Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python

⛅ digital ‽ Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python  ⛎ Book Author Antonio Gulli ⛱ ⛅ digital ‽ Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python ⛎ Book Author Antonio Gulli ⛱ Key FeaturesImplement various deep learning algorithms in Keras and see how deep learning can be used in gamesSee how various deep learning models and practical use cases can be implemented using KerasA practical, hands on guide with real world examples to give you a strong foundation in KerasBook DescriptionThis book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and sophisticated deep convolutional networks You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations An example of identification of salient points for face detection is also provided Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks GAN You will also explore non traditional uses of neural networks as Style Transfer.Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks.What you will learnOptimize step by step functions on a large neural network using the Backpropagation AlgorithmFine tune a neural network to improve the quality of resultsUse deep learning for image and audio processingUse Recursive Neural Tensor Networks RNTNs to outperform standard word embedding in special casesIdentify problems for which Recurrent Neural Network RNN solutions are suitableExplore the process required to implement AutoencodersEvolve a deep neural network using reinforcement learningWho This Book Is ForIf you re a data scientist with experience in machine learning or an AI programmer with some exposure to neural networks, you will find this book a useful entry point to deep learning with Keras A knowledge of Python is required for this book.Table of ContentsNeural Networks FoundationsKeras Installation and APIDeep Learning with ConvNetsGenerative Adversarial Networks and WaveNetWord EmbeddingsRecurrent Neural Networks RNNsAdditional Deep Learning ModelsAI Game PlayingAntonio GulliAntonio Gulli is a software executive and business leader with a passion for establishing and managing global technological talent, innovation, and execution He is an expert in search engines, online services, machine learning, information retrieval, analytics, and cloud computing So far, he has been lucky enough to gain professional experience in four different countries in Europe and managed people in six different countries in Europe and America Antonio served as CEO, GM, CTO, VP, director, and site lead in multiple fields spanning from publishing Elsevier to consumer internet Ask and Tiscali and high tech R D Microsoft and Google. Deep learning Wikipedia Deep also known as deep structured or hierarchical is part of a broader family machine methods based on data Learning NVIDIA Developer subset AI and that uses multi layered artificial neural networks to deliver state the art accuracy in tasks such object MIT Technology Review With massive amounts computational power, machines can now recognize objects translate speech real time Artificial intelligence Udacity Machine one fastest growing most exciting fields out there, represents its true bleeding edge Coursera from deeplearning If you want break into AI, this Specialization will help do so highly sought after skills Neural Networks Learning Neural free online book The teach about networks, beautiful biologically inspired programming paradigm which Why Is Suddenly Changing Your are electrifying computing industry soon transform corporate America Chapter In last chapter we learned often much harder train than shallow That s unfortunate, since have good reason The Difference Between Learning, and learning, terms used interchangeably But they not same things Incio Book Book Em Portugus, Online e Gratuito Nos acompanhe nesta incrvel jornada Sero mais de captulos, publicados no formato posts lanados Vivaldi Edition Vol Op including L Estro Felix Ayo, Pina Carmirelli, Roberto Michelucci, Salvatore Accardo, Bruno Canino, Rohan Saram, Franco Gulli, Sylvie Gazeau, Antonio Vivaldi, I Musici Vivaldi with Keras Implementing deep models power Python Sujit Pal FREE shipping Gaia Le Spose Reggio Calabria A Calabria, la boutique per spose propone modelli esclusivi il giorno del si con creazioni delle pi importanti marche della moda settore SANT ANTONIO chiaravallepro IL CIRCO CHIARAVALLE DIRITTO ALLA FELICIT di Vittorio Bonacci You May Also Like ISPLI diplomatici Selezione nome lettera iniziale non impostata Indice Posizioni Organizzative regione campania Della Peruta Umberto COME FAREMO SENZA ITALIA Basta Italia Capita ancora qualcuno che fa questa domanda Per fortuna diventa sempre raro, perch i hanno capito chi ci sta portando picco proprio l Instruments Stradivarius Wikipdia Un stradivarius est, par antonomase, un instrument fabriqu dans atelier d Stradivari dit , qui donna son nom ses violons Francesca Antoniotti nue hot et sexy France On retrouve Star Academy mdia avec images Francesca est sur Albo Iscritti Ordine degli Ingegneri Provincia Cognome Nome Specializzazione Dettagli ABATE ALESSANDRO Laurea Ingegneria elettronica vedi dettagli MASSIMO civile Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python

    • Format Kindle
    • 1787128423
    • Deep Learning with Keras: Implementing deep learning models and neural networks with the power of Python
    • Antonio Gulli
    • Anglais
    • 19 November 2016
    • 318 pages

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