Introduction to PyTorch for Deep Learning

What is PyTorch?

PyTorch is a Python-based library that provides maximum flexibility and speed. We’ve found PyTorch to be as simple as working with NumPy! You’ll figure this out inside the course for yourself.

We highly recommend learning PyTorch right now - it is quickly becoming the framework of choice for deep learning practitioners. PyTorch will be adopted by the industry soon as well so get on board today!

Why should you learn PyTorch?

PyTorch is one of the most popular and upcoming deep learning frameworks that allows you to build complex neural networks. It is rapidly growing among the research community and companies like Facebook and Uber are using it as well.

Here is what Andrej Karpathy, head of AI at Tesla, has to say about PyTorch - “I've been using PyTorch a few months now and I've never felt better. I have more energy. My skin is clearer. My eyesight has improved.”

PyTorch vs. TensorFlow vs. Keras - which deep learning framework is the best?

This is a common question and a relevant one. There is no shortage of deep learning frameworks out there so which one should you choose?

There’s no one-size-fits-all approach here. Each deep learning framework has its own unique set of features which is why data scientists go for one over the other.

We recommend checking out this article on Analytics Vidhya to understand how PyTorch compares against the other deep learning frameworks like TensorFlow and Keras. This will help you settle the PyTorch vs. TensorFlow debate for sure!

What are the advantages of using PyTorch?

The main advantage of PyTorch is the imperative programming feature - which performs computations on your code as you are typing it, so debugging it is super easy! It is also much faster than NumPy and easy to learn too.

What are some challenges you might face when using PyTorch?

PyTorch is not meant to be an end-to-end deep learning framework and using it for production in the industry remains a challenge. It is also relatively newer than other deep learning frameworks and has only recently released its stable versions.

What kind of deep learning projects can you solve using PyTorch?

You can work on all sorts of deep learning projects using PyTorch! Here are a few examples:

• Handwritten Digit Classification
• Object and Image Classification
• Sentiment Text Classification
• Image Style Transfer, among others

You can check out the different datasets and projects to apply PyTorch on Analytics Vidhya’s DataHack platform.

Is PyTorch relevant in the industry?

Absolutely! While it’s still in its nascent stage, PyTorch is quickly becoming the go-to tool of choice for a lot of leading organizations. It’s flexible approach and easy-to-understand style have won over a lot of newcomers and industry veterans.

Do you need to know deep learning to learn PyTorch?

No! PyTorch is a framework - you do not need to know deep learning to learn how it works. It will of course help you to learn both PyTorch and deep learning - they both go hand-in-hand to be truly effective.

Make sure you check out our popular Computer Vision using Deep Learning course to dive in depth into this subject.

What kind of neural networks can you build using PyTorch?

PyTorch is an excellent framework for getting into actual machine learning and neural network building. In fact, in the course, we will be building a neural network from scratch using PyTorch. It is ideal for more complex neural networks like RNNs, CNNs, LSTMs, etc and neural networks you want to design for a specific purpose.

Which programming language works best with PyTorch?

As the name suggests, PyTorch is built on Python. The flexibility and ease- of understanding comes from Python as you’ll see in this Introduction to PyTorch for Deep learning course.