Book The Kaggle Workbook: Self-learning exercises and valuable insights for Kaggle data science competitions PDF Download - Konrad Banachewicz, Luca Massaron
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The Kaggle Workbook: Self-learning exercises and valuable insights for Kaggle data science competitions
Konrad Banachewicz, Luca Massaron
Page: 120
Format: pdf, ePub, mobi, fb2
ISBN: 9781804611210
Publisher: Packt Publishing
Download or Read Online The Kaggle Workbook: Self-learning exercises and valuable insights for Kaggle data science competitions Free Book (PDF ePub Mobi) by Konrad Banachewicz, Luca Massaron
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Get on the leader boards in Kaggle competitions and learn valuable skills to supercharge your data science and machine learning career Explore data science, original ideas, and winning solutions from past Kaggle competitions Challenge yourself and start thinking like a Kaggle Grandmaster Fill your portfolio with impressive case studies that will come in handy during interviews More 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. The first guidebook on techniques for success has since 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 See how expert Kagglers estimated the uncertainty distribution of Walmart unit sales Discover the different solutions on how to identify the type of disease present on cassava leaves that were discovered in 2021 And learn how the Kaggle community classified detected toxic content on Quora with NLP 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. Boost your data science skillset with a curated selection of exercises Combine different methods to create better solutions Case studies and exercises to take your data modeling skills further Get a deeper insight into NLP and how it can help you solve unlikely challenges Sharpen your knowledge of time-series forecasting Challenge yourself to become a better data scientist If 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. The most renown tabular competition: Porto Seguro's Safe Driver Prediction The Makridakis competitions: M5 on Kaggle for accuracy and uncertainty Vision competition: Cassava Leaf Disease classification NLP competition: Quora insincere questions classification
Self-learning exercises and valuable insights for Kaggle data
The Kaggle Workbook: Self-learning exercises and valuable insights for Kaggle data science competitions eBook : Banachewicz, Konrad, Massaron,
The Kaggle Book: Data analysis and machine learning for
It offers a guide to both how Kaggle works, as well as many of the key learnings that they have taken out of their time on the site. Collectively, they've been
SOLUTIONS MANUAL FOR FUNDAMENTALS OF MACHINE
Machine Learning for Predictive Data Analytics: Exercise Solutions How the notation used in the book relates to the elements of a dataset. Datasets.
Konrad Banachewicz: Kindle Store - Amazon.in
The Kaggle Workbook: Self-learning exercises and valuable insights for Kaggle data science competitions This item will be released on December 9, 2022.
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The book covers a lot of statistics starting with descriptive statistics – mean, median, mode, standard deviation – and then go on to
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This list gets updated as soon as a new competition finishes. 2022 Kaggle Machine Learning & Data Science Survey Kind: Analytics.