Build Your own Self Driving Car [Course -2]
Build Your own Self Driving Car [Course -2], available at $19.99, has an average rating of 4.4, with 37 lectures, based on 137 reviews, and has 852 subscribers.
You will learn about Learn How to Setup Raspberry Pi 3 for any IOT Projects Learn How to Setup Arduino UNO as a Slave micro-controller for any IOT Project Learn Image Processing using OpenCV4 for any Platform Learn Machine Learning & Train your own Image Classifier Learn How to Troubleshoot any Hardware & Software issues Most Important!! Learn to Design Embedded Product totally from scratch This course is ideal for individuals who are College or University student from Electronics/Electrical or Computer Engineering or relevant Diploma or Hobbyist interested in Machine Learning & Image Processing or Anybody Who wants to create Embedded IOT Project It is particularly useful for College or University student from Electronics/Electrical or Computer Engineering or relevant Diploma or Hobbyist interested in Machine Learning & Image Processing or Anybody Who wants to create Embedded IOT Project.
Enroll now: Build Your own Self Driving Car [Course -2]
Summary
Title: Build Your own Self Driving Car [Course -2]
Price: $19.99
Average Rating: 4.4
Number of Lectures: 37
Number of Published Lectures: 37
Number of Curriculum Items: 37
Number of Published Curriculum Objects: 37
Original Price: CA$24.99
Quality Status: approved
Status: Live
What You Will Learn
- Learn How to Setup Raspberry Pi 3 for any IOT Projects
- Learn How to Setup Arduino UNO as a Slave micro-controller for any IOT Project
- Learn Image Processing using OpenCV4 for any Platform
- Learn Machine Learning & Train your own Image Classifier
- Learn How to Troubleshoot any Hardware & Software issues
- Most Important!! Learn to Design Embedded Product totally from scratch
Who Should Attend
- College or University student from Electronics/Electrical or Computer Engineering or relevant Diploma
- Hobbyist interested in Machine Learning & Image Processing
- Anybody Who wants to create Embedded IOT Project
Target Audiences
- College or University student from Electronics/Electrical or Computer Engineering or relevant Diploma
- Hobbyist interested in Machine Learning & Image Processing
- Anybody Who wants to create Embedded IOT Project
“Machine Learning will change the lives of all of us. What is Machine Learning? It’s behind what makes self-driving cars a reality”
This unique course is a complete walk-through process to Design, Build and Program a Embedded IOT Project (Self driving Car). Everything is discussed with details and clear explanation. Whole Project is divided into 2 parts.
(Course – 2) Contents:
1. Stop Sign Detection (Published)
2. Object Detection (Published)
3. Traffic Light Detection (Published)
4. LED Dynamic Turn Indicator (Published)
(Course – 1) Previous Course
1. Learn to design complete hardware for self driving car
a. Learn to setup Master device ( Raspberry Pi ) for any project
b. Learn to setup Slave device ( Arduino UNO ) for any project
c. Learn to Establish Communication link between Master and Slave device
2. Learn Image Processing using OpenCV4
3. Learn to driver robot on road lanes
“Machine Learning will change the lives of all of us. What is Machine Learning? It’s behind what makes self-driving cars a reality”
Machine learning is important because it gives enterprises a view of trends in customer behavior and business operational patterns, as well as supports the development of new products. Many of today’s leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations. Machine learning has become a significant competitive differentiator for many companies
Course Curriculum
Chapter 1: Introduction to Machine Learning
Lecture 1: Basic Steps & Terminologies
Chapter 2: (Stop Sign) Neural Network Training
Lecture 1: Creating Stop sign
Lecture 2: C++ code to Capture & Save Images
Lecture 3: Capturing Positive Samples for Stop sign
Lecture 4: Capturing Negative Samples
Lecture 5: Cascade Training Software and Image Cropping
Lecture 6: Training of Haar Cascade Model for Stop Sign
Chapter 3: Stop Sign Detection on Raspberry Pi3
Lecture 1: Load (.xml) file in C++ Code
Lecture 2: Writing Image Classifier Program in C++
Lecture 3: Stop Sign Detection Testing
Lecture 4: Create Linear Equations to Calculate Distance
Lecture 5: Solve Linear Equations & Distance Testing
Chapter 4: Stop Sign Detection Testing
Lecture 1: C++ Programming in Raspberry Pi
Lecture 2: C++ Programming in Arduino UNO
Lecture 3: Final Testing (Stop Sign)
Chapter 5: (Obstacle) Neural Network Training
Lecture 1: Positive Sample for Object
Lecture 2: Extracting Positive samples for Object
Lecture 3: Cascade Training for Object Detection
Chapter 6: Obstacle Detection on Raspberry Pi3
Lecture 1: C++ Code to Detect Object
Lecture 2: Create Linear Equations to Calculate Distance (for Object)
Lecture 3: Solve Linear Equations & Distance Testing (for object)
Chapter 7: Obstacle Detection Testing
Lecture 1: Arduino Programming
Lecture 2: Lane Change Operation
Lecture 3: Final Testing (Object)
Chapter 8: Traffic Light Training
Lecture 1: Traffic Light Model
Lecture 2: Positive Sample for Red Light
Lecture 3: Negative Sample for Red Light
Lecture 4: Training Data
Lecture 5: Cascade Model for Red Light
Chapter 9: Traffic Light Detection
Lecture 1: Loading .XML File
Lecture 2: Linear Equations With Calibration
Lecture 3: Finding Actual Distance
Chapter 10: Traffic Light Testing
Lecture 1: Arduino Programming & Final Testing
Chapter 11: LED Dynamic Turn Signal Indicator
Lecture 1: Schematic Diagram
Lecture 2: Clock Circuit Build
Lecture 3: Indicator Circuit Build
Lecture 4: C++ Code to Control the indicators
Instructors
-
Rajandeep Singh
Embedded System Engineer
Rating Distribution
- 1 stars: 5 votes
- 2 stars: 5 votes
- 3 stars: 12 votes
- 4 stars: 43 votes
- 5 stars: 72 votes
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