Developing Kaggle Notebooks : Pave your way to becoming a Kaggle Notebooks Grandmaster
Language: English
Published by Packt Publishing, 2023
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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nach der Bestellung gedruckt Neuware - Printed after ordering - Printed in ColorDevelop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Not Elektronisches Buch with substance, style and impactLeverage the power of Generative AI with Kaggle ModelsPurchase of the print or Kindle book includes a free PDF Elektronisches BuchKey FeaturesMaster the basics of data ingestion, cleaning, exploration, and prepare to build baseline modelsWork robustly with any type, modality, and size of data, be it tabular, text, image, video, or soundImprove the style and readability of your Not Elektronisches Buch, making them more impactful and compellingBook DescriptionDeveloping Kaggle Not Elektronisches Buch introduces you to data analysis, with a focus on using Kaggle Not Elektronisches Buch to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Not Elektronisches Buch tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Not Elektronisches Buch alongside various data analysis techniques.For each topic, we provide one or more not Elektronisches Buch, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future not Elektronisches Buch to enhance code reusability on Kaggle. It aims to make the not Elektronisches Buch' code more structured, easy to maintain, and readable.Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Not Elektronisches Buch. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing not Elektronisches Buch that leverage the power of generative AI using Kaggle Models.What you will learnApproach a dataset or competition to perform data analysis via a notebookLearn data ingestion and address issues arising with the ingested dataStructure your code using reusable componentsAnalyze in depth both small and large datasets of various typesDistinguish yourself from the crowd with the content of your analysisEnhance your notebook style with a color scheme and other visual effectsCaptivate your audience with data and compelling storytelling techniquesWho this book is forThis book is suitable for a wide audience with a keen interest in data science and machine learning, looking to use Kaggle Not Elektronisches Buch to improve their skills and rise in the Kaggle Not Elektronisches Buch ranks. This book caters to:Beginners on Kaggle from any backgroundSeasoned contributors who want to build various skills like ingestion, preparation, exploration, and visualizationExpert contributors who want to learn from the Grandmasters to rise into the upper Kaggle rankingsProfessionals who already use Kaggle for learning and competingTable of ContentsIntroducing Kaggle and Its Basic FunctionsGetting Ready for Your Kaggle EnvironmentStarting Our Travel - Surviving the Titanic DisasterTake a Break and Have a Beer or Coffee in LondonGet Back to Work and Optimize Microloans for Developing CountriesCan You Predict Bee Subspecies Text Analysis Is All You NeedAnalyzing Acoustic Signals to Predict the Next Simulated EarthquakeCan You Find Out Which Movie Is a Deepfake Unleash the Power of Generative AI with Kaggle ModelsClosing Our Journey: How to Stay Relevant and on Top.…
Seller Inventory # 9781805128519
- Title
- Developing Kaggle Notebooks : Pave your way to becoming a Kaggle Notebooks Grandmaster
- Author
- Gabriel Preda
- Publisher
- Packt Publishing
- Publication year
- 2023
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1805128515
- ISBN 13
- 9781805128519
- Item weight
- 690 grams
- Dimensions
- 235x191x20 mm
Printed in Color
Develop an array of effective strategies and blueprints to approach any new data analysis on the Kaggle platform and create Notebooks with substance, style and impact
Leverage the power of Generative AI with Kaggle Models
Purchase of the print or Kindle book includes a free PDF eBook
Key Features
- Master the basics of data ingestion, cleaning, exploration, and prepare to build baseline models
- Work robustly with any type, modality, and size of data, be it tabular, text, image, video, or sound
- Improve the style and readability of your Notebooks, making them more impactful and compelling
Book Description
Developing Kaggle Notebooks introduces you to data analysis, with a focus on using Kaggle Notebooks to simultaneously achieve mastery in this fi eld and rise to the top of the Kaggle Notebooks tier. The book is structured as a sevenstep data analysis journey, exploring the features available in Kaggle Notebooks alongside various data analysis techniques.
For each topic, we provide one or more notebooks, developing reusable analysis components through Kaggle's Utility Scripts feature, introduced progressively, initially as part of a notebook, and later extracted for use across future notebooks to enhance code reusability on Kaggle. It aims to make the notebooks' code more structured, easy to maintain, and readable.
Although the focus of this book is on data analytics, some examples will guide you in preparing a complete machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and data quality assessment, you'll move on to preliminary data analysis, advanced data exploration, feature qualifi cation to build a model baseline, and feature engineering. You'll also delve into hyperparameter tuning to iteratively refi ne your model and prepare for submission in Kaggle competitions. Additionally, the book touches on developing notebooks that leverage the power of generative AI using Kaggle Models.
What you will learn
- Approach a dataset or competition to perform data analysis via a notebook
- Learn data ingestion and address issues arising with the ingested data
- Structure your code using reusable components
- Analyze in depth both small and large datasets of various types
- Distinguish yourself from the crowd with the content of your analysis
- Enhance your notebook style with a color scheme and other visual effects
- Captivate your audience with data and compelling storytelling techniques
Who this book is for
This book is suitable for a wide audience with a keen interest in data science and machine learning, looking to use Kaggle Notebooks to improve their skills and rise in the Kaggle Notebooks ranks. This book caters to:
Beginners on Kaggle from any background
Seasoned contributors who want to build various skills like ingestion, preparation, exploration, and visualization
Expert contributors who want to learn from the Grandmasters to rise into the upper Kaggle rankings
Professionals who already use Kaggle for learning and competing
Table of Contents
- Introducing Kaggle and Its Basic Functions
- Getting Ready for Your Kaggle Environment
- Starting Our Travel – Surviving the Titanic Disaster
- Take a Break and Have a Beer or Coffee in London
- Get Back to Work and Optimize Microloans for Developing Countries
- Can You Predict Bee Subspecies?
- Text Analysis Is All You Need
- Analyzing Acoustic Signals to Predict the Next Simulated Earthquake
- Can You Find Out Which Movie Is a Deepfake?
- Unleash the Power of Generative AI with Kaggle Models
- Closing Our Journey: How to Stay Relevant and on Top
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Gabriel Preda is a Principal Data Scientist for Endava, a major software services company. He has worked on projects in various industries, including financial services, banking, portfolio management, telecom, and healthcare, developing machine learning solutions for various business problems, including risk prediction, churn analysis, anomaly detection, task recommendations, and document information extraction. In addition, he is very active in competitive machine learning, currently holding the title of a three-time Kaggle Grandmaster and is well-known for his Kaggle Notebooks.
"About the title" may belong to another edition of this title.
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