This deep learning software is used by enterprises and developers to solve real-world, challenging problems, such as detecting respiratory diseases, accessing human rights info, etc. Companies like Airbnb, Coca-Cola, Google, Intel, Twitter, GE Healthcare, etc., use TensorFlow to make innovations....
in-depth learning became essential for machine learning practitioners and even for many software engineers. This book provides a wide range of role for data scientists and software engineers with experience in machine learning. You will start with the basics of deep learning and quickly move on to...
In traditional ML, the learning process is supervised, and the programmer must be extremely specific when telling the computer what types of things it should be looking for to decide if an image contains a dog or doesn't contain a dog. This is a laborious process calledfeature extraction, an...
types of data independently and then integrating the results in some master model, only one model is designed to receive data from all types and process them all to get the target output. This approach of learning and processing of data in a single model is called “End-to-end Learning.”...
Learn what deep learning is, what deep learning is used for, and how it works. Get information on how neural networks and BERT NLP works, and their benefits.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. - deepspeedai/DeepSpeed
Compare the top 11 deep learning frameworks and their features that play an integral part in Artificial Intelligence and Machine Learning.
On this page you can find the release notes of the MVTec Deep Learning Tool, including Early Adopter releases.
Deep Learning tutorial helps you learn about deep learning, how it is related to Machine Learning and AI. Also, learn about basics of Artificial Neural Networks.
The point of deep learning frameworks Easily build big computational graphs Easily compute gradients in computational graphs Run it all efficiently on GPU (wrap cuDNN, cuBLAS, etc) DL frameworks Pytorch大法好 TensorFlow First define the graph, and then run it many times. ...