Presented By O’Reilly and Intel AI
Put AI to work
April 10-11, 2018: Training
April 11-13, 2018: Tutorials & Conference
Beijing, CN

深度学习工程师, 梅卡曼德


Grace Lee is the author of Technical Analysis and Practice in TensorFlow and the founder of the TensorFlow communication community. She is active in the technical community and is known for her answers to programming questions. Grace has deep experience with TensorFlow, source code analysis and application in different areas, processing images, social text data emotional analysis, and data mining. She participated in the the autopilot two-dimensional perception system hackathon competition based on deep learning. Previously, she was a deep learning engineer at Baidu.


16:2017:00 Thursday, April 12, 2018
Secondary topics:  深度学习(Deep Learning)
李嘉璇 (梅卡曼德)
随着神经网络算法在图像、语音等领域都大幅度超越传统算法,但在应用到实际项目中却面临两个问题:计算量巨大及模型体积过大,不利于移动端和嵌入式的场景;模型内存占用过大,导致功耗和电量消耗过高。因此,如何对神经网络模型进行优化,使尽可能不损失精度的情况下,能减少模型的体积,并且计算量也降低,就是我们将深度学习在更广泛地场景下应用时要解决的问题。本次讲解主要着眼于在安防、工业物联网、智能机器人等设备,需要解决图像、语音场景下深度学习的加速问题,减小模型大小及计算量,构建高性能神经网络模型。 Read more.