Udemy – Deep Learning on ARM Processors – From Ground Up™ 2020-9

Description

Deep Learning on ARM CPUs – From the Ground Up, name of a training course, deep learning with CPU usage, ARM industry. In this period, for a fun journey together, we will go to where the recall, we took the operation of neural networks on the microcontroller, the construction. The work begins this course by learning the basics of deep learning with code, practice, it would be that all the blocks of the Builder Base that led to the construction of a massive neural network were, it will be seen . All of this is the microcontroller education and inference that we are going to do. In this period, the beneficial use of libraries such as Keras and Tensorflow alongside famous Deep Learning libraries for the microcontroller, such as CMSIS-NN, CubeMX.AI and TensorFlow Lite also taught.

In the Deep Learning on ARM Processors – From the Ground Up course, learn:

Build a neural network from the ground up without using library download
Methodically, Master quantization for expanding neural networks on microcontrollers upload
Build firmware for diagnosis of human activity (Human Activity Recognition – HAR) like walking, jogging and…
Build deep learning firmware to recognize handwriting
Build Deep Learning Firmware for Acoustic Scene Classification (ASC)
You will be able to talk about the deep learning will give.

Specification volume:

Publisher: Udemy
Instructor: Israel Gbati and EmbeddedExpertIO
French language
Level of training: basic to advanced
Number of courses: 118
Duration: 19 hours and 16 minutes

Course content :

1. Introduction
2. Building Blocks of Neural Networks
3. Introduction to Neural Network (Part 2)
4. Logistic regression
5. Deep Neural Networks
6. Improve neural networks with regularization techniques
7. Build a logistic regression model
8. Build deep neural networks from scratch
9. Convolutional Neural Networks (CNN)
10. CubeMX 5 and CubeIDE Primer
11. CubeMX AI
12. Case Study Deploying MNIST Handwriting Recognition Model on ARM Microcontrollers
13. Configure
14. Python Essentials
15. CubeMX Primer
16. Closure