Building a Self-Driving Car with JavaScript: Neural Networks and Machine Learning
Learn how to build a self-driving car using JavaScript, neural networks, and machine learning. Covers physics-based controls, lane control, border detection, and traffic interactions.
00:00:00 Learn how to build a self-driving car simulation using JavaScript. No libraries used. Covers neural networks and modern JavaScript techniques.
๐๐ This course teaches you how to build a self-driving car simulation using JavaScript and neural networks.
๐ฃ๏ธ๐ You will learn how to implement physics, create a road, and simulate sensors for the car.
๐ง ๐ฌ The course also covers neural networks and optimization algorithms for the self-driving car.
00:21:59 Self-Driving Car with JavaScript Course - Neural Networks and Machine Learning. Implementing physics-based controls, rotation, and movement using JavaScript canvas.
The video discusses the implementation of a self-driving car using JavaScript and neural networks.
The video covers topics such as friction, speed control, and left and right controls of the car.
The video also explains the implementation of the road and different lanes for the car to maneuver.
00:43:55 This video demonstrates how to create a self-driving car using JavaScript, neural networks, and machine learning. It covers topics like lane control, border detection, and adding sensors to the car.
โ๏ธ The car's lane count is adjusted using the minimum function to ensure it stays within the screen boundaries.
๐ฃ๏ธ The road object is updated to include borders, which can be customized and used for collision detection.
๐๐ก A sensor is added to the car to detect road borders, and its functionality is explained.
01:05:58 This YouTube video explains how to create a self-driving car using JavaScript, neural networks, and machine learning. The video covers topics such as array mapping, finding the minimum offset, drawing readings, detecting collisions, and adding traffic.
๐ The code uses array map to create a new array called offsets, which represents the elements' offsets.
๐ The minimum offset is found using the math minimum method and the spread operator is used to pass multiple values.
๐ง The code demonstrates how to implement collision detection using polygons and intersection code.
01:28:07 This video covers the creation of a self-driving car with JavaScript using neural networks and machine learning. It explains how to disable sensors, update traffic interactions, and implement sensors that can detect road borders and other cars. The video also introduces the concept of artificial neural networks and their connection to the car's controls.
๐ The video focuses on implementing self-driving car functionalities, such as disabling sensors for a dummy car and preventing damage in traffic interactions.
๐ง The second part of the video introduces artificial neural networks, which are computing systems inspired by biological neural networks in our brain. It explains how neurons work together and the importance of weights and biases in determining neuron firing.
๐ป The video concludes by discussing the implementation of neural networks in JavaScript. It explains the concept of levels in a neural network and how to code feed forward algorithms to compute output values.
01:50:12 Learn how to create a self-driving car using JavaScript and neural networks. Connect the car's sensors to the neural network to make decisions on whether to go forward, backward, left, or right.
๐ The self-driving car uses neural networks and machine learning to make decisions.
๐ง The neural network receives input from car sensors and outputs commands for the car to go forward, backward, left, or right.
๐ The video demonstrates the process of connecting the neural network to the car controls and visualizing the network in action.
02:12:12 Learn to build a self-driving car using JavaScript and neural networks. Explore mutation, fitness functions, and optimization techniques to improve car performance.
๐ The video discusses how to implement a self-driving car using JavaScript and neural networks.
๐ง The concept of storing and retrieving the car's brain from local storage is explained.
๐ The video demonstrates how to create clickable buttons with emojis using HTML and CSS.
๐งฌ The process of mutating the neural network is demonstrated to improve the performance of the car.
๐ Different fitness functions are discussed and how they can impact the behavior of the car.
๐ฅ The addition of more cars and complex scenarios is explored to test the car's abilities.
๐น๏ธ The video concludes by suggesting the possibility of further courses and projects related to neural networks and JavaScript.
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