Python 実践データ分析100本ノック 第3版
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XPF 3162
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- リアルな実践データで練習するから即戦力になるスキルが身につく!!○100本ノック 実践練習! …実力をアップする特訓○朝練 まずは準備運動! …分析ツールの使い方○放課後練 応用ノック! …さらなる挑戦を!総ノック120本(超)!!⦅Point!⦆無料のGoogleアカウントがあれば誰でも利用できるColaboratory(データ分析や機械学習に必要な多くのライブラリが標準搭載)で、すぐに練習をはじめられる!!■目次■■朝練 100本ノックに備えて準備運動を行いましょう。序章 朝練 (はじめる前の準備運動・環境整備など)■第1部 基礎編:データ加工第1章 ウェブからの注文数を分析する10本ノック第2章 小売店のデータでデータ加工を行う10本ノック■第2部 実践編1:機械学習第3章 顧客の全体像を把握する10本ノック第4章 顧客の行動を予測する10本ノック第5章 顧客の退会を予測する10本ノック■第3部 実践編2:最適化問題第6章 物流の最適ルートをコンサルティングする10本ノック第7章 ロジスティクスネットワークの最適設計を行う10本ノック第8章 数値シミュレーションで消費者行動を予測する10本ノック■第4部 発展編:画像処理/言語処理第9章 潜在顧客を把握するための画像認識10本ノック第10章 アンケート分析を行うための自然言語処理10本ノック■放課後ノック ローカルLLMを使ってみる20本ノック第11章 大規模言語モデル(LLM)を活用した20本ノック
| Publisher | 秀和システム新社 |
| Publication date | October 10, 2025 |
| Edition | Third |
| Language | Japanese |
| Print length | 352 pages |
| ISBN-10 | 4798075663 |
| ISBN-13 | 978-4798075662 |
| Item Weight | 440 g |
| Dimensions | 5.83 x 0.87 x 8.27 inches (14.8 x 2.2 x 21 cm) |
Who Should Buy?
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Data Science Beginners
Those new to data analysis will benefit from structured exercises that build foundational skills effectively.
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Python Practitioners
Individuals with basic Python knowledge looking to deepen their understanding of data analysis and visualization techniques.
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Educators and Trainers
Teachers seeking comprehensive materials for data analysis courses can find valuable resources and examples in this book.
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Advanced Analysts
Experienced data analysts may find the content too basic, lacking the complexity they require for advanced projects.
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下山輝昌 , 松田雄馬 Editorial Review
Python 実践データ分析100本ノック 第3版 is an essential guide for anyone looking to enhance their data analysis skills with Python. This third edition, published by 幸和システム新社, covers a comprehensive array of practical challenges designed to sharpen your analytical abilities across 352 pages. Readers appreciate that it combines a hands-on approach with a solid foundation in data analysis principles, making it suitable for both beginners and seasoned practitioners. The book’s format allows learners to tackle 100 practical tasks, which many reviews have highlighted as an effective method for mastering Python data analysis tactically. Furthermore, the publication date in October 2025 positions it as a current resource in the rapidly evolving world of data science, ensuring users are learning relevant techniques.
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Pros
- Hands-on approach with practical challenges
- Comprehensive coverage of data analysis techniques
- Suitable for both beginners and advanced users
- Current resource in the evolving data science field
- Well-structured for efficient learning
Cons
- Might seem dense for absolute beginners
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XPF 3162
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