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

Description

Deep Learning on ARM Processors – From the Ground Up, name of a training course, Deep Learning using the processor, the ARM industry. During this time, we will go on a fun journey together, remembering how deep fundamentals of neural networks work on the microcontroller and how they are built. The work in this course begins with learning the basics of deep learning with code. In practice, it will be shown that all the blocks in the builder base that led to the construction of a neural network are too massive. All of this is what education is and what conclusions on the microcontroller we are going to do. This period also taught the beneficial use of libraries such as Keras and Tensorflow alongside the famous deep learning library for microcontrollers such as CMSIS-NN, CubeMX.AI and TensorFlow Lite.

What you will learn in the Deep Learning on ARM Processors – From the Ground Up course:

Build a neural network from scratch without using a library upload
Methodically, the master quantization for the expansion of neural networks can be uploaded to microcontrollers
Create firmware for Human Activity Recognition (HAR) diagnostics such as 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 deep learning.

Specifications Volume:

Publisher: Udemy
Teacher: Israel Gbati And EmbeddedExpertIO
Language: English
Training level: 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. Improving neural networks with regularization techniques
7. Building a logistic regression model
8. Building deep neural networks from scratch
9. Convolutional Neural Networks (CNN)
10. CubeMX 5 & CubeIDE Primer
11. CubeMX AI
12. Case study of deploying MNIST handwriting recognition model on ARM MCUs
13. Set up
14. Python Basics
15. CubeMX Primer
16. Graduation