The role of data scientists and analysts in data-driven decision-making cannot be overstated. Flexibility is a must when it comes to handling large datasets. This abstract introduces a Python library that optimizes critical stages of the data science workflow. It simplifies data loading and preprocessing, facilitates exploratory data analysis (EDA), and streamlines feature engineering, machine learning modeling, and output visualization.
"Sinopsis" puede pertenecer a otra edición de este libro.
Librería: AwesomeBooks, Wallingford, Reino Unido
paperback. Condición: Very Good. Python Libraries for Data Science: Tech insights exploring the future 3 This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. . Nº de ref. del artículo: 7719-9798210693341
Cantidad disponible: 1 disponibles
Librería: Bahamut Media, Reading, Reino Unido
paperback. Condición: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee. Nº de ref. del artículo: 6545-9798210693341
Cantidad disponible: 1 disponibles
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Paperback. Condición: new. Paperback. The role of data scientists and analysts in data-driven decision-making cannot be overstated. Flexibility is a must when it comes to handling large datasets. This abstract introduces a Python library that optimizes critical stages of the data science workflow. It simplifies data loading and preprocessing, facilitates exploratory data analysis (EDA), and streamlines feature engineering, machine learning modeling, and output visualization. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798210693341
Cantidad disponible: 1 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Print on Demand. Nº de ref. del artículo: I-9798210693341
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L0-9798210693341
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L0-9798210693341
Cantidad disponible: Más de 20 disponibles
Librería: Ria Christie Collections, Uxbridge, Reino Unido
Condición: New. In. Nº de ref. del artículo: ria9798210693341_new
Cantidad disponible: Más de 20 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. The role of data scientists and analysts in data-driven decision-making cannot be overstated. Flexibility is a must when it comes to handling large datasets. This abstract introduces a Python library that optimizes critical stages of the data science workflow. It simplifies data loading and preprocessing, facilitates exploratory data analysis (EDA), and streamlines feature engineering, machine learning modeling, and output visualization. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798210693341
Cantidad disponible: 1 disponibles
Librería: AussieBookSeller, Truganina, VIC, Australia
Paperback. Condición: new. Paperback. The role of data scientists and analysts in data-driven decision-making cannot be overstated. Flexibility is a must when it comes to handling large datasets. This abstract introduces a Python library that optimizes critical stages of the data science workflow. It simplifies data loading and preprocessing, facilitates exploratory data analysis (EDA), and streamlines feature engineering, machine learning modeling, and output visualization. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9798210693341
Cantidad disponible: 1 disponibles