Machine Learning using Arm community

Arm is at the heart of the world’s most advanced digital products. Our technology enables the creation of new markets and transformation of industries and society. We design scalable, energy efficient-processors and related technologies to deliver the intelligence in applications ranging from sensors to servers, including smartphones, tablets, enterprise infrastructure and the Internet of Things.Arm provides training on a wide range of Arm technology topics, written and delivered by the world’s most experienced Arm technology trainers. With face-to-face and online options available, Arm Training is flexible too.

<H3 CLASS="MsoNoSpacing">Summary:</H3>
This training topic covers essential information on Arm’s IP solutions for optimizing Machine Learning (ML) applications for Arm hardware. The topic introduces Arm’s solutions for implementing ML on Android and Linux platforms with our suite of ML software tools and how they relate to corresponding Arm hardware. 
The topic provides an overview of Arm Compute Library, an open source toolkit for implementing ML applications on Arm’s Mali GPU’s. 
Because Arm’s ML solution is optimized for Convolutional Neural Networks (CNNs), the course also provides an introduction to (CNNs) and how they operate. Finally, the course has some tutorials for you to follow that demonstrate how to run some ML example applications on Arm hardware, including Arm Cortex-A, Arm Cortex-M, and Arm Mali GPUs.
<H3 CLASS="MsoNoSpacing">Prerequisites:</H3>
<UL>
<LI> A basic understanding of neural networks</LI>
</UL>
<H3 CLASS="MsoNoSpacing">Audience:</H3>
The course is relevant to anyone who wants to start targeting Machine Learning applications on Arm hardware IP.
<H3 CLASS="MsoNoSpacing">Delivery Method:</H3>
<UL>
<LI>Online</LI>
</UL>
<H3 CLASS="MsoNoSpacing">Length: </H3>
<UL>
<LI>1 hour</LI>
</UL>
<H3 CLASS="MsoNoSpacing">Modules:</H3>
<H4 CLASS="MsoNoSpacing">Arm IP and Machine Learning</H4>
<UL>
<LI>Intro to Arm's machine learning IP</LI>
<LI>Arm SW Library - Arm NN</LI>
<LI>Arm SW Library - ACL and CMSIS-NN</LI>
<LI>Arm ML Hardware</LI>
</UL>
<H4 CLASS="MsoNoSpacing">Introduction to Machine Learning</H4>
<UL>
<LI>Introducing Convolutional Neural Networks (CNNs)</LI>
<LI>How does convolution work?</LI>
<LI>Convolution - stride and padding</LI>
<LI>Convolution - channels</LI>
<LI>Convolutional Neural Networks (CNNS) in action</LI>
<LI>Transfer learning</LI>
</UL>
<H4 CLASS="MsoNoSpacing">Introduction to Object Detection</H4>
<UL>
<LI>Introduction to Object Detection</LI>
<LI>Bounding boxes</LI>
<LI>Sliding windows</LI>
<LI>Region proposals</LI>
<LI>Landmark detection</LI>
<LI>YOLO - You Only Look Once</LI>
<LI>Anchor boxes</LI>
</UL>
<H4 CLASS="MsoNoSpacing">OpenCL Concepts</H4>
<UL>
<LI>Intro to OpenCL</LI>
<LI>OpenCL Execution Model</LI>
<LI>OpenCL example</LI>
</UL>
<H4 CLASS="MsoNoSpacing">How-to run ML tasks on Arm hardware </H4>
<UL>
<LI>Overview</LI>
<LI>Image recognition on Arm Cortex-M with CMSIS-NN</LI>
<LI>Running and profiling Arm NN on the HiKey 960 (Arm Cortex-A) </LI>
<LI>Running and profiling Arm NN on the HiKey 960 (Arm Mali GPU)</LI>
</UL>
Language: This course is presented in English.
Delivery Method: Bitesized video content 
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Machine Learning using Arm community

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