TensorFlow, PyTorch, and JAX: Choosing a deep learning framework
Three widely used frameworks are leading the way in deep learning research and production today. Which one should you use?
Three widely used frameworks are leading the way in deep learning research and production today. Which one should you use?
Deep learning is solving challenging problems in industries as diverse as retail, manufacturing, and agriculture. These companies are leading the way.
From data preparation and training to model deployment, these start-ups offer state-of-the-art platforms for managing the entire machine learning lifecycle.
Look no further than these excellent free resources to master the development of deep learning models using PyTorch.
PyTorch is definitely the flavour of the moment, especially with the recent 1.3 and 1.4 releases bringing a host of performance improvements.
Couchbase might seem like a bit of an outsider in the world of NoSQL datastores. After all, MongoDB grabs most of the limelight, while Cassandra and HBase have sewn up most of the big data world, and Redis has pretty much supplanted Memcache as the key/value cache that people reach for by default. But Couchbase has not been sitting on the sidelines looking in. You might not know it from Hacker News, but the use of Couchbase Server has been growing steadily for the past couple of years.