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Stavka #:
211318723
生成AI、LLMのためのPythonディープラーニング教科書
Stavka #:
211318723
€ 41
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What Stands Out
Comprehensive Coverage
This book provides an in-depth exploration of AI and LLM technologies, ensuring both beginners and advanced users can effectively grasp complex concepts and practical applications in Python deep learning.
Hands-on Learning
With numerous practical examples and exercises, readers can apply their knowledge immediately, gaining valuable hands-on experience that enhances understanding and retention of deep learning techniques.
Future-Proof Content
Published in 2026, the content is tailored to include the latest developments in AI and deep learning, ensuring readers stay ahead in a fast-evolving field, making it a valuable resource for years to come.
Detalji o proizvodu
- 生成AI時代のエンジニア必須知識を Keras開発者がコードファースト で解説！Pythonディープラーニングのベストセラー書籍が、生成AI、Keras 3 、PyTorch、JAXを網羅！ ディープラーニングと生成AIの背後にある概念を分かりやすく解説します ベストセラーとなったManning刊 Deep Learning with Python が全面的に書き直され、Transformer、GPTライクなLLMの構築、拡散モデルを用いた画像生成などの新章も追加されました。ディープラーニングを段階的に理解できる実践的なプロジェクトとコード例が各章で紹介されます。 10年足らずの間に、ディープラーニングは世界を二度も変えました。Keras、TensorFlow、PyTorchといったPythonベースのライブラリが、ニューラルネットワークを実験室レベルから、大規模に展開される高性能な本番システムへと進化させました。LLMや生成AIツールを通して、ディープラーニングは再びビジネスと社会を変革しつつあります。 ディープラーニングと生成AIの背後にある概念をKerasの開発者から直接学びとりPythonを使ったディープラーニング世界に自信を持って踏み出そう！ 1章 ディープラーニングとは何か 2章 ニューラルネットワークの数学的要素 3章 Tensorflow、PyTorch、JAX、Keras 4章 分類と回帰 5章 機械学習の基礎 6章 機械学習の普遍的なワークフロー 7章 Kerasを深く理解する 8章 画像分類 9章 ConvNetアーキテクチャパターン 10章 ConvNetが何を学習するのかを解釈する 11章 画像セグメンテーション 12章 物体検出 13章 時系列予測 14章 テキスト分類 15章 言語モデルとTransformer 16章 テキスト生成 LLM（大規模言語モデル） 17章 画像生成 18章 実務におけるベストプラクティス 19章 AIの未来 20章 本書のまとめ
| Publisher | マイナビ出版 |
| Publication date | March 18, 2026 |
| Language | Japanese |
| Print length | 640 pages |
| ISBN-10 | 4839989680 |
| ISBN-13 | 978-4839989682 |
| Item Weight | 600 g |
| Dimensions | 1.18 x 7.17 x 9.21 inches (3 x 18.2 x 23.4 cm) |
Who Should Buy?
-
Beginner Programmers
New to Python and eager to learn deep learning for AI applications will find this resource invaluable.
-
AI Enthusiasts
Individuals interested in generative AI and language models will benefit from the comprehensive coverage of these topics.
-
Educators and Trainers
Educators looking for structured material to teach Python deep learning will find this book an excellent resource.
-
Advanced Practitioners
Experienced data scientists may find the content too basic and not challenging enough for their skill level.
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Značajke i prednosti
- Essential knowledge for engineers in the era of Generative AI.
- Comprehensive coverage of Keras 3, PyTorch, and JAX.
- Easy-to-understand explanations of deep learning concepts.
- Updated best-seller with new chapters on Transformers and image generation.
- Practical projects and code examples in every chapter.
- Transforms the deep learning landscape for business and society.
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