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  1. SimPy: Simulação em Python
    Um guia prático
    Afonso C. Medina

    Aprenda a construir modelos de simulação de eventos discretos e de simulação baseadas em agentes utilizando o SimPy, uma biblioteca da linguagem Python.

  2. This book provides a guided tour of ML techniques utilized in process industry for plant health management. Step-by-step instructions, supported with industrial-scale process datasets, show how to develop ML-based solutions for equipment condition monitoring, plantwide monitoring, and predictive maintenance solutions. Also available at Google Play 

  3. This book powers our MicroMasters program on edX and specialization on Coursera, one of the ten most popular computer science courses on Coursera. Over half a million students have tried to solve many programming challenges and algorithmic puzzles described in this book. We invite you to join them! See the webpage of the book for more details.

  4. This book teaches you to use R to effectively visualize and explore complex datasets. Exploratory data analysis is a key part of the data science process because it allows you to sharpen your question and refine your modeling strategies. This book is based on the industry-leading Johns Hopkins Data Science Specialization.

  5. Ready to Master Python? Your Journey Begins Here! 🚀 Skip the jargon and stop feeling lost. This hands-on guide is your mission manual, taking you from your first "Hello World" to building real applications. With crystal-clear diagrams and practical exercises, we make learning intuitive and effective. Start your coding adventure today!

  6. Deep Learning for Network Engineers
    Understanding Traffic Patterns and Network Requirements in the AI Data Center
    Toni Pasanen

    Modern Deep Learning models can be extremely large, often exceeding the memory capacity of a single GPU or CPU. In these cases, training must be distributed across multiple processors. This introduces the need for high-speed communication between GPUs—both within a single server and across multiple servers. Intra-node GPU communication typically relies on high-speed interconnects like NVLink, with Direct Memory Access operations enabling efficient data transfers between GPUs. Inter-node communication, however, depends on the backend network, either  InfiniBand or Ethernet-based. Synchronization of model parameters across GPUs places strict requirements on the network: high throughput, ultra-low latency, and zero packet loss. Achieving this in an Ethernet fabric is challenging but possible.   This is where datacenter networking meets Deep Learning. Understanding how GPUs communicate and what the network must deliver is essential for designing effective AI data center infrastructures.

  7. The definitive guide to programming on the ESP32.

  8. This textbook is designed for use in introductory Software Engineering courses. Additionally, it can be used by junior developers intending to consolidate their knowledge in the field. It has also a web version available at https://softengbook.org.

  9. For the first time ever, C++23 changes "Hello World" in C++. What kind of fundamental changes does this mean for your code?

  10. Linux Troubleshooting Strategies
    Creative Fixes and Workarounds for Common Linux Problems
    Jay LaCroix

    Troubleshooting Linux systems can feel like solving a mystery—but the right strategies make all the difference. This ebook teaches practical techniques, tools, and real-world approaches that help you diagnose problems faster and fix them with confidence.

  11. "Your Java microservice runs in 2GB of memory. The same service in Rust? 200MB. Scale that across 100 instances in production, and you're looking at $3,000/month in savings. But it's not just about money—it's about predictability. While Java's garbage collector unpredictably pauses your latency-critical workloads, Rust guarantees deterministic performance. This book teaches you Rust from a Java developer's perspective: same powerful type system, same design patterns, but with compile-time safety that prevents entire categories of bugs. No more race conditions in concurrent code. No more null pointer exceptions. Just code that works, fast."

  12. The Orange Book of Machine Learning - Green edition
    The essentials of making predictions using supervised regression and classification for tabular data.
    Carl McBride Ellis

    The essentials of making predictions using supervised regression and classification for tabular data. Tech stack: python, pandas, scikit-learn, CatBoost, LightGBM, XGBoost

  13. The BDD Books - Formulation (Japanese Edition)
    BDD/ATDDの第2ステップ:Given/When/Then を使って具体例を定式化する
    Yuya Kazama, Gáspár Nagy, and Seb Rose

    本書籍は、振る舞い駆動開発(BDD)や受け入れテスト駆動開発(ATDD)の定式化フェーズを最大限に活用する方法を提供します。 書籍内では、優れたコラボレーション手法を具体例で示しており、実用的なガイドとなっています。

  14. Prepare yourself for the HashiCorp Certified: Vault Associate exam with this guide! HashiCorp Ambassador, Ned Bellavance reviews the certification objectives, provides insight from real-world experience, and gives key takeaways for to help you focus on what matters most.

  15. Perl New Features
    The evolution of Perl from v5.6 to now
    brian d foy

    In 2010, Joshua McAdams and I updated Joseph Hall's seminal book Effective Perl Programming for v5.10. We also set up a website to continue that work, and in the next 10 years we posted hundreds more articles, many of which explained new features that showed up after v5.10. I've collected and updated the items explicating those new features.