Neural Networks and Deep Learning

Ready to crank up a deep neural network to get your self-driving car pick up the kids from school? Want to add 'Neural Networks' and 'Deep Learning' to your LinkedIn profile? Well, hold on there... Before you embark on your epic journey into the world of deep learning, there is basic theory to march through first! Check out this exceptional bundle of 3 books... This bundle contains 3 books: Book 1: Neural Networks & Deep Learning: Deep Learning explained to your granny - A visual introduction for beginners who want to make their own Deep Learning Neural Network... What you will gain from this book: * A deep understanding of how Deep Learning works * A basics comprehension on how to build a Deep Neural Network from scratch Who this book is for: * Beginners who want to approach the topic, but are too afraid of complex math to start! * Two main Types of Machine Learning Algorithms * A practical example of Unsupervised Learning * What are Neural Networks? * McCulloch-Pitts's Neuron * Types of activation function * Types of network architectures * Learning processes * Advantages and disadvantages * Let us give a memory to our Neural Network * The example of book writing Software * Deep learning: the ability of learning to learn * How does Deep Learning work? * Main architectures and algorithms * Main types of DNN * Available Frameworks and libraries * Convolutional Neural Networks * Tunnel Vision * Convolution * The right Architecture for a Neural Network * Test your Neural Network * A general overview of Deep Learning * What are the limits of Deep Learning? * Deep Learning: the basics * Layers, Learning paradigms, Training, Validation * Main architectures and algorithms * Models for Deep Learning * Probabilistic graphic models * Restricted Boltzmann Machines * Deep Belief Networks Book2: Deep Learning: Deep Learning explained to your granny - A guide for Beginners... What's Inside? * A general overview of Deep Learning * What are the limits of Deep Learning? * Deep Learning: the basics * Layers, Learning paradigms, Training, Validation * Main architectures and algorithms * Convolutional Neural Networks * Models for Deep Learning * Probabilistic graphic models * Restricted Boltzmann Machines * Deep Belief Networks * Available Frameworks and libraries * TensorFlow Book 3: Blockchain Blueprint: The ultimate guide to understanding blockchain, cryptocurrencies, smart contracts and the future of money The current emerging innovation of this decade may be the connected world of computing relying on blockchain encryption. The attention given to this technology by global giant players suggests that it will become the operational philosophy of the economic system of the future, ranging across many industries. Blockchain can become the solution we needed for speeding up the economy and transactions in order to keep up with our multi-device connected world. In this book, high tech expert Pat Nakamoto answers your questions concerning the future of Blockchain technology along with addressing different major developments linked to it, like Smart Contracts, Fintech and Ethereum. Hit download. Now!