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Python Data Cleaning and Preparation Best Practices. A practical guide to organizing and handling data from various sources and formats using Python

Język publikacji: angielskim
Autor:
Maria Zervou
Python Data Cleaning and Preparation Best Practices. A practical guide to organizing and handling data from various sources and formats using Python Maria Zervou - okladka książki

Python Data Cleaning and Preparation Best Practices. A practical guide to organizing and handling data from various sources and formats using Python Maria Zervou - okladka książki

Serie wydawnicze:
Hands-on
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
456
Dostępne formaty:
     PDF
     ePub

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Do przechowalni

Professionals face several challenges in effectively leveraging data in today's data-driven world. One of the main challenges is the low quality of data products, often caused by inaccurate, incomplete, or inconsistent data. Another significant challenge is the lack of skills among data professionals to analyze unstructured data, leading to valuable insights being missed that are difficult or impossible to obtain from structured data alone.
To help you tackle these challenges, this book will take you on a journey through the upstream data pipeline, which includes the ingestion of data from various sources, the validation and profiling of data for high-quality end tables, and writing data to different sinks. You’ll focus on structured data by performing essential tasks, such as cleaning and encoding datasets and handling missing values and outliers, before learning how to manipulate unstructured data with simple techniques. You’ll also be introduced to a variety of natural language processing techniques, from tokenization to vector models, as well as techniques to structure images, videos, and audio.
By the end of this book, you’ll be proficient in data cleaning and preparation techniques for both structured and unstructured data.
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O autorze książki

Maria is a Greek expat experiencing London life! With a Master's degree in Data Science and a lot of curiosity about how data can unlock new ways of solving problems, her journey into the data world started. Maria has worked as a Data Scientist and an ML engineer for the past 4 years. Today, she is working as Senior Specialist Solutions Architect at Databricks where she helps businesses leverage data and AI to solve their data challenges at scale. Her passion for new technologies and cloud infrastructure, as well as automation and simplicity, comes as no surprise. Maria is also a public speaker advocating how to build Machine learning products at scale and how we can make the data space more inclusive and diverse.

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