: 
Published 08/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 36 lectures (4h 14m) | Size: 3.3 GB
Power up your Embedded projects with Artificial Intelligence in Python using TF Lite
What you'll learn
Build your own AI Projects
Raspberry Pi 4 based Robot for Computer Vision
Neural Network to classify your Voice
Custom Convolution Network Creation
Requirements
Basic Python Programming
Raspberry pi 4
Basic Electronics Understanding
Power Bank
Description
Course Updated ROS Kinetic to ROS 2 Foxy
Rating is for OLD version of this course , New update to projects and way of explanation is what you are going to love :)
Course Workflow
This Course is for mobile robot which is a 2 wheel differential drive with a caster . We will First build the robot using 3D printed parts. All electronics is going to be explained for proper connections .
Raspberry Pi 4 is going to be main brain for this robot . ROS2 foxy and humble both are going to be utilized using this course . WiFi Communication between laptop and Raspberry Pi will be done .
We will look into image data transmission and bandwidth optimization for our computer vision based projects .
Sections
ROS2 Workspace Raspberry pi Setup
Robot Building and Driving with Joystick
QR Maze Solving using OpenCV
Line Following Real and Simulation Robot
AI Surveillance Robot using Tensorflow Lite
Outcomes After this Course : You can create
Custom Workspace
Custom Python Packages
Launch files
Custom Mobile Robots
ROS 2 Robot and Simulation integration
RVIZ and Gazebo Simulation Fundamentals
Computer Vision with ROS 2 using OPENCV
Deep Neural Networks on ROS 2 based Nodes
Software Requirements
Ubuntu 22.04
ROS 2 Foxy
Motivated mind for a huge programming Project
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Before buying take a look into this course GitHub repository
Who this course is for
Developers
Electrical Engineers
Artificial Intelligence Enthusiasts
Homepage
https://www.udemy.com/course/deep-learning-using-tensorflow-lite-on-raspberry-pi/Download from UploadCloud
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