide.

This page will briefly guide you through basic to expert-level PyTorch topics. But before that let us get started with PyTorch.

## PyTorch Tutorial For Beginners

The PyTorch is built based on Python which supports the calculation of tensors on GPU. PyTorch is the most recommended library for deep learning and artificial intelligence.

- What is PyTorch and how to use it
- PyTorch Save Model – Complete Guide
- Cross Entropy Loss PyTorch
- Adam optimizer PyTorch with Examples
- PyTorch nn linear + Examples
- PyTorch Load Model + Examples
- PyTorch Batch Normalization
- PyTorch Tensor to Numpy
- Keras Vs PyTorch – Key Differences
- PyTorch MSELoss – Detailed Guide
- PyTorch Pretrained Model
- PyTorch Early Stopping + Examples
- PyTorch Model Eval + Examples

By the end of this section, you will get a clear idea of What is PyTorch and how to install and get started with PyTorch.

## PyTorch Tutorial For Deep Learning

After understanding how to get started with PyTorch, let us move to the next phase where we understand PyTorch Tutorial for deep learning.

Now, PyTorch is the most recommended library for deep learning and artificial intelligence.

Deep learning is a subgroup of machine learning, which is basically a neural network with three or more layers.

Additionally, this tutorial will also illustrate Deep Neural Networks with PyTorch. And discuss various examples which will help you get a better understanding of the topics.

- PyTorch Dataloader + Examples
- PyTorch Logistic Regression
- PyTorch Binary Cross Entropy
- PyTorch Model Summary – Detailed Tutorial
- PyTorch MNIST Tutorial
- PyTorch fully connected layer
- PyTorch RNN – Detailed Guide
- PyTorch Activation Function [With 11 Examples]
- PyTorch Numpy to Tensor [With 11 Examples]
- PyTorch Leaky ReLU – Useful Tutorial
- PyTorch Linear Regression [With 7 Useful Examples]
- Jax Vs PyTorch [Key Differences]
- PyTorch Hyperparameter Tuning
- PyTorch nn Conv2d [With 12 Examples]
- PyTorch Reshape Tensor – Useful Tutorial
- PyTorch Add Dimension [With 6 Examples]

## Learning PyTorch with Examples

PyTorch is easy to use and has efficient memory usage, dynamic computational graph, flexibility, and creating coding feasible which increases the processing speed.

So, in this PyTorch section, we will discuss different types of functions. Moreover, here we also look at multiple examples.

This is the complete list of the tutorials that will help you get better with PyTorch.

- PyTorch Conv1d [With 12 Amazing Examples]
- Introduction to PyTorch Lenet
- PyTorch View Tutorial [With 11 Examples]
- PyTorch Conv3d – Detailed Guide
- How to squeeze a tensor in PyTorch
- PyTorch Flatten + 8 Examples
- How to use PyTorch Full() Function
- Create PyTorch Empty Tensor
- PyTorch Stack Tutorial + Examples
- How to use PyTorch Cat function
- How to use PyTorch Polar
- PyTorch Resize Images
- PyTorch Softmax [Complete tutorial]
- PyTorch TanH
- PyTorch nn Sigmoid tutorial with example