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| File Name: | Machine Learning & Self-Driving Cars: Bootcamp with Python |
| Content Source: | https://www.udemy.com/course/machine-learning-self-driving-cars/ |
| Genre / Category: | Programming |
| File Size : | 3.7GB |
| Publisher: | udemy |
| Updated and Published: | July 29, 2023 |
Combine the power of Machine Learning, Deep Learning and Computer Vision to make a Self-Driving Car!
Interested in Machine Learning or Self-Driving Cars (i.e. Tesla)? Then this course is for you!
This course has been designed by a professional Data Scientist, expert in Autonomous Vehicles, with the goal of sharing my knowledge and help you understand how Self-Driving Cars work in a simple way.
Each topic is presented at three levels:
- Introduction: the topic will be presented, initial intuition about it
- Hands-On: practical lectures where we will learn by doing
- [Optional] Deep dive: going deep into the maths to fully understand the topic
What tools will we use in the course?
- Python: probably the most versatile programming language in the world, from websites to Deep Neural Networks, all can be done in Python
- Python libraries: matplotlib, OpenCV, numpy, scikit-learn, keras, … (those libraries make the possibilities of Python limitless)
- Webots: a very powerful simulator, which free and open source but can provide a wide range of simulation scenarios (Self-Driving Cars, drones, quadrupeds, robotic arms, production lines, …)
Who this course is for?
- All-levels: there is no previous knowledge required, there is a section that will teach you how to program in Python
- Maths/logic: High-school level is enough to understand everything!
Sections:
- [Optional] Python sections: How to program in python, and how to use essential libraries
- Computer Vision: teaches a computer how to see, and introduces key concepts for Neural Networks
- Machine Learning: introduction, key concepts, and road sign classification
- Collision Avoidance: so far we have used cameras, in this section we understand how radar and lidar sensors are used for self-driving cars, use them for collision avoidance, path planning
- Help us understand the difference between Tesla and other car manufacturers, because Tesla doesn’t use radar sensors
- Deep learning: we will use all the concepts that we have seen before in CV, in ML and CA, neural networks introduction, Behavioural Cloning
- Control Theory: control systems is the glue that stitches all engineering fields together
- If you are mainly interested in ML, you can only listen to the introduction for this section, but you should know that the initial Neural Networks were heavily influenced by CT
Who am I, and why am I qualified to talk about Self-driving cars?
- Worked in self-driving motorbikes, boats and cars
- Some of the biggest companies in the world
- Over 8 years experience in the industry and a master in Robotic & CV
- Always been interested in efficient learning, and used all the techniques that I’ve learned in this course
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