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Madaniyat. Madaniyatshunoslik
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Distributed Services with Go
Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and The Pragmatic Programmers, LLC was aware of a trademark claim, the designations have been printed in initial capital letters or in all capitals. The Pragmatic Starter Kit, The Pragmatic Programmer, Pragmatic Programming, Pragmatic Bookshelf, PragProg and the linking g device are trademarks of The Pragmatic Programmers, LLC. Every precaution was taken in the preparation of this book. However, the publisher assumes no responsibility for errors or omissions, or for damages that may result from the use of information (including program listings) contained herein. For our complete catalog of hands-on, practical, and Pragmatic content for software developers, please visit https://pragprog.com.
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TAEKVONDO NAZARIYASI VA USLUBIYATI
Ushbu o’quv qo’llanma tа’lim yo‘nаlishi 61010300 – Spоrt fаоliyati (faoliyat turlari bo‘yicha) ishlab chiqildi. O'quv qo'llanmada Taekvondo texnikasi va taktikasi turish holati va steplardan foydalanishda ishlash texnikasi, Taekvondo strategiyasi va taktikasi hamda taekvondo mashqlari, taekvondoda boshqaruvga oid mavzular berilgan. Ushbu o'quv qo'llanma taekvondo bo'yicha ixtisoslashgan jismoniy tarbiya fakultetlarining universitet talabalari, magistrantlari, shuningdek, o'smirlar sport maktablari va olimpiya zaxiralari kollejlari murabbiylari uchun mo'ljallangan.
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Deep_Learning_and_Convolutional_Neural_Networks_for_Medical_Imagwe
These types of large-scale annotated image datasets are, unfortunately, not available in medical image analysis tasks yet, even though improving medical imaging applications through deep neural network models and imaging data is highly valuable. This is partly explained by the fact that labels or annotations for medical image database are much harder or expensive to obtain.
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Spatial Analysis with R Statistics, Visualization, and Computational Methods
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Ўзбекистонда маънавият соҳасидаги ислоҳотлар: ривожланиш босқичлари эришилган натижалар ва истиқболи
Ушбу китоюда Ўзбекистонда маънавият соҳасидаги олиб борилаётган ислоҳотлар ва уларнинг босқичма босқич ривожланиши ҳақида маълумотлар келтирилган.
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Deep Neuro-Fuzzy Systems with Python
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Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. TinyML, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc. TinyML is a trademark of the tinyML Foundation and is used with permission. While the publisher and the authors have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. Use of the information and instructions contained in this work is at your own risk. If any code samples or other technology this work contains or describes is subject to open source licenses or the intellectual property rights of others, it is your responsibility to ensure that your use thereof complies with such licenses and/or rights.
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Deep Learning with PyTorch
A lot of data is generated by businesses every day. This data is rich and when analyzed properly, we can gain insights that are of great importance. Deep learning is a branch of machine learning through which we can extract such insights from data. Deep learning involves the creation of neural networks to process data. These normally work from the inspiration of how the human brain works. PyTorch is a deep learning library that can be used for creation of neural networks. This book helps you understand deep learning in Python using PyTorch.
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Tiny Python Projects
No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps.
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Пособие для работы по газете
Цель пособия-привить учащимся первичные навыки чтения газетных текстов, подготовить их к повседневному чтению газет.
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Deep Learning with Python
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0 ‘ZBEKIST0N MADANIYATI
0 “quv qoMlanmada o ‘zbek m adaniyatining nazariy asoslari, tarixi va Mustaqillik davridagi yutuqlari o ‘z ifodasini topgan. U nda madaniyat tushunchasi va uning mohiyati, turlari, funksiyalari. m a’naviy m eros, sivilizatsiya m asalalari, tarixim izning turli davrlarida yaratilgan madaniy boyliklar va ulam ing o ‘ziga xos xususiyatlari, tajribalari yangicha yondashuvlar asosida yoritilgan. Ayniqsa. Mustaqillik davri madaniyatiga, jumladan , madaniy islohotlar, milliy g ‘oya, a n ’anaviy m adaniyatning tiklanishi, 0 ‘zbekiston badiiy m adaniyati yutuqlari, m adaniy-m a’rifiy muassasalar faoliyatiga alohida e 'tib o r berilgan.
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Automotive Systems and Software Engineering
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Маълумотлар узатиш тизимлари ва тармоқлари
Ушбу китобда “Маълумотлар узатиш тизимлари ва тармоқлари” ўқув курси бўйича таълимни технологиялаштириш қоидалари, яъни дидактик тамойиллар, маъруза, амалий (семинар) ва тажриба машғулотлари технологиясини ишлаб чиқиш усуллари, унинг асосий хусусиятлари ҳисобга олинган ҳолда таълим-тарбия жараёнини лойиҳалаштирилган тажриба-синов таълим технологияси келтирилган. Китоб «Маълумотлар узатиш тизимлари ва тармоқлари» фанини ўқитадиган олий ўқув юртлари ва узлуксиз таълим тизимидаги барча ўқув муассасалари профессор-ўқитувчилари учун мўлжалланган.
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Deep Learning with Keras
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
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