The Kaggle Book
Packt Publishing Limited (Verlag)
978-1-80181-747-9 (ISBN)
Purchase of the print or Kindle book includes a free eBook in the PDF format.
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 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.
Plus, join our Discord Community to learn along with more than 1,000 members and meet like-minded people!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 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.
Konrad Banachewicz is the author of the bestselling, The Kaggle Book and The Kaggle Workbook. He is a data science manager with experience stretching longer than he likes to ponder on. He holds a PhD in statistics from Vrije Universiteit Amsterdam, where he focused on problems of extreme dependency modeling in credit risk. He slowly moved from classic statistics towards machine learning and into the business applications world. Having joined Kaggle over 10 years ago, Luca Massaron is a Kaggle Grandmaster in discussions and a Kaggle Master in competitions and notebooks. In Kaggle competitions he reached no. 7 in the worldwide rankings. On the professional side, Luca is a data scientist with more than a decade of experience in transforming data into smarter artifacts, solving real-world problems, and generating value for businesses and stakeholders. He is a Google Developer Expert(GDE) in machine learning and the author of best-selling books on AI, machine learning, and algorithms.
Table of Contents
Introducing Kaggle and Other Data Science Competitions
Organizing Data with Datasets
Working and Learning with Kaggle Notebooks
Leveraging Discussion Forums
Competition Tasks and Metrics
Designing Good Validation
Modeling for Tabular Competitions
Hyperparameter Optimization
Ensembling with Blending and Stacking Solutions
Modeling for Computer Vision
Modeling for NLP
Simulation and Optimization Competitions
Creating Your Portfolio of Projects and Ideas
Finding New Professional Opportunities
| Erscheinungsdatum | 28.04.2022 |
|---|---|
| Vorwort | Anthony Goldbloom |
| Verlagsort | Birmingham |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Mathematik / Informatik ► Informatik ► Grafik / Design | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-10 | 1-80181-747-2 / 1801817472 |
| ISBN-13 | 978-1-80181-747-9 / 9781801817479 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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