The Kaggle Book: Data analysis and machine learning for competitive data science (Paperback)
暫譯: Kaggle 書籍:競賽數據科學的數據分析與機器學習 (平裝本)

Banachewicz, Konrad, Massaron, Luca

  • 出版商: Packt Publishing
  • 出版日期: 2022-04-22
  • 售價: $2,100
  • 貴賓價: 9.5$1,995
  • 語言: 英文
  • 頁數: 530
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1801817472
  • ISBN-13: 9781801817479
  • 相關分類: Data ScienceMachine Learning
  • 立即出貨 (庫存=1)

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商品描述

Get a step ahead of your competitors with insights from over 30 Kaggle Masters and Grandmasters. Discover tips, tricks, and best practices for competing effectively on Kaggle and becoming a better data scientist.

Key Features

- Learn how Kaggle works and how to make the most of competitions from over 30 expert Kagglers
- Sharpen your modeling skills with ensembling, feature engineering, adversarial validation and AutoML
- A concise collection of smart data handling techniques for modeling and parameter tuning

Book Description

Millions of data enthusiasts from around the world compete on Kaggle, the most famous data science competition platform of them all. Participating in Kaggle competitions is a surefire way to improve your data analysis skills, network with an amazing community of data scientists, and gain valuable experience to help grow your career.

The first book of its kind, The Kaggle Book assembles in one place the techniques and skills you'll need for success in competitions, data science projects, and beyond. Two Kaggle Grandmasters walk you through modeling strategies you won't easily find elsewhere, and the knowledge they've accumulated along the way. As well as Kaggle-specific tips, you'll learn more general techniques for approaching tasks based on image, tabular, textual data, and reinforcement learning. You'll design better validation schemes and work more comfortably with different evaluation metrics.

Whether you want to climb the ranks of Kaggle, build some more data science skills, or improve the accuracy of your existing models, this book is for you.

What you will learn

- Get acquainted with Kaggle as a competition platform
- Make the most of Kaggle Notebooks, Datasets, and Discussion forums
- Create a portfolio of projects and ideas to get further in your career
- Design k-fold and probabilistic validation schemes
- Get to grips with common and never-before-seen evaluation metrics
- Understand binary and multi-class classification and object detection
- Approach NLP and time series tasks more effectively
- Handle simulation and optimization competitions on Kaggle

Who this book is for

This book is suitable for anyone new to Kaggle, veteran users, and anyone in between. Data analysts/scientists who are trying to do better in Kaggle competitions and secure jobs with tech giants will find this book useful.

A basic understanding of machine learning concepts will help you make the most of this book.

商品描述(中文翻譯)

獲得超過30位Kaggle大師和特級大師的見解,讓您在競爭中領先一步。發現有效參加Kaggle競賽的技巧、竅門和最佳實踐,並成為更優秀的數據科學家。

主要特點

- 了解Kaggle的運作方式,並從超過30位專家Kaggler那裡獲取競賽的最大收益
- 通過集成、特徵工程、對抗驗證和AutoML來提升您的建模技能
- 精簡的智能數據處理技術集合,用於建模和參數調整

書籍描述

來自世界各地的數百萬數據愛好者在Kaggle上競爭,這是最著名的數據科學競賽平台。參加Kaggle競賽是提升數據分析技能、與優秀的數據科學家社群建立聯繫以及獲得寶貴經驗以促進職業發展的可靠途徑。

這本書是同類書籍中的第一本,將您在競賽、數據科學項目及其他領域成功所需的技術和技能集中在一個地方。兩位Kaggle特級大師將帶您了解在其他地方不易找到的建模策略,以及他們在過程中積累的知識。除了Kaggle特定的技巧外,您還將學習基於圖像、表格、文本數據和強化學習的更一般性技術。您將設計更好的驗證方案,並更輕鬆地使用不同的評估指標。

無論您是想在Kaggle中提升排名、增強數據科學技能,還是提高現有模型的準確性,這本書都適合您。

您將學到的內容

- 熟悉Kaggle作為競賽平台
- 充分利用Kaggle Notebooks、Datasets和討論論壇
- 創建項目和想法的作品集,以便在職業生涯中更進一步
- 設計k-fold和概率驗證方案
- 理解常見和前所未見的評估指標
- 理解二元和多類別分類及物體檢測
- 更有效地處理NLP和時間序列任務
- 處理Kaggle上的模擬和優化競賽

本書適合對Kaggle感興趣的新手、資深用戶以及介於兩者之間的任何人。希望在Kaggle競賽中表現更好並獲得科技巨頭工作的數據分析師/科學家將會發現這本書非常有用。

對機器學習概念的基本理解將幫助您充分利用這本書。

目錄大綱

1. Introducing Kaggle and Other Data Science Competitions
2. Organizing Data with Datasets
3. Working and Learning with Kaggle Notebooks
4. Leveraging Discussion Forums
5. Competition Tasks and Metrics
6. Designing Good Validation
7. Modeling for Tabular Competitions
8. Hyperparameter Optimization
9. Ensembling with Blending and Stacking Solutions
10. Modeling for Computer Vision
11. Modeling for NLP
12. Simulation and Optimization Competitions
13. Creating Your Portfolio of Projects and Ideas
14. Finding New Professional Opportunities

目錄大綱(中文翻譯)

1. Introducing Kaggle and Other Data Science Competitions

2. Organizing Data with Datasets

3. Working and Learning with Kaggle Notebooks

4. Leveraging Discussion Forums

5. Competition Tasks and Metrics

6. Designing Good Validation

7. Modeling for Tabular Competitions

8. Hyperparameter Optimization

9. Ensembling with Blending and Stacking Solutions

10. Modeling for Computer Vision

11. Modeling for NLP

12. Simulation and Optimization Competitions

13. Creating Your Portfolio of Projects and Ideas

14. Finding New Professional Opportunities