Python Deep Learning Projects : 9 Projects Demystifying Neural Network and Deep Learning Models for Building Intelligent Systems

Insightful projects to master deep learning and neural network architectures using Python and Keras Key Features Explore deep learning across computer vision, natural language processing (NLP), and image processing Discover best practices for the training of deep neural networks and their deployment Access popular deep learning models as well as widely used neural network architectures Book Description Deep learning has been gradually revolutionizing every field of artificial intelligence, making application development easier. Python Deep Learning Projects imparts all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each of these projects is unique, helping you progressively master the subject. You'll learn how to implement a text classifier system using a recurrent neural network (RNN) model and optimize it to understand the shortcomings you might experience while implementing a simple deep learning system. Similarly, you'll discover how to develop various projects, including word vector representation, open domain question answering, and building chatbots using seq-to-seq models and language modeling. In addition to this, you'll cover advanced concepts, such as regularization, gradient clipping, gradient normalization, and bidirectional RNNs, through a series of engaging projects. By the end of this book, you will have gained knowledge to develop your own deep learning systems in a straightforward way and in an efficient way What you will learn Set up a deep learning development environment on Amazon Web Services (AWS) Apply GPU-powered instances as well as the deep learning AMI Implement seq-to-seq networks for modeling natural language processing (NLP) Develop an end-to-end speech recognition system Build a system for pixel-wise semantic labeling of an image Create a system that generates images and their regions Who this book is for Python Deep Learning Projects is for you if you want to get insights into deep learning, data science, and artificial intelligence. This book is also for those who want to break into deep learning and develop their own AI projects. It is assumed that you have sound knowledge of Python programming Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub .. 1: BUILDING DEEP LEARNING ENVIRONMENTS 2: TRAINING NN FOR PREDICTION USING REGRESSION 3: WORD REPRESENTATION USING WORD2VEC 4: BUILDING AN NLP PIPELINE FOR BUILDING CHATBOTS 5: SEQUENCE-TO-SEQUENCE MODELS FOR BUILDING CHATBOTS 6: GENERATIVE LANGUAGE MODEL FOR CONTENT CREATION 7: BUILDING SPEECH RECOGNITION WITH DEEPSPEECH2 8: HANDWRITTEN DIGITS CLASSIFICATION USING CONVNETS 9: OBJECT DETECTION USING OPENCV AND TENSORFLOW 10: BUILDING FACE RECOGNITION USING FACENET 11: AUTOMATED IMAGE CAPTIONING 12: POSE ESTIMATION ON 3D MODELS USING CONVNETS 13: IMAGE TRANSLATION USING GANS FOR STYLE TRANSFER 14: DEVELOP AN AUTONOMOUS AGENT WITH DEEP R LEARNING 15: SUMMARY AND NEXT STEPS IN YOUR DEEP LEARNING CAREER Python Deep Learning Projects book will simplify and ease how deep learning works, and demonstrate how neural networks play a vital role in exploring predictive analytics across different domains. You will explore projects in the field of computational linguistics, computer vision, machine translation, pattern recognition and many more