Raspberry Pi Deep Learning From Ground Up™

Welcome to the  Raspberry Pi Deep Learning From Ground Up™ course. We are going to embark on a very exciting journey together. We are going to learn how to build deep neural networks from scratch on our Raspberry Pi. We shall begin by learning the basics of deep learning with practical code showing each of the basic building blocks that end up making a giant deep neural network. All of this on our Raspberry, both training and inference.As we begin to deal with large datasets we shall start training our neural networks on our computers and then deploying  the trained models on our Raspberry Pi. Due to the limited memory and processing power of Raspberry Pi we shall learn methods for quantizing our models before deploying them on our resource constrained Raspberry without compromising the accuracy of our models.We shall also learn how to thoroughly take advantage of deep learning libraries such as Keras and Tensorflow .By the end of this course you will be able to build neural networks from scratch without libraries, be able to master quantization methods for deploying neural networks on Raspberry Pi, be able to build  deep learning applications for Image Classification, be able to build  deep learning applications for object recognition, be able to use Keras and Tensorflow, and so much more.If you are new to machine learning and deep learning, this course is for you. The course starts from the very basic building block of neural networks and teaches you how to build your own neural network using pure python code before we move on to see how to use readily available libraries.If you already have some experience with deep learning and want to see how to deploy models on Raspberry Pi you can also join this course. This course gives an in-depth training on the design methodology