Automatic Differentiation in Python and PyTorch

Check out Carl Osipov’s book Serverless Machine Learning in Action | 📚📚📚 To save 40% on this book use the Discount Code: twitosip40 📚📚📚 Deep dive into understanding automatic differentiation used by PyTorch autograd for deep learning with the help of Carl Osipov, who has spent over 15 years working on big data processing and machine learning in multi-core, distributed systems, such as service-oriented architecture and cloud computing platforms. “Serverless Machine Learning in Action: With PyTorch on AWS“ is a guide to bringing your experimental machine learning code to production using serverless capabilities from major cloud providers. You’ll start with best practices for your datasets, learning to bring VACUUM data-quality principles to your projects, and ensure that your datasets can be reproducibly sampled. Next, you’ll learn to implement machine learning models with PyTorch, discovering how to scale up your models