Python Deep Learning Projects

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 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