Have you found it difficult to deploy neural networks on mobile devices and IoT devices? Have you ever found it too slow to train neural networks? This course is a deep dive into efficient machine learning techniques that enable powerful deep learning applications on resource-constrained devices. Topics cover efficient inference techniques, including model compression, pruning, quantization, neural architecture search, and distillation; and efficient training techniques, including gradient compression and on-device transfer learning; followed by application-specific model optimization techniques for videos, point cloud, and NLP; and efficient quantum machine learning. Students will get hands-on experience implementing deep learning applications on microcontrollers, mobile phones, and quantum machines with an open-ended design project related to mobile AI.
In the config.bib file: NK 80200000 00C00000 RAMIMAGE ;for 48M appRAM RAM 80E00000 03000000 RAM [color=#FF0000]FLASH 92000000 00100000 RESERVED[/color] What is the reserved FLASH memory segment used f
[align=left]Regarding the point of "via cover oil" and "via window", many customers often ask what this means when placing an order. Now, Jieduobang explains this issue as follows: [/align][align=left
Today's high-tech market requires more capacity and more reliable performance of wireless technology, especially low-cost and low-power wireless communication with relatively low data rates. These typ
[i=s]This post was last edited by littleshrimp on 2017-10-19 12:28[/i] [font=微软雅黑][size=5]Complete the SensorTile sound source localization code. All calculation codes are available. STM32L476 calcula
Recently, when I was adjusting F2812 to implement the CANOpen protocol, I found a strange problem. When reading the CAN message data registers MDL and MDH of F2812, the reading was 0, as shown below.