Autonomous Vehicles: Instructional Materials


Machine Learning K-Nearest Neighbors (KNN) Algorithm In Python

#artificialintelligence

Machine Learning is one of the most popular approaches in Artificial Intelligence. Over the past decade, Machine Learning has become one of the integral parts of our life. It is implemented in a task as simple as recognizing human handwriting or as complex as self-driving cars. It is also expected that in a couple of decades, the more mechanical repetitive task will be over. With the increasing amounts of data becoming available there is a good reason to believe that Machine Learning will become even more prevalent as a necessary element for technological progress.


Self-driving car expert offer online degree in flying cars

Daily Mail

Self-driving car pioneer Sebastian Thrun has shifted his gaze to the skies, as his Silicon Valley online school Udacity launches what it calls the first'nanodegree' in flying car engineering. With companies from Airbus and Amazon to Uber throttling up development of their own autonomous aerial vehicles, Thrun believes'in a few years time, this will be the hottest topic on the planet.' As usual, Thrun intends to be on the cutting edge of this emerging technology. Self-driving car pioneer Sebastian Thrun has shifted his gaze to the skies, as his Silicon Valley online school Udacity launches what it calls the first'nanodegree' in flying car engineering You can now learn how to build a flying car in just four months thanks to a new $400 (£295) online course. Online education provider Udacity, also owned by Sebastian Thrun, has announced two new'nanodegrees' teaching users to make driverless or flying vehicles.


MIT 6.S094: Deep Learning for Self-Driving Cars

@machinelearnbot

This class is an introduction to the practice of deep learning through the applied theme of building a self-driving car. It is open to beginners and is designed for those who are new to machine learning, but it can also benefit advanced researchers in the field looking for a practical overview of deep learning methods and their application. MIT 6.S094: Deep Learning for Self-Driving Cars is a course on a cutting-edge research area. Support for this course was genorously provided by the companies whose logos are shown below. And none of it would be possible without the great community of bright young minds at MIT and beyond.


Machine Learning For Absolute Beginners Udemy

#artificialintelligence

If you've ever wanted Jetsons to be real, well we aren't that far off from a future like that. If you've ever chatted with automated robots, then you've definitely interacted with machine learning. From self-driving cars to AI bots, machine learning is slowly spreading it's reach and making our devices smarter. Artificial intelligence is the future of computers, where your devices will be able to decide what is right for you. Machine learning is the core for having a futuristic reality where robot maids and robodogs exist.


Learn how to use that new drone you got as a gift

Mashable

Heads up: All products featured here are selected by Mashable's commerce team and meet our rigorous standards for awesomeness. If you buy something, Mashable may earn an affiliate commission. So you got a drone as gift over the holidays, or maybe you purchased one on sale during Cyber Monday. If you can't seem to figure out how to fly the thing, let alone take selfies with it, maybe you need some training wheels. Thankfully, there's a course called Drones: Learn Aerial Photography and Videography Basics on sale right now that will help you maximize your new gadget's potential.


Robotics: Aerial Robotics Coursera

@machinelearnbot

About this course: How can we create agile micro aerial vehicles that are able to operate autonomously in cluttered indoor and outdoor environments? You will gain an introduction to the mechanics of flight and the design of quadrotor flying robots and will be able to develop dynamic models, derive controllers, and synthesize planners for operating in three dimensional environments. You will be exposed to the challenges of using noisy sensors for localization and maneuvering in complex, three-dimensional environments. Finally, you will gain insights through seeing real world examples of the possible applications and challenges for the rapidly-growing drone industry. Mathematical prerequisites: Students taking this course are expected to have some familiarity with linear algebra, single variable calculus, and differential equations.


Enterprise Machine Learning in a Nutshell (Repeat)

#artificialintelligence

Machine learning enables computers to learn from large amounts of data without being explicitly programmed to do so. We can already see how machine learning gives rise to new intelligent applications, from self-driving cars to intelligent assistants on our smartphones. Increasingly, businesses recognize the importance of using machine learning to transform their data assets into business value. However, many companies are unsure how machine learning can be applied to solve problems in an enterprise context. As the world's most relevant enterprise data is part of SAP's system and business network, SAP aspires to make all its enterprise solutions intelligent and help customers to leverage their data.


Nvidia looks to reduce AI training material through 'imagination'

ZDNet

Nvidia researchers have used a pair of generative adversarial networks (GANs) along with some unsupervised learning to create an image-to-image translation network that could allow for artificial intelligence (AI) training times to be reduced. In a blog post, the company explained how its GANs are trained on different data sets, but share a "latent space assumption" that allows for the generation of images by passing the image representation from one GAN to the next. "The use of GANs isn't novel in unsupervised learning, but the Nvidia research produced results -- with shadows peeking through thick foliage under partly cloudy skies -- far ahead of anything seen before," the company said. The benefits of this work could allow for network training to require less labelled data, it said. "For self-driving cars alone, training data could be captured once and then simulated across a variety of virtual conditions: Sunny, cloudy, snowy, rainy, nighttime, etc," Nvidia said.


Machine Learning & Artificial Intelligence: Crash Course Computer Science #34

#artificialintelligence

So we've talked a lot in this series about how computers fetch and display data, but how do they make decisions on this data? From spam filters and self-driving cars, to cutting edge medical diagnosis and real-time language translation, there has been an increasing need for our computers to learn from data and apply that knowledge to make predictions and decisions. This is the heart of machine learning which sits inside the more ambitious goal of artificial intelligence. We may be a long way from self-aware computers that think just like us, but with advancements in deep learning and artificial neural networks our computers are becoming more powerful than ever. Want to know more about Carrie Anne? https://about.me/carrieannephilbin


Machine Learning & Artificial Intelligence: Crash Course Computer Science #34

#artificialintelligence

So we've talked a lot in this series about how computers fetch and display data, but how do they make decisions on this data? From spam filters and self-driving cars, to cutting edge medical diagnosis and real-time language translation, there has been an increasing need for our computers to learn from data and apply that knowledge to make predictions and decisions. This is the heart of machine learning which sits inside the more ambitious goal of artificial intelligence. We may be a long way from self-aware computers that think just like us, but with advancements in deep learning and artificial neural networks our computers are becoming more powerful than ever. Want to know more about Carrie Anne? https://about.me/carrieannephilbin