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Ivan Idris

    Ivan Idris se concentre sur la rédaction d'articles techniques et de code propre et testable. Ses principaux centres d'intérêt professionnels résident dans la Business Intelligence, le Big Data et le Cloud Computing. Il met à profit son expertise pour créer des publications techniques qui démystifient les technologies complexes pour les lecteurs. Son approche met l'accent sur l'application pratique et la transparence du code, rendant son travail à la fois informatif et accessible.

    Numpy Beginner's Guide - Third Edition
    Numpy Cookbook
    Numpy Beginner's Guide (2nd Edition)
    • Numpy Beginner's Guide (2nd Edition)

      • 310pages
      • 11 heures de lecture
      3,9(21)Évaluer

      The book is written in beginner's guide style with each aspect of NumPy demonstrated with real world examples and required screenshots.If you are a programmer, scientist, or engineer who has basic Python knowledge and would like to be able to do numerical computations with Python, this book is for you. No prior knowledge of NumPy is required.

      Numpy Beginner's Guide (2nd Edition)
    • Numpy Cookbook

      • 226pages
      • 8 heures de lecture
      3,4(13)Évaluer

      Written in Cookbook style, the code examples will take your Numpy skills to the next level. This book will take Python developers with basic Numpy skills to the next level through some practical recipes.

      Numpy Cookbook
    • Numpy Beginner's Guide - Third Edition

      • 348pages
      • 13 heures de lecture

      About This Book Written as a step-by-step guide, this book aims to give you a strong foundation in NumPy and breaks down its complex library features into simple tasks Perform high performance calculations with clean and efficient NumPy code Analyze large datasets with statistical functions and execute complex linear algebra and mathematical computations Who This Book Is For This book is for the scientists, engineers, programmers, or analysts looking for a high-quality, open source mathematical library. Knowledge of Python is assumed. Also, some affinity, or at least interest, in mathematics and statistics is required. However, I have provided brief explanations and pointers to learning resources.

      Numpy Beginner's Guide - Third Edition