Develop an array of effective strategies and blueprints to approach any new data analysis on Kaggle and create Notebooks with substance, style, and impact for Kaggle.Key FeaturesStart from the basics to master ingestion, cleaning, and exploration of data, and prepare for building baseline modelsDevelop a robust approach to working with any type, modality, and size of data - from tabular, text, and image to video and sound dataImprove your style and readability and make your Notebooks more visible and impactfulBook DescriptionDeveloping Kaggle Notebooks is here to introduce you to the wide world of data analysis, with a focus on using Kaggle Notebooks resources to help you achieve mastery in this field as well as rising to the top in the Kaggle Notebooks tier. The book is structured as a seven-step trip into the world of analysis, exploring the features available in Kaggle Notebooks alongside various data analysis techniques and different kinds of datasets.For each topic, we will provide one or more Notebooks and develop reusable analysis components using the Kaggle utility scripts feature. These will be introduced gradually, first as part of a Notebook, and then extracted and used across future Notebooks to improve code reusability on Kaggle and make the Notebooks' code more structured, easy to maintain, and readable.Although the focus of this book is on data analytics, some of the examples will also help you learn how to prepare a full machine learning pipeline using Kaggle Notebooks. Starting from initial data ingestion and assessment of data quality, you'll move on to preliminary data analysis and advanced data exploration. Discover how to qualify features to build an initial model baseline and perform feature engineering and hyperparameter tuning to iteratively refine your model and prepare for a submission on Kaggle competitions.What you will learnApproach a new dataset or competition to perform a data analysis via a Notebook and get noticedStart exploring a new source of data, from tools to use for ingestion to treating various issues with ingested dataStructure your code using reusable componentsPerform a deep dive for both small and large datasets of various typesDifferentiate yourself from the crowd with the content of your analysisImprove the style of your color scheme, content organization, visual effects, and themeUse storytelling techniques to captivate your audience, improve the clarity of the presentation, and raise its impactWho this book is forThis book is suitable for a wide audience with a keen interest in data science and machine learning and those who want to use Kaggle Notebooks to improve their skills and rise in the Kaggle Notebooks ranks.Beginners on Kaggle from any background will benefitSeasoned contributors who want to improve various skills like ingestion, preparation, exploration, and visualizationExpert contributors who would like to learn from the Grandmasters to rise into the upper Kaggle rankingsProfessionals who already use Kaggle for learning and competingTable of ContentsIntroductionGetting ready for Kaggle environmentStarting our travel - how to survive on Titanic?Take a break and have a beer or a coffee in LondonGet back to work and optimize the microloans for developing countriesCan you predict bee species?