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

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

Apr 17, 2025 - 06:13 Updated: May 4, 2025 - 14:43

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

Deep Learning on ARM Processors – From the Ground Up, name of a training course, deep learning with the use of the processor, the ARM industry. In this period, to a fun trip together we’ll go where the recall, we took the how neural networks deep foundation work on the microcontroller, the build. The work starts this course by learning the basics of deep learning with code, practical, would be that all the blocks in the Builder Base that led to the construction of a neural network to massive they are, it will show. All these are what is education and what is inference on the microcontroller our will be done. In this period, the beneficial use of library such as Keras and Tensorflow on the side of library famous Deep Learning for the microcontroller, such as CMSIS-NN ,CubeMX.AI and TensorFlow Lite also taught.

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

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

Specifications volume:

Publisher: Udemy
Instructor: Israel Gbati and EmbeddedExpertIO
Language: English
Training level: basic to advanced
Number of courses: 118
Duration Time: 19 hours and 16 minutes

Course contents:

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 Deploying the MNIST Handwriting Recognition Model on ARM MCUs
13. Set Up
14. Python Essentials
15. CubeMX Primer
16. Closing