What you would learn in Deep learning using Tensorflow Lite on Raspberry Pi course?
The rating is for the OLD edition of this class. Updates to the projects and methods of explaining are what you're going to enjoy :)
Course Workflow
This course is designed for mobile robots that have the result of a two-wheel differential drive that has the wheel. We will First create the robot by using 3D printed components. The entire electronics will be explained to make good connections.
Raspberry Pi 4is is going to be the motor of this robotic. ROS2 simple and foxy are both expected to be employed in this course. WiFi communication between laptops with Raspberry Pi can be accomplished.
We will be looking at the issue of image information transmission as well as optimization of bandwidth to support our computer vision-based projects.
Sections:
ROS2 Workspace Setup for Raspberry Pi
Robots and Drivers are built and driven using Joystick
QR Maze Solving with OpenCV
Line Following Simulation and Real Robot
AI Surveillance Robot using Tensorflow Lite
The outcomes of this course
Custom Workspace
Custom Python Packages
Launch files
Custom Mobile Robots
ROS 2 Robot and Simulation integration
RVIZ, along with Gazebo Simulation Fundamentals
Computer Vision with ROS 2 with OPENCV
Deep Neural Networks on ROS 2 ROS 2 Nodes
The Software Requirements
Content of the Course:
- Create Your own AI Projects
- Raspberry Pi 4-based Robot for Computer Vision
- Neural Network to classify your Voice
- Convolution Network Creation - Custom Convolution Network Creation
Download Deep learning using Tensorflow Lite on Raspberry Pi from below links NOW!
