The Kaggle Workbook: Self-learning exercises and valuable insights for Kaggle data science competitions
- Length: 172 pages
- Edition: 1
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2023-02-24
- ISBN-10: 1804611212
- ISBN-13: 9781804611210
- Sales Rank: #559491 (See Top 100 Books)
source link Move up the Kaggle leaderboards and supercharge your data science and machine learning career by analyzing famous competitions and working through exercises.
https://technocretetrading.com/beq3l6fxnclick Purchase of the print or Kindle book includes a free eBook in PDF format.
https://marcosgerente.com.br/tjf9jl1dKey Features
- Challenge yourself to start thinking like a Kaggle Grandmaster
- Fill your portfolio with impressive case studies that will come in handy during interviews
- Packed with exercises and notes pages for you to enhance your skills and record key findings
Book Description
Valium To Buy 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, 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.
https://www.drcarolineedwards.com/2024/09/18/xc3jx4cagoyhttps://trevabrandonscharf.com/g1v0di3z 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.
https://ragadamed.com.br/2024/09/18/4bwty9fgl8https://luisfernandocastro.com/snv9ibps4w 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.
go hereWhat you will learn
- Take your modeling to the next level by analyzing different case studies
- Boost your data science skillset with a curated selection of exercises
- Combine different methods to create better solutions
- 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
Who this book is for
Buy Diazepam Online India 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.
https://luisfernandocastro.com/xau27gvhttps://technocretetrading.com/atwymmg7gl 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.
enter sitehttps://vbmotorworld.com/vd8ua9v2t Cover Copyright Table of Contents Preface Chapter 1: The Most Renowned Tabular Competition – Porto Seguro’s Safe Driver Prediction Understanding the competition and the data Understanding the evaluation metric Examining the top solution ideas from Michael Jahrer Building a LightGBM submission Setting up a denoising autoencoder and a DNN Ensembling the results Summary Chapter 2: The Makridakis Competitions – M5 on Kaggle for Accuracy and Uncertainty Understanding the competition and the data Understanding the Evaluation Metric Examining the 4th place solution’s ideas from Monsaraida Computing predictions for specific dates and time horizons Assembling public and private predictions Summary Chapter 3: Vision Competition: Cassava Leaf Disease Competition Understanding the data and metrics Building a baseline model Learning from top solutions Pretraining Test time augmentation Transformers Ensembling A complete solution Summary Chapter 4: NLP Competition – Google Quest Q&A Labeling The baseline solution Learning from top solutions Summary Packt page Other Books You May Enjoy Index
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