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Auteur Konrad BANACHEWICZ |
Documents disponibles écrits par cet auteur (2)
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The Kaggle Workbook : Self-learning exercises and valuable insights for Kaggle data science competitions / Konrad BANACHEWICZ / PACKT PUBLISHING (2023)
Titre : The Kaggle Workbook : Self-learning exercises and valuable insights for Kaggle data science competitions Type de document : e-book Auteurs : Konrad BANACHEWICZ Editeur : PACKT PUBLISHING Année de publication : 2023 ISBN/ISSN/EAN : 9781804611210 Note générale : copyrighted Langues : Anglais (eng) Résumé : Move up the Kaggle leaderboards and supercharge your data science and machine learning career by analyzing famous competitions and working through exercises.Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesChallenge yourself to start thinking like a Kaggle GrandmasterFill your portfolio with impressive case studies that will come in handy during interviewsPacked with exercises and notes pages for you to enhance your skills and record key findingsBook DescriptionMore than 80,000 Kaggle novices currently participate in Kaggle competitions. To help them navigate the often-overwhelming world of Kaggle, two Grandmasters put their heads together to write The Kaggle Book, which made plenty of waves in the community. Now, they've come back with an even more practical approach based on hands-on exercises that can help you start thinking like an experienced data scientist.In this book, you'll get up close and personal with four extensive case studies based on past Kaggle competitions. You'll learn how bright minds predicted which drivers would likely avoid filing insurance claims in Brazil and see how expert Kagglers used gradient-boosting methods to model Walmart unit sales time-series data. Get into computer vision by discovering different solutions for identifying the type of disease present on cassava leaves. And see how the Kaggle community created predictive algorithms to solve the natural language processing problem of subjective question-answering.You can use this workbook as a supplement alongside The Kaggle Book or on its own alongside resources available on the Kaggle website and other online communities. Whatever path you choose, this workbook will help make you a formidable Kaggle competitor.What you will learnTake your modeling to the next level by analyzing different case studiesBoost your data science skillset with a curated selection of exercisesCombine different methods to create better solutionsGet a deeper insight into NLP and how it can help you solve unlikely challengesSharpen your knowledge of time-series forecastingChallenge yourself to become a better data scientistWho this book is forIf you're new to Kaggle and want to sink your teeth into practical exercises, start with The Kaggle Book, first. A basic understanding of the Kaggle platform, along with knowledge of machine learning and data science is a prerequisite.This book is suitable for anyone starting their Kaggle journey or veterans trying to get better at it. Data analysts/scientists who want to do better in Kaggle competitions and secure jobs with tech giants will find this book helpful. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88941172 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=572640
Titre : The Kaggle Book Type de document : e-book Auteurs : Konrad BANACHEWICZ Editeur : PACKT PUBLISHING Année de publication : 2022 ISBN/ISSN/EAN : 9781801817479 Note générale : copyrighted Langues : Anglais (eng) Résumé : 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 FeaturesLearn how Kaggle works and how to make the most of competitions from over 30 expert KagglersSharpen your modeling skills with ensembling, feature engineering, adversarial validation and AutoMLA concise collection of smart data handling techniques for modeling and parameter tuningBook DescriptionMillions 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 learnGet acquainted with Kaggle as a competition platformMake the most of Kaggle Notebooks, Datasets, and Discussion forumsCreate a portfolio of projects and ideas to get further in your careerDesign k-fold and probabilistic validation schemesGet to grips with common and never-before-seen evaluation metricsUnderstand binary and multi-class classification and object detectionApproach NLP and time series tasks more effectivelyHandle simulation and optimization competitions on KaggleWho this book is forThis 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. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88929424 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=546763
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