The Complete Self-Driving Car Course - Applied Deep Learning [Video]

More Information
Learn
  • Learn to apply Computer Vision and Deep Learning techniques to build automotive-related algorithms
  • Understand, build and train Convolutional Neural Networks with Keras
  • Simulate a fully functional Self-Driving Car with Convolutional Neural Networks and Computer Vision
  • Train a Deep Learning Model that can identify between 43 different Traffic Signs
  • Learn to use essential Computer Vision techniques to identify lane lines on a road
  • Learn to build and train powerful Neural Networks with Keras
  • Understand Neural Networks at the most fundamental perceptron-based level
About

Self-driving cars have rapidly become one of the most transformative technologies to emerge. Fuelled by Deep Learning algorithms, they are continuously driving our society forward and creating new opportunities in the mobility sector. Deep Learning jobs command some of the highest salaries in the development world. This is the first, and only course which makes practical use of Deep Learning, and applies it to building a self-driving car, one of the most disruptive technologies in the world today. Learn & Master Deep Learning in this fun and exciting course with top instructor Rayan Slim. With over 28000 students, Rayan is a highly rated and experienced instructor who has followed a "learn by doing" style to create this amazing course. By the end of the course, you will have built a fully functional self-driving car fuelled entirely by Deep Learning. This powerful simulation will impress even the most senior developers and ensure you have hands on skills in neural networks that you can bring to any project or company.

This course will show you how to:

  • Use Computer Vision techniques via OpenCV to identify lane lines for a self-driving car.
  • Learn to train a Perceptron-based Neural Network to classify between binary classes.
  • Learn to train Convolutional Neural Networks to identify various traffic signs.
  • Train Deep Neural Networks to fit complex datasets.
  • Master Keras, a power Neural Network library written in Python.
  • Build and train a fully functional self-driving car to drive on its own!

All the code and supporting files for this course are available at: https://github.com/PacktPublishing/The-Complete-Self-Driving-Car-Course---Applied-Deep-Learning

Style and Approach

This is the first, and only course which makes practical use of Deep Learning, and applies it to building a self-driving car, one of the most disruptive technologies in the world today. This course is designed to take students with no programming/mathematics experience to accomplished Deep Learning developers.

Features
  • You'll go from beginner to Deep Learning expert
  • Your instructor will complete each task with you step by step on screen.
  • No experience required.
Course Length 17 hours 40 minutes
ISBN 9781838829414
Date Of Publication 3 Apr 2019
Anaconda Distribution – Mac
Anaconda Distribution – Windows
Text Editor
Outro
Intro to Keras
Keras Models
Keras – Predictions
Part 7 – Outro
Implementation
Section 13 – Conclusion

Authors

Rayan Slim

Rayan Slim - Teacher

Rayan is a full-time software developer based in Ottawa, Canada. He is the first ventured into development when working on a start-up. Since then, he has built countless web and mobile applications as a freelance developer, meanwhile expanding his repertoire and exploring new avenues in Robotics, Deep Learning & Data Analytics. In his free time, he loves to teach!

Jad Slim

Jad Slim - Data Science Entrepreneur

Jad studied mechanical engineering at the University of Ottawa. Jad also has experience in machine learning, computer vision, mathematical modeling, computer simulation, and intelligent systems. He has also developed many deep learning applications, and is currently pursuing an interest in autonomous machines. Skilled in deep learning libraries such as Tensorflow, Keras and MATLAB.

Amer Sharaf

Amer Sharaf - Developer

Amer is a full-time developer with a specialized interest in Artificial intelligence (AI). AI is now taking on more sophisticated roles that can truly amplify human capabilities. With a background in Mechanical Engineering and computer science, he has always looked for ways to use the power of AI to create practical solutions that revolutionize the way we live. He aims to make artificial intelligence more accessible to all students, no matter the skill level! 

Sarmad Tanveer

Sarmad Tanveer - Data Scientist

Sarmad has a deep passion for data science. He is a Mechanical Engineering graduate turned Data Scientist and had gained experience in the field while working on his very own startups. His main work focuses on creating predictive models using a combination of complex deep learning algorithms and sentiment analysis. He also has prior experience with deep learning fueled autonomous machines. In his spare time, he enjoys teaching courses and sharing his knowledge with all of you!