Name: AI Projects in PyTorch
SKU: 195199876
Price: 96230 KRW
Availability: InStock
Author: Siddhesh Prashant Chaubal
ISBN: 9798868821165

카트

이미지 검색을 사용해 보세요

검색창 이전화면 이전화면

최근 검색어: 전체삭제

인기 검색어

닫기

사이즈비교 공유하기

소득공제 수입

직수입양서 AI Projects in PyTorch

Hands-On Projects in Vision, Text, and Generative Models Perfect,eng, POD 주문제작도서

바인딩/에디션 안내

Siddhesh Prashant Chaubal

Springer Nature B.V. 2026.01.03.

회원리뷰 첫번째 리뷰어가 되어주세요

직수입외서는 변심/착오로 인해 주문을 취소할 경우 해외주문 취소수수료 20%가 부과됩니다.?

가격: 96,230원

96,230

YES포인트?: 2,890원 (3%) 마니아추가적립

5만원 이상 구매 시 2천원 추가 적립

앱 다운 시 1천원 상품권

결제혜택: 최대 6만원 캐시백

주문 제작 (POD) 도서로 제본 및 인쇄 품질이 다소 미흡할 수 있습니다 (해당 사유 반품 불가)

이미 소장하고 있다면 판매해 보세요.

예스24에 팔기 바이백 신청 불가 내 가게에서 팔기

국내배송만 가능
해외 거래처 사정에 의하여 품절/지연 가능
도서 정보 중 미표기 사항 안내?
문화비소득공제 가능

시리즈 태그 업체 공지사항 중고직수입양서 소개 구성 소개 특별 구성 MD 한마디 카드뉴스 상세 이미지 책소개 관련 동영상 목차 저자 소개 관련분류 품목정보 만든이 코멘트 예스24 리뷰 책 속으로 줄거리 캐스팅 관련 자료 부가 영상 출판사 리뷰 전문가 리뷰 추천평

펼치기/닫기

책소개

Dive into computer vision, natural language processing, and recommender systems by building end-to-end projects in PyTorch ? one of the most widely used deep learning frameworks among researchers and engineers worldwide. This book takes you from the fundamentals to complete, hands-on projects, giving you the confidence to start creating your own AI solutions. The book begins with a chapter on the fundamentals of machine learning, laying the groundwork by introducing key aspects of an ML project such as data preprocessing, feature engineering, model training, and evaluation, along with essential concepts like overfitting and underfitting. The following chapter, "Tensors in PyTorch," explores data handling in PyTorch -- from basic tensor operations to advanced gradient computations -- providing a deeper understanding of data transformations. With the foundations in place, the book moves on to hands-on projects. Chapter 3 introduces you to the world of computer vision, where you will build an image classifier using convolutional neural networks. The next three chapters immerse you in natural language processing: beginning with text classification (Chapter 4), tackling a range of NLP tasks with Hugging Face (Chapter 5), and culminating in the creation of a storytelling language model (Chapter 6). The focus then shifts to other key AI domains ? you will tackle an audio classification task (Chapter 7), build a recommender system in PyTorch (Chapter 8), and finish with a multi-modal project that combines computer vision and natural language processing to build an image captioning system (Chapter 9). Whether you're a software engineer looking to break into the world of AI or a beginner with basic Python skills, "AI Projects with PyTorch" offers practical guidance and hands-on experience to start building your own AI applications with confidence. What you will learn: Master the core principles of machine learning and gain confidence with the typical PyTorch project workflow. Build a solid understanding of data handling in PyTorch ? including tensors, datasets, data loaders, and gradient computations. Build natural language processing models, from text classification to storytelling language models. Work on multiple natural language processing tasks with Hugging Face libraries. Combine vision and language to build an image captioning system. ? Who this is book is for: - ? ? ? ? ?Python programmers and software engineers who are new to AI and want a practical, project-based introduction with PyTorch. ?ML engineers who wish to expand into other AI domains such as computer vision, natural language processing, audio processing, etc.

책소개 더보기펼치기