Download Machine Learning & Self-Driving Cars: Bootcamp with Python

What you would learn in Machine Learning & Self-Driving Cars: Bootcamp with Python course?

Are you interested in Machine Learning or Self-Driving Cars (i.e., Tesla)? This course is designed ideal for you!

This course was designed by a highly skilled Data Scientist specialist in Autonomous Vehicles to impart my knowledge and assist you in understanding how autonomous vehicles function effortlessly.

Each topic is discussed in three levels:

• Introduction: The subject will be discussed, and the initial thoughts about the subject will be gathered.

• Workshops: Practical, where we'll learn by doing

• Optional Deep dive: diving deep into maths to grasp the topic

What tools are we going to use to teach?

• Python is a definite and flexible programming language on the planet that can be used for everything from websites and databases to Deep Neural Networks; all can be accomplished with Python.

• Python libraries include matplotlib Numpy, OpenCV sci-kit-learn, keras ... (those libraries allow the potential of Python endless)

• Webots is a powerful simulator that can be free and open-source yet offers a variety of scenarios for simulation (Self-Driving Cars, drones, robotic arms, quadrupeds, and production lines ...)

Who are these courses for?

• All levels: no prerequisite knowledge, and there is an area that will show you how to code using Python

• Mathematics/logic: High school level is sufficient to grasp all things!

Sections:

• [Optional[Optional Python sections What you can do to program using Python, and how to make use of the essential libraries

• Control Theory: Control Systems are the glue that holds all engineering fields

  • If you're primarily interested in ML, it is possible to look at the introduction section. However, you must be aware that the very first Neural Networks were significantly in the hands of CT. CT

• Computer Vision: teaches a computer to recognize and learn about key concepts in Neural Networks.

• Introduction to Machine Learning of critical concepts, road sign classification

• Collision Avoidance: So far, we've employed cameras; in this article, we'll learn the ways the lidar and radar sensors can be employed in self-driving vehicles and make use of them to avoid collisions and path planning

  • Help us understand the differences between Tesla and other automobile companies as Tesla does not use radar sensors.

• Deep learning: We will apply all the concepts we've seen previously in a CV in ML, and CA, introduction to neural networks, and Behavioural Cloning

Content of the Course:

• Learn to use Machine Learning algorithms to develop a Self-Driving Car from scratch
• Simulate a self-driving car in a real-world setting with various methods (Computer Vision Convolution Neural Networks, ...)
• Learn the way Self Driving Cars work (sensors and actuators and speed control). ...)
• Find out about Computer Vision in a practical method, beginning with simple examples until you're capable of creating an algorithm that can drive a self-driving car.
• A gentle intro to Machine Learning, all the essential concepts are explained easy-to-understand and straightforward.
• Discuss why Deep Learning is so powerful and how it can be used to make your car behave like an actual human (Behavioural Cloning)
• Code Deep Convolutional Neural Neural Networks using Keras (the most well-known library)
• Develop, train and test different models, from traditional Machine Learning to Deep Neural Networks
• How do I write code in Python beginning at the beginning
• Python libraries: NumPy, Sklearn (Scikit-Learn), Keras, OpenCV, Matplotlib

Download Machine Learning & Self-Driving Cars: Bootcamp with Python from below links NOW!