The Kaggle Book : Master data science competitions with machine learning, GenAI, and LLMs
Stay one step ahead of your competitors with proven tips, strategies, and insights from over 30 Kaggle Masters and Grandmasters and become a better data scientist. This new edition features updated content and new chapters on Kaggle Models, time series, and Generative AI competitions. Key Features:...
সংরক্ষণ করুন:
| প্রধান লেখক: | , , |
|---|---|
| বিন্যাস: | Livre numérique |
| ভাষা: | Anglais |
| প্রকাশিত: |
Birmingham :
Packt Publishing
2025.
Paris : Cyberlibris |
| অনলাইন ব্যবহার করুন: | Accès Université d'Orléans et IFPM |
| টীকা: |
Couverture. https://static2.cyberlibris.com/books_upload/300pix/9781835088630.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • The Kaggle Book, Master data science competitions with machine learning, GenAI, and LLMs, Luca Massaron, Bojan Tunguz, Konrad Banachewicz, Birmingham, Packt Publishing, 2025, 1 vol. (709 p.), 978-18-3508-320-8 |
| LEADER | 04410nam a22002417a 4500 | ||
|---|---|---|---|
| 001 | 1424263 | ||
| 008 | 260313s2025 xxg ||| |||| 00| 0 eng d | ||
| 009 | PPN294911898 | ||
| 020 | |a 9781835088630 | ||
| 041 | 0 | |a eng | |
| 100 | 1 | |a Massaron, Luca, |d 19..- | |
| 245 | 1 | 0 | |a The Kaggle Book : |b Master data science competitions with machine learning, GenAI, and LLMs |c Luca Massaron, Bojan Tunguz, Konrad Banachewicz. |
| 260 | |a Birmingham : |b Packt Publishing. | ||
| 260 | |a Paris : |b Cyberlibris, |c 2025. | ||
| 500 | |a Couverture. https://static2.cyberlibris.com/books_upload/300pix/9781835088630.jpg | ||
| 500 | |a Cyberlibris (ScholarVox) corpus Informatique | ||
| 506 | |a L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris | ||
| 520 | |a Stay one step ahead of your competitors with proven tips, strategies, and insights from over 30 Kaggle Masters and Grandmasters and become a better data scientist. This new edition features updated content and new chapters on Kaggle Models, time series, and Generative AI competitions. Key Features: Learn how Kaggle works to make the most of every competition with winning strategies from 30+ expert Kagglers; Sharpen your modeling skills with feature engineering, adversarial validation, gradient boosting, tabular deep learning, ensembling, and AutoML; Master data handling techniques for smarter modeling and parameter tuning. Book Description: Kaggle has become the proving ground for millions of data enthusiasts worldwide, offering what no classroom tutorial can match: battle-tested skills built through real-world challenges and the hands-on experience that employers seek. Every competition sharpens your data analysis skills, expands your network within the data scientist community, and gives compelling proof of expertise to unlock career opportunities. The first book of its kind, The Kaggle Book brings together everything you need to excel in competitions, data science projects, and beyond. This new edition includes fresh content and new chapters on Kaggle Models, time series, and Generative AI competitions, with three Kaggle Grandmasters guiding you through modeling strategies and sharing hard-earned insights accumulated over years of competition. The book extends far past competition tactics, revealing techniques for tackling image, tabular, and textual data as well as reinforcement learning tasks. You'll also discover tips for designing better validation schemes and working confidently with both standard and unconventional evaluation metrics. Whether you want to climb the Kaggle leaderboard, accelerate your data science career, or improve the accuracy of your models, this book is for you. Join our Discord community of over 1,000 members to learn, share, and grow together! What you will learn: Get acquainted with Kaggle as a competition platform; Make the most of Kaggle Notebooks, Datasets, Models and Discussion forums; Build a compelling portfolio of projects and ideas to advance your career; Understand binary and multi-class classification, as well as object detection; Approach NLP and time series problems with greater efficiency; Design k-fold and probabilistic validation schemes and experiment with multiple approaches; Get to grips with common and never-before-seen evaluation metrics; Handle simulation, optimization, and the new Generative AI competitions on Kaggle. Who this book is for: This book is for anyone interested in Kaggle, whether you're just starting out, a veteran user, or somewhere in between. Data analysts and data scientists looking to improve their performance in Kaggle competitions and improve their job prospects with tech giants will find this book useful. A basic understanding of machine learning concepts will help you get the most out of this book | ||
| 700 | 1 | |a Tunguz, Bojan. |4 aut | |
| 700 | 1 | |a Banachewicz, Konrad. |4 aut | |
| 776 | 0 | |t The Kaggle Book |o Master data science competitions with machine learning, GenAI, and LLMs |f Luca Massaron, Bojan Tunguz, Konrad Banachewicz |c Birmingham |n Packt Publishing |d 2025 |p 1 vol. (709 p.) |z 978-18-3508-320-8 | |
| 856 | 4 | |5 452349901:879126043 |u https://ezproxy.univ-orleans.fr/login?url=https://univ.scholarvox.com/book/88977564 |z Accès Université d'Orléans et IFPM | |
| 997 | |0 1424263 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/ScholarVox (ebooks)/ | ||