PyTorch is on the rise as it is more Pythonic than other prominent deep learning web framework. This enables researchers and new developers to learn quickly and get started with neural networks in no time. Besides, anyone can assimilate the algorithms written in PyTorch due to its effective readability. This is one of the key reasons why it has now become a go-to language for deep learning initiatives for developers, researchers, and enterprises alike.
To help aspirants get better acquainted with this deep learning library, Analytics India Magazine has curated a list to assist you in getting your hand dirty in deep learning and innovating in the artificial intelligence landscape.
1. Deep Learning With PyTorch: A 60 Minute Blitz
What better way can one take other than learning from the PyTorch’s core team. This tutorial helps one get a quick understanding of the library and at the same time, train a small neural network to classify images. This tutorial has enough to attain knowledge about the convolutional neural network (CNN), loss function, training on both single and multiple GPUs, and more.
Following the 60 Minutes Blitz tutorial, there are other more advanced tutorials, but it can be overwhelming for a beginner. Consequently, aspirants should use this to get an idea rather than mastering PyTorch. Besides, the tutorial does not include videos, so if you are a novice stick to only the A 60 Minute Blitz.
2. Intro To Deep Learning With PyTorch
This course provides intro To Deep Learning With PyTorch for helping beginners in learning right from the basics of the library to the intermediate level. The course was made in collaboration with Facebook’s team. This makes it a sublime resource as one can learn from the team behind the development of PyTorch.
The course includes CNN, RNN, sentiment prediction, and deploying PyTorch models with Torch Script. Depending upon your proficiency in Python and machine learning knowledge, it can take from one to three month for learning and mastering PyTorch.
3. Deep Neural Networks With PyTorch
Offered by IBM through Coursera, the Deep Neural Networks With PyTorch comprises of tensor and datasets, different types of regression, shallow neural networks (NN), deep networks, and CNN.
Taught by Joseph Santarcangelo, Data Scientist at IBM, the course has received a rating of 4.5 by the leaners, thus making it a must-have course for beginners.
4. Deep Learning With Python And PyTorch
Instructed by the same person as in the above course, the Deep Learning With Python and PyTorch is a bit different. Unlike others, this course also teaches about Python libraries such as Pandas and NumPy before moving on to PyTorch. This helps in acquiring the necessary background for getting into deep learning techniques such as convolution, batch normalisation, and more.
5. Introduction To Deep Learning With PyTorch
Introduction To Deep Learning With PyTorch is a short course on deep learning from DataCamp. With this, aspirants can learn about learning to train, evaluate CNN, and improve accuracy. Since it is mostly focused on CNN, users will have to learn other techniques from several sources for getting familiar with the library before opting for self-learning through random searches.
6. PyTorch Tutorial For Deep Learning Lovers
This is a Kaggle kernel for learning the ropes for PyTorch. The kernel is has got more than 50 thousand views and have also received a lot of positive comments. It covers the basics of PyTorch, different regression techniques, ANN, CNN, and RNN. Beginners can start with this kernel as it is very informative and focused towards the new learners.
7. Practical Deep Learning For Coders
Fast.ai is built on top of PyTorch to help users learn and master deep learning. Practical Deep Learning For Coders is a complete deep learning course for beginners. However, if you are already familiar with deep learning, you can take Deep Learning From The Foundations, which is their advanced course.