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Learn from scratch on how to create augmented reality apps using Vuforia 7 and Unity SDs.

About This Video: Together we will build a strong foundation in AR in Unity SDK with this training for beginners. This course will enable you to:

• Get started in Unity and how to download the Vuforia SDK.
• Create a simple AR app with a floating cube.
• Once you have mastered the basics we go ahead and create multiple targets in Augmented Reality.
• Create virtual buttons to add interactivity to your AR apps.
• Display Video on a physical wall.
• Leverage the Leap Motion Controller to create a pinch drawing app in AR. (Really Cool!)
• Implement Vuforia's smart terrain algorithm to detection objects in Real-Time!
• Detect Cylindrical Target Objects and animate markers.

In Detail: Do you want to learn the new augmented reality in Unity SDK? Are you not satisfied with poor tracking algorithms and the limitations of the ARtoolkit or other AR SDK's? Or are you new to Vuforia 7 SDK? This course will teach you all the fundamentals of augmented reality in the shortest time so that you can get started developing your own augmented reality apps. This class covers these capabilities, including getting started, simple and multiple target detection, smart terrain as well as leap motion integration. You will learn all the fundamentals through practice as you follow along with the training.

Applications of augmented reality:

- AR business cards
- AR Gaming
- Entertainment
- Medical
- Military
- Industrial and domestic maintenance
- Navigation
- Advertising and promotional content.

Step into the world of PyTorch to create deep learning models with the help of real-world examples.

About This Video: Learn to use PyTorch Open Source Deep Learning framework Dive into specific Deep Learning concepts using real-world projects. Build and train neural networks to make them more efficient.

In Detail: PyTorch is a Deep Learning framework that is a boon for researchers and data scientists. It supports Graphic Processing Units and is a platform that provides maximum flexibility and speed. With PyTorch, you can dynamically build neural networks and easily perform advanced Artificial Intelligence tasks. The course starts with the fundamentals of PyTorch and how to use basic commands. Next, you’ll learn about Convolutional Neural Networks (CNN) through an example of image recognition, where you’ll look into images from a machine perspective. The next project shows you how to predict character sequence using Recurrent Neural Networks (RNN) and Long Short Term Memory Network (LSTM). Then you’ll learn to work with autoencoders to detect credit card fraud. After that, it’s time to develop a system using Boltzmann Machines, where you’ll recommend whether to watch a movie or not. We’ll continue with Boltzmann Machines, where you’ll learn to give movie ratings using AutoEncoders. In the end, you’ll get to develop and train a model to recognize a picture or an object from a given image using Deep Learning, where we’ll not only detect the shape, but also the color of the object. By the end of the course, you’ll be able to start using PyTorch to build Deep Learning models by implementing practical projects in the real world. So, grab this course as it will take you through interesting real-world projects to train your first neural nets.