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Md Abul,
Quantization is a valuable process in Deep Learning of mapping continuous values to a smaller set of discrete finite values.
In this talk, we will explore the different types of quantization techniques that can be applied to deep learning models. In addition, we will give an overview of the Neural Network Compression Framework (NNCF) and how it complements the OpenVINO™ toolkit to achieve outstanding performance.
What you’ll learn:
- The value of quantization and different types of quantization
- How to harness NNCF with the OpenVINO™ toolkit
- A Jupyter Notebook demonstrating a neural network graph before-and-after quantization with performance comparisons
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Adrian Boguszewski
AI Software Evangelist, Intel
Adrian is frequently a speaker at data science conferences, enjoys working with big data and creating solutions for big companies in Poland.
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Zhuo Wu
AI Software Evangelist, Intel
Zhuo is an AI evangelist at Intel focusing on OpenVINO toolkit. Her work ranges from deep learning technologies to 5G wireless communication technologies.
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