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You're reading from  Data Science for Web3

Product typeBook
Published inDec 2023
PublisherPackt
ISBN-139781837637546
Edition1st Edition
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Author (1)
Gabriela Castillo Areco
Gabriela Castillo Areco
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Gabriela Castillo Areco

Gabriela Castillo Areco holds an M.Sc. in big data science from the TECNUM School of Engineering, University of Navarra. With extensive experience in both the business and data facets of blockchain technology, Gabriela has undertaken roles as a data scientist, machine learning analyst, and blockchain consultant in both large corporations and small ventures. She served as a professor of new crypto businesses at Torcuato di Tella University and is currently a member of the BizOps data team at IOV Labs.
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Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “The following information was taken from the CSV file, filtered by the Betweenness centrality column.”

A block of code is set as follows:

{'domain': {'id': '131',
'name': 'Unified Twitter Taxonomy',
'description': 'A taxonomy of user interests. '},
'entity': {'id': '913142676819648512',
'name': 'Cryptocurrencies',
'description': 'Cryptocurrency'}},

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

'annotations': 'annotations': [{'start': 10,
'end': 18,
'probability': 0.8568,
'type': 'Organization',
'normalized_text': 'Blackrock'},

Any command-line input or output is written as follows:

decompose = seasonal_decompose(df, model= 'additive').plot(observed=True, seasonal=True, trend=True, resid=True, weights=False)

Bold: Indicates a new term, an important word, or words that you see on screen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “Once we have filled in the mandatory requirements on the API page, we can press the blue Execute button, which will return the URL we can use.”

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Data Science for Web3
Published in: Dec 2023Publisher: PacktISBN-13: 9781837637546

Author (1)

author image
Gabriela Castillo Areco

Gabriela Castillo Areco holds an M.Sc. in big data science from the TECNUM School of Engineering, University of Navarra. With extensive experience in both the business and data facets of blockchain technology, Gabriela has undertaken roles as a data scientist, machine learning analyst, and blockchain consultant in both large corporations and small ventures. She served as a professor of new crypto businesses at Torcuato di Tella University and is currently a member of the BizOps data team at IOV Labs.
Read more about Gabriela Castillo Areco