Today's episode is on Python's most popular auto-differentiation library, PyTorch, and how you can use it to design, train and deploy deep neural nets, including LLMs. Acclaimed PyTorch instructor Luka Anicin is our guide.

Luka:

Is one of Udemy’s all-time bestselling instructors on A.I.; over 500,000 students have taken his courses.
His latest course, available exclusively at SuperDataScience.com, is called “PyTorch: From Zero to Hero”.
CEO of full-lifecycle A.I. consultancy Datablooz.
Holds a Bachelor’s in Computer Science, a Master’s in Data Science and is nearing completion of his PhD in Applied A.I.

Today’s episode will probably appeal most to hands-on practitioners like data scientists, software developers and ML engineers.

In it, Luka details:

What the popular Python library PyTorch is for.
Why you would select PyTorch over TensorFlow or Scikit-learn.
The tensor building blocks PyTorch provides for designing, training and deploying state-of-the-art deep neural networks, including Large Language Models (LLMs).
His top tips for accurate and efficient deep learning.
Guidance on PyTorch portfolio projects.
Real-world PyTorch case-studies from his experience leading an A.I. consultancy.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.