Hi, I'd like to propose the following talk. Thanks for the consideration.
Title: Apache MXNet 2.0: Bridging Deep Learning and Machine Learning Abstract: Deep learning community has largely evolved independently from the prior community of data science and machine learning community in NumPy. While most deep learning frameworks now provide NumPy-like math and array library, they differ in the definition of the operations which creates a steeper learning curve of deep learning for machine learning practitioners and data scientists. This creates a chasm not only in the skillsets of the two different communities, but also hinders the exchange of knowledge. The next major version, 2.0, of Apache MXNet (incubating) seeks to bridge the fragmented deep learning and machine learning ecosystem. It provides NumPy-compatible programming experiences and simple enhancements to NumPy for deep learning with the new Gluon 2.0 interface. The NumPy-compatible array API also brings the advances in GPU acceleration, auto-differentiation, and high-performance one-click deployment to the NumPy ecosystem. Thanks, Sheng --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
