Autonomous Vehicles: Instructional Materials


Autonomous Cars: Deep Learning and Computer Vision in Python

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The automotive industry is experiencing a paradigm shift from conventional, human-driven vehicles into self-driving, artificial intelligence-powered vehicles. Self-driving vehicles offer a safe, efficient, and cost effective solution that will dramatically redefine the future of human mobility. Self-driving cars are expected to save over half a million lives and generate enormous economic opportunities in excess of $1 trillion dollars by 2035. The automotive industry is on a billion-dollar quest to deploy the most technologically advanced vehicles on the road. As the world advances towards a driverless future, the need for experienced engineers and researchers in this emerging new field has never been more crucial.


The Complete Self-Driving Car Course - Applied Deep Learning

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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. 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.


Math for Machine Learning

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From self-driving cars and recommender systems to speech and face recognition, machine learning is the way of the future. Would you like to learn the mathematics behind machine learning to enter the exciting fields of data science and artificial intelligence? There aren't many resources out there that give simple detailed examples and that walk you through the topics step by step. This ebook not only explains what kind of math is involved and the confusing notation, it also introduces you directly to the foundational topics in machine learning. This book will get you started in machine learning in a smooth and natural way, preparing you for more advanced topics and dispelling the belief that machine learning is complicated, difficult, and intimidating.


Dip your toes into AI with these online courses for Google Cloud

Mashable

AI systems have led to improvements in a broad spectrum of industries, including medicine and business, and sprouted new technologies like voice assistants (can you imagine what your day would be like without Alexa?) and self-driving cars. If you're curious about learning more and want to dip your toes in a bit -- whether out of sheer fascination or for business and job hunting purposes -- the Google Cloud Mastery Bundle can serve as your primer to the world of AI. While Google Cloud has yet to reach the heights of what Amazon Web Services and Microsoft Azure have achieved, it sure is promising. After all, its litany of cloud computing services runs on the same infrastructure as Google Search and YouTube, two of the most frequently digital products used today. Undoubtedly, learning its inner workings can prove to be useful if you're running a business or carving out a career in tech.


Ensemble Machine Learning in Python: Random Forest, AdaBoost

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In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning. Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning. Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.


Data Science: Supervised Machine Learning in Python

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In recent years, we've seen a resurgence in AI, or artificial intelligence, and machine learning. Machine learning has led to some amazing results, like being able to analyze medical images and predict diseases on-par with human experts. Google's AlphaGo program was able to beat a world champion in the strategy game go using deep reinforcement learning. Machine learning is even being used to program self driving cars, which is going to change the automotive industry forever. Imagine a world with drastically reduced car accidents, simply by removing the element of human error.


Math for Machine Learning: Open Doors to Data Science and Artificial Intelligence

#artificialintelligence

From self-driving cars and recommender systems to speech and face recognition, machine learning is the way of the future. Would you like to learn the mathematics behind machine learning to enter the exciting fields of data science and artificial intelligence? There aren't many resources out there that give simple detailed examples and that walk you through the topics step by step. This ebook not only explains what kind of math is involved and the confusing notation, it also introduces you directly to the foundational topics in machine learning. This book will get you started in machine learning in a smooth and natural way, preparing you for more advanced topics and dispelling the belief that machine learning is complicated, difficult, and intimidating.


Machine Learning Coursera

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Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.


MIT faculty approves new urban science major

MIT News

Urban settlements and technology around the world are co-evolving as flows of population, finance, and politics are reshaping the very identity of cities and nations. Rapid and profound changes are driven by pervasive sensing, the growth and availability of continuous data streams, advanced analytics, interactive communications and social networks, and distributed intelligence. At MIT, urban planners and computer scientists are embracing these exciting new developments. The rise of autonomous vehicles, sensor-enabled self-management of natural resources, cybersecurity for critical infrastructure, biometric identity, the sharing or gig economy, and continuous public engagement opportunities through social networks and data and visualization are a few of the elements that are converging to shape our places of living. In recognition of this convergence and the rise of a new discipline bringing together the Institute's existing programs in urban planning and computer science, the MIT faculty approved a new undergraduate degree, the bachelor of science in urban science and planning with computer science (Course 11-6), at its May 16 meeting.


Ever wanted to teach yourself AI? Here's 22 online classes from Stanford to MIT

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For some us, AI is kind of an iffy proposition. To many, it is nebulous enough to seem like it might replace us or our jobs. And the harbingers of this sea change aren't exactly affirming: every other week in the news, self-driving smart cars keep crashing, with injuries and sometimes fatalities. AI generally doesn't seem to be that well-received in mass media, either, like in movies like Minority Report or TV shows like Westworld. Because of all this, the public perception of AI might be on the negative side.