Online learning portal Udacity launched its first 36-week "nanodegree" course for self-driving car engineering last year. There's a new, introductory course available now as well, focused on bringing students with minimal programming into the larger program. Even better, Udacity has partnered with Lyft (which has self-driving plans of its own) to provide scholarships to the intro course in order to increase diversity to the program. Lyft says that people "from all backgrounds and perspectives" should have the opportunity to contribute to the future of transportation in the form of self-driving cars. "Diversity is crucial for creating solutions that serve everyone, and ridesharing is for everyone," the company writes on its website.

Welcome to this course: Deep Learning - Learn Convolutional Neural Networks. Deep Learning has made some huge and significant contributions and it's one of the mostly adopted techniques in order to drive insights from your data nowadays. Convolutional neural networks have gained a special status over the last few years as an especially promising form of deep learning. Rooted in image processing, convolutional layers have found their way into virtually all subfields of deep learning, and are very successful for the most part. Convolutional Neural Networks are very similar to ordinary Neural Networks: they are made up of neurons that have learnable weights and biases.

Description: Learn how to Visualize Data with MATLAB in 2D, 3D, 4D, 5D and create animated plots with tens of projects and examples!

A new degree program at Carnegie Mellon University and an online data science training course at MIT are focused on arming those in the workforce with new skills. This complimentary document comprehensively details the elements of a strategic IT plan that are common across the board – from identifying technology gaps and risks to allocating IT resources and capabilities. You forgot to provide an Email Address. This email address doesn't appear to be valid. This email address is already registered.

About this course: Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems. This course is the second in a sequence of three.

In the past year, flying cars have gone from LOL, to maybe a real thing, to a booming industry raking in VC cash and churning out sweet renderings of an aerial future. The chance to trigger the next great transportation revolution has drawn in big companies, like Airbus and Uber, big names, like Google's Larry Page, and naturally, a horde of startups. They all believe the proliferation of vertical takeoff and landing (or VTOL) aircraft, which combine the best features of helicopters and planes, can make traveling throughout and between cities not just faster, but maybe cheaper and greener. AI expert Sebastian Thrun thinks the idea will only climb higher, especially once these aircraft can fly themselves, and he wants to help make it happen. "I see a future where everybody flies at least once a day," he says.

Night driving in an autonomous vehicle designed by Udacity, an online training service that specializes in high-tech vocations. Sebastian Thrun, the original leader of Google's self-driving car project, is going to help rideshare company Lyft staff up its autonomous vehicle team with training through Udacity, his high-tech vocational service. And if robot cars weren't enough, he's creating the first academic program for those wanting to design so-called flying cars. Lyft will sponsor 400 scholarships over the next year for qualified candidates to complete Udacity's online self-driving car "nanodegree" program, which certifies them to work with companies struggling to find engineering talent in that field. Along with finding people for its new Level 5 Engineering Center, Lyft wants the scholarships help attract a more diverse range of people to work on autonomous vehicles, said Chief Strategy Officer Raj Kapoor.

When buying any of my courses, I also give you free coupons to the rest of my courses. Just send me a message after enrolling. Pay one course, get 5!! Linear regression is the primary workhorse in statistics and data science. Its high degree of flexibility allows it to model very different problems. We will review the theory, and we will concentrate on the R applications using real world data (R is a free statistical software used heavily in the industry and academia).

Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. It can be hard to get started with machine learning, particularly as new frameworks like TensorFlow start to gain traction across enterprise companies. TensorFlow is an open source software library for numerical computation using data flow graphs. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. This Learning Path begins by covering a mastery on Python with a deep focus on unlocking Python's secrets.

Wouldn't it be great if an Android app could see and understand its surroundings? Can you imagine how much better its user interface could be if it could look at its users and instantly know their ages, genders, and emotions? Well, such an app might seem futuristic, but it's totally doable today. With the IBM Watson Visual Recognition service, creating mobile apps that can accurately detect and analyze objects in images is easier than ever. In this tutorial, I'll show you how to use it to create a smart Android app that can guess a person's age and gender and identify prominent objects in a photograph.