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  • av Sunil Patel
    526,-

    Sunil Patel, un adev¿rat pasionat al buc¿t¿riei indiene, v¿ poart¿ într-o c¿l¿torie epic¿ a gusturilor ¿i aromelor autentice ale Indiei cu cartea sa, "Buc¿t¿ria Indian¿: Arome Exotice ¿i Pove¿ti de Gust."Aceast¿ carte v¿ introduce în universul captivant al gastronomiei indiene, dezv¿luind secretele g¿titului cu ingrediente exotice ¿i arome pline de mister. Chef Sunil Patel v¿ împ¿rt¿¿e¿te nu doar re¿ete tradi¿ionale, ci ¿i povestea cultural¿ ¿i istoric¿ din spatele fiec¿rui preparat.De la curry-uri parfumate ¿i biryani colorate la deserturi decadente precum gulab jamun ¿i jalebi, ve¿i înv¿¿a arta autentic¿ a buc¿t¿riei indiene. Cartea include, de asemenea, sfaturi esen¿iale privind utilizarea corect¿ a condimentelor ¿i tehnicile de g¿tit specifice acestei buc¿t¿rii uimitoare.Cu "Buc¿t¿ria Indian¿: Arome Exotice ¿i Pove¿ti de Gust," ve¿i explora bog¿¿ia gastronomiei indiene ¿i ve¿i înv¿¿a cum s¿ preg¿ti¿i preparate cu adev¿rat remarcabile. Aceast¿ carte v¿ va transforma într-un buc¿tar cu adev¿rat pasionat de aromele ¿i culturile Indiei.Indiferent dac¿ sunte¿i un novice în arta g¿titului indian sau un maestru experimentat în buc¿t¿ria indian¿, aceast¿ carte v¿ va inspira s¿ creäi experien¿e culinare autentice ¿i memorabile.

  • av Sunil Patel
    1 406,-

    This book is the out come from the personnel's who have their foot in microbiology science last two decades. It's a collection of almost a dozen of sister concerned disciplines in microbiology. It includes more than 6900 terms related to microbiology. This book will become and essential book to all who have some bearing with microbiology and fields like mycology, bacteriology, virology, microbe-biotechnology, parasitology etc.

  • - Learn how to build NLP applications with Deep Learning (English Edition)
    av Sunil Patel
    336,-

    Learn how to redesign NLP applications from scratch. Key FeaturesGet familiar with the basics of any Machine Learning or Deep Learning application. Understand how does preprocessing work in NLP pipeline. Use simple PyTorch snippets to create basic building blocks of the network commonly used in NLP. Get familiar with the advanced embedding technique, Generative network, and Audio signal processing techniques.DescriptionNatural language processing (NLP) is one of the areas where many Machine Learning and Deep Learning techniques are applied. This book covers wide areas, including the fundamentals of Machine Learning, Understanding and optimizing Hyperparameters, Convolution Neural Networks (CNN), and Recurrent Neural Networks (RNN). This book not only covers the classical concept of text processing but also shares the recent advancements. This book will empower users in designing networks with the least computational and time complexity. This book not only covers basics of Natural Language Processing but also helps in deciphering the logic behind advanced concepts/architecture such as Batch Normalization, Position Embedding, DenseNet, Attention Mechanism, Highway Networks, Transformer models and Siamese Networks. This book also covers recent advancements such as ELMo-BiLM, SkipThought, and Bert. This book also covers practical implementation with step by step explanation of deep learning techniques in Topic Modelling, Text Generation, Named Entity Recognition, Text Summarization, and Language Translation. In addition to this, very advanced and open to research topics such as Generative Adversarial Network and Speech Processing are also covered. What you will learnLearn how to leveraging GPU for Deep Learning Learn how to use complex embedding models such as BERT Get familiar with the common NLP applications Learn how to use GANs in NLP Learn how to process Speech data and implementing it in Speech applications Who this book is forThis book is a must-read to everyone who wishes to start the career with Machine learning and Deep Learning. This book is also for those who want to use GPU for developing Deep Learning applications.Table of Contents1. Understanding the basics of learning Process2. Text Processing Techniques3. Representing Language Mathematically4. Using RNN for NLP5. Applying CNN In NLP Tasks6. Accelerating NLP with Advanced Embeddings7. Applying Deep Learning to NLP tasks8. Application of Complex Architectures in NLP9. Understanding Generative Networks10. Techniques of Speech Processing11. The Road AheadAbout the Authors Sunil Patel has completed his master s in Information Technology from the Indian Institute of Information technology-Allahabad with a thesis focused on investigating 3D protein-protein interactions with deep learning. Sunil has worked with TCS Innovation Labs, Excelra, and Innoplexus before joining to Nvidia. The main areas of research were using Deep Learning, Natural language processing in Banking, and healthcare domain. Sunil started experimenting with deep learning by implanting the basic layer used in pipelines and then developing complex pipelines for a real-life problem. Apart from this, Sunil has also participated in CASP-2014 in collaboration with SCFBIO-IIT Delhi to efficiently predict possible Protein multimer formation and its impact on diseases using Deep Learning. Currently, Sunil works with Nvidia as Data Scientist III.LinkedIn Profile: https: //www.linkedin.com/in/linus1/Read mo

  • av Sunil Patel & Himanshu Barot
    696,-

  • av Sunil Patel, Himanshu Barot & Keyur Darji
    696,-

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