Python

ブラックボックスのフレームワークは不要。純粋なPythonでプロダクションレベルのAIコーディングエージェントをゼロから構築。クラウドでもローカルでも、pytestでテスト済み、すべて1つのファイルに収まります。

Learn Polars, the pandas killer for data analysis.

The best compliment a reader can pay your code is not "this is impressive" — it is "this was exactly what I expected." Beautiful but Boring teaches the discipline of writing Python that earns that compliment: precise naming contracts, type annotations that say what a function actually requires, and a framework for maintaining those standards consistently across a codebase, a team, and a career.

The recipes in this book are practical answers to the kind of problems that real Django applications encounter, sometimes on the first day of a project and sometimes deep into the life of a codebase that has grown well beyond its original design. This book is written to guide you to utilize Django 6.0 capabilities in your apps with ease of implementation.

Learn LangGraph the fast, practical way by building real projects from your very first chapter. This hands-on guide cuts out the fluff and walks you step-by-step from simple graphs to powerful AI agents like ReAct and RAG. If you prefer learning by doing, this book will get you up and running quickly without overwhelming you.

Master AWS IoT Core with this hands-on, comprehensive guide. Learn how to securely connect, manage, and scale your IoT device fleets using MQTT, AWS IoT Greengrass, bulk enrollments, and OTA updates. From edge hardware setups to cloud analytics and Zero Trust security, build enterprise-grade architectures today.

Your Python is elegant, expressive, and — let's be honest — slow where it counts. This book teaches you to rewrite the 3% that hurts in Rust, without rewriting the 97% that doesn't, by building a real log intelligence platform from first spark to production-ready package. If you've ever stared at a profiler's output and thought there has to be a faster way — there is, and you won't even need to give up pip install.

Satélites capturam enormes volumes de imagens todos os dias, mas transformar pixels em conhecimento requer IA. Este livro ensina você a construir, treinar e aplicar modelos de aprendizado profundo a imagens de satélite reais usando Python e ferramentas de código aberto, com 23 capítulos de código executável que você pode usar hoje mesmo. Todos os exemplos de código estão disponíveis gratuitamente em https://book.opengeoai.org.

Satelit menangkap volume citra yang sangat besar setiap hari, tetapi mengubah piksel menjadi wawasan memerlukan AI. Buku ini mengajarkan Anda untuk membangun, melatih, dan menerapkan model deep learning pada citra satelit nyata menggunakan Python dan alat open source, dengan 23 bab berisi kode yang dapat dijalankan sekarang juga. Semua contoh kode tersedia gratis di https://book.opengeoai.org.

Спутники ежедневно собирают огромные объёмы изображений, но чтобы превратить пиксели в знания, требуется ИИ. Эта книга научит вас создавать, обучать и применять модели глубокого обучения к реальным спутниковым изображениям с использованием Python и инструментов с открытым исходным кодом. Она включает 23 главы с исполняемым кодом, который вы можете использовать уже сегодня. Все примеры кода доступны бесплатно на https://book.opengeoai.org.

위성은 매일 방대한 양의 이미지를 수집하지만, 픽셀을 통찰로 바꾸기 위해서는 AI가 필요합니다. 이 책은 Python과 오픈소스 도구를 사용하여 실제 위성 이미지에 딥러닝 모델을 구축, 학습, 적용하는 방법을 알려줍니다. 지금 바로 실행할 수 있는 코드로 구성된 23개의 장을 포함하고 있으며, 모든 코드 예제는 https://book.opengeoai.org 에서 무료로 제공됩니다.

衛星は毎日膨大な量の画像を取得していますが、ピクセルから洞察を得るにはAIが必要です。本書では、Pythonとオープンソースツールを用いて、実際の衛星画像に対してディープラーニングモデルを構築・学習・適用する方法を解説します。すぐに実行できるコードを含む23章で構成されており、すべてのコード例は https://book.opengeoai.org で無料公開されています。

I satelliti acquisiscono ogni giorno enormi volumi di immagini, ma trasformare i pixel in conoscenza richiede l’IA. Questo libro ti insegna a costruire, addestrare e applicare modelli di deep learning a immagini satellitari reali utilizzando Python e strumenti open source, con 23 capitoli di codice eseguibile che puoi utilizzare fin da subito. Tutti gli esempi di codice sono disponibili gratuitamente su https://book.opengeoai.org.

Satelliten erfassen täglich enorme Mengen an Bilddaten, doch um aus Pixeln Erkenntnisse zu gewinnen, ist KI erforderlich. Dieses Buch zeigt Ihnen, wie Sie Deep-Learning-Modelle für reale Satellitenbilder mit Python und Open-Source-Tools entwickeln, trainieren und anwenden können. Es enthält 23 Kapitel mit ausführbarem Code, den Sie sofort nutzen können. Alle Codebeispiele sind frei verfügbar unter https://book.opengeoai.org.

卫星每天获取海量影像数据，但将像素转化为洞察需要借助人工智能。本书将教你如何使用 Python 和开源工具构建、训练并应用深度学习模型，处理真实的卫星影像。全书包含 23 个可运行的代码章节，帮助你即学即用。所有代码示例均可在 https://book.opengeoai.org 免费获取。