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Essential Python De La Ciencia De Datos A La Automatizaci N

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Essential Python De La Ciencia De Datos A La Automatizaci N

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Author : Marcel Souza
language : es
Publisher: GAVEA LAB
Release Date :

Essential Python De La Ciencia De Datos A La Automatizaci N written by Marcel Souza and has been published by GAVEA LAB this book supported file pdf, txt, epub, kindle and other format this book has been release on with Business & Economics categories.

Sumérgete en el mundo de la programación con "Python Esencial: De la Ciencia de Datos a la Automatización". Este cautivador libro es tu compañero definitivo mientras exploras la emocionante aventura de aprender y dominar el lenguaje de programación Python. Imagina la emoción de escribir tus primeras líneas de código y ver cómo tus programas cobran vida. Con este libro en tus manos, estarás preparado para dominar desde los conceptos básicos hasta las complejidades de Python. Desde la ciencia de datos hasta la automatización, cada aspecto se aborda con detalle. Visualiza cómo tus proyectos cobran forma y funcionalidad, como piezas de un rompecabezas encajando perfectamente. Este libro ofrece valiosos consejos y trucos de programación que te permitirán crear aplicaciones eficientes y efectivas. Aprenderás a manipular datos, diseñar interfaces y automatizar tareas, llevando tus habilidades al siguiente nivel. Pero este libro no es solo un manual; es una historia apasionante sobre la creación y la innovación. Sumérgete en anécdotas y experiencias de programadores experimentados que te harán reír, reflexionar y sentirte identificado. Descubre los desafíos y triunfos que acompañan al mundo de la programación, y encuentra inspiración en la comunidad de apasionados por la tecnología. Ya seas un principiante curioso o un programador con experiencia, "Python Esencial: De la Ciencia de Datos a la Automatización" es tu recurso imprescindible. Deja que este libro sea tu guía mientras exploras el emocionante mundo de Python y descubres su potencial ilimitado en la ciencia, la tecnología y más allá.

Python Extreme Data Science

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Author : Diego Rodrígues
language : es
Publisher: StudioD21
Release Date : 2025-04-16

Python Extreme Data Science written by Diego Rodrígues and has been published by StudioD21 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-16 with Business & Economics categories.

Python Extreme Data Science es una guía completa, intensiva y técnicamente rigurosa para profesionales que desean dominar la ciencia de datos con Python en contextos reales de producción. Estructurado de forma modular, el contenido recorre desde la recolección, ingeniería y modelado de datos hasta la automatización, experimentación y operación en entornos escalables. Cada capítulo está desarrollado con base en el Protocolo TECHWRITE 2.2, asegurando una progresión didáctica eficiente, resolución de errores comunes y aplicación directa en pipelines complejos. El libro ofrece un enfoque práctico, orientado por problemas, utilizando bibliotecas y frameworks esenciales como Pandas, NumPy, Scikit-Learn, Matplotlib, Seaborn, XGBoost, LightGBM, además de técnicas avanzadas de preprocesamiento, validación cruzada e ingeniería de atributos. También incluye temas fundamentales como versionado de experimentos, deploy de modelos, explainability (interpretación de modelos) y evaluación de impacto en producción. Ideal para científicos de datos, ingenieros de machine learning, analistas técnicos y profesionales de datos que trabajan en entornos de alto rendimiento, esta obra propone una jornada práctica y objetiva, evitando superficialidades y yendo directo a los puntos críticos que diferencian un proyecto funcional de un fracaso técnico. La estructura es compatible con aplicaciones en cloud, edge, automatización con scripts e integración con sistemas de monitoreo. Ya sea para acelerar el ciclo de experimentación o escalar soluciones con robustez, Python Extreme Data Science entrega lo más relevante de la ingeniería aplicada a la ciencia de datos moderna. Python, Data Science, Machine Learning, Ingeniería de Datos, Feature Engineering, Modelado Predictivo, Pipelines, Automatización, Scikit-Learn, XGBoost, Producción, Validación, Deploy, Interpretación de Modelos.

Python Extreme Data Science

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Author : STUDIOD21 SMART TECH CONTENT
language : es
Publisher: Independently Published
Release Date : 2025-04-17

Python Extreme Data Science written by STUDIOD21 SMART TECH CONTENT and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-17 with Computers categories.

Python For Data Science

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Author : Muddana A Lakshmi Lakshmi
language : en
Publisher: Springer
Release Date : 2024-04-05

Python For Data Science written by Muddana A Lakshmi Lakshmi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-05 with Computers categories.

The book is designed to serve as a textbook for courses offered to undergraduate and graduate students enrolled in data science. This book aims to help the readers understand the basic and advanced concepts for developing simple programs and the fundamentals required for building machine learning models. The book covers basic concepts like data types, operators, and statements that enable the reader to solve simple problems. As functions are the core of any programming, a detailed illustration of defining & invoking functions and recursive functions is covered. Built-in data structures of Python, such as strings, lists, tuples, sets, and dictionary structures, are discussed in detail with examples and exercise problems. Files are an integrated part of programming when dealing with large data. File handling operations are illustrated with examples and a case study at the end of the chapter. Widely used Python packages for data science, such as Pandas, Data Visualization libraries, and regular expressions, are discussed with examples and case studies at the end of the chapters. The book also contains a chapter on SQLite3, a small relational database management system of Python, to understand how to create and manage databases. As AI applications are becoming popular for developing intelligent solutions to various problems, the book includes chapters on Machine Learning and Deep Learning. They cover the basic concepts, example applications, and case studies using popular frameworks such as SKLearn and Keras on public datasets

Python Data Science

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Author : Andrew Park
language : en
Publisher:
Release Date : 2020-11-14

Python Data Science written by Andrew Park and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-14 with Computers categories.

If you want to learn more about Data Science or how to master it with the Python Programming Language, then keep reading. Data Science is one of the biggest buzzwords in the business world nowadays. Many businesses know the importance of collecting information, but as they can collect so much data in a short period, the real question is: "what is the next step?" Data Science includes all the different steps that you take with the data: collecting and cleaning them if they come from more than one source, analyzing them, applying Machine Learning algorithms and models, and then presenting your findings from the analysis with some good Data Visualizations. And this is what you will learn in Python Data Science. You will learn about the main steps that are needed to correctly implement Data Science techniques and the algorithms to help you sort through the data and see some amazing results. Some of the topics that we will discuss inside include: What data science is all about and why so many companies are using it to give them a competitive edge. Why Python and how to use it to implement Data Science What is the intersection between Machine Learning and Data Science and how to combine them The main Data Structures & Object-Oriented Python, with practical codes and exercises to use Python Functions and Modules in Python The 7 most important algorithms and models in Data Science Data Aggregation and Group Operations 9 important Data Mining techniques in Data Science Interaction with databases and data in the cloud And Much More! Where most books only focus on how collecting and cleaning the data, this book goes further, providing guidance on how to perform a proper analysis in order to extract precious information that may be vital for a business. Don't miss the opportunity to learn more about these topics. Even if you have never implemented Data Science techniques, learning them is easier than it looks. You just need the right guidance. And Python Data Science provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn, the techniques to manipulate and process datasets, the principles of Python programming, and its most important real-world applications. Would You Like To Know More? Scroll Up And Click The BUY NOW Button To Get Your Copy Now!

Data Science For Beginners

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Author : Andrew Park
language : en
Publisher:
Release Date : 2021-02-09

Data Science For Beginners written by Andrew Park and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-09 with categories.

★ 55% OFF for Bookstores! Now at $39.95 instead of $49.95! ★ Your Customers Will Never Stop To Use This Complete Guide! Did you know that according to Harvard Business Review the Data Scientist is the sexiest job of the 21st century? And for a reason! If "sexy" means having rare qualities that are much in demand, data scientists are already there. They are expensive to hire and, given the very competitive market for their services, difficult to retain. There simply aren't a lot of people with their combination of scientific background and computational and analytical skills. Data Science is all about transforming data into business value using math and algorithms. And needless to say, Python is the must-know programming language of the 21st century. If you are interested in coding and Data Science, then you must know Python to succeed in these industries! Data Science for Beginners is the perfect place to start learning everything you need to succeed. Contained within these four essential books are the methods, concepts, and important practical examples to help build your foundation for excelling at the discipline that is shaping the modern word. This bundle is perfect for programmers, software engineers, project managers and those who just want to keep up with technology. With these books in your hands, you will: ● Learn Python from scratch including the basic operations, how to install it, data structures and functions, and conditional loops ● Build upon the fundamentals with advanced techniques like Object-Oriented Programming (OOP), Inheritance, and Polymorphism ● Discover the importance of Data Science and how to use it in real-world situations ● Learn the 5 steps of Data Analysis so you can comprehend and analyze data sitting right in front of you ● Increase your income by learning a new, valuable skill that only a select handful of people take the time to learn ● Discover how companies can improve their business through practical examples and explanations ● And Much More! This bundle is essential for anyone who wants to study Data Science and learn how the world is moving to an open-source platform. Whether you are a software engineer or a project manager, jump to the next level by developing a data-driven approach and learning how to define a data-driven vision of your business! Order Your Copy of the Bundle and Let Your Customers Start Their New Career Path Today!

Practical Data Science With Python

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Author : Nathan George
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-30

Practical Data Science With Python written by Nathan George and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-30 with Computers categories.

Learn to effectively manage data and execute data science projects from start to finish using Python Key FeaturesUnderstand and utilize data science tools in Python, such as specialized machine learning algorithms and statistical modelingBuild a strong data science foundation with the best data science tools available in PythonAdd value to yourself, your organization, and society by extracting actionable insights from raw dataBook Description Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science. The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by working through the examples. The code has been broken down into small chunks (a few lines or a function at a time) to enable thorough discussion. As you progress, you will learn how to perform data analysis while exploring the functionalities of key data science Python packages, including pandas, SciPy, and scikit-learn. Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments. By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source. What you will learnUse Python data science packages effectivelyClean and prepare data for data science work, including feature engineering and feature selectionData modeling, including classic statistical models (such as t-tests), and essential machine learning algorithms, such as random forests and boosted modelsEvaluate model performanceCompare and understand different machine learning methodsInteract with Excel spreadsheets through PythonCreate automated data science reports through PythonGet to grips with text analytics techniquesWho this book is for The book is intended for beginners, including students starting or about to start a data science, analytics, or related program (e.g. Bachelor’s, Master’s, bootcamp, online courses), recent college graduates who want to learn new skills to set them apart in the job market, professionals who want to learn hands-on data science techniques in Python, and those who want to shift their career to data science. The book requires basic familiarity with Python. A "getting started with Python" section has been included to get complete novices up to speed.

Python Data Science Handbook

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Author : Jake VanderPlas
language : en
Publisher: O'Reilly Media
Release Date : 2023-01-17

Python Data Science Handbook written by Jake VanderPlas and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-17 with categories.

Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all--IPython, NumPy, pandas, Matplotlib, scikit-learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you'll learn how: IPython and Jupyter provide computational environments for scientists using Python NumPy includes the ndarray for efficient storage and manipulation of dense data arrays Pandas contains the DataFrame for efficient storage and manipulation of labeled/columnar data Matplotlib includes capabilities for a flexible range of data visualizations Scikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithms

Python Data Science

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Author : Andrew Park
language : en
Publisher:
Release Date : 2020-11-14

Python Data Science

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Author : Andrew Park
language : en
Publisher:
Release Date : 2019-12-17

Python Data Science written by Andrew Park and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-17 with categories.

If you want to learn more about Data Science or how to master it with the Python Programming Language, then keep reading. Data Science is one of the biggest buzzwords in the business world nowadays. Many businesses know the importance of collecting information, but as they can collect so much data in a short period, the real question is: "what is the next step?" Data Science includes all the different steps that you take with the data: collecting and cleaning them if they come from more than one source, analyzing them, applying Machine Learning algorithms and models, and then presenting your findings from the analysis with some good Data Visualizations. And this is what you will learn in Python Data Science. You will learn about the main steps that are needed to correctly implement Data Science techniques and the algorithms to help you sort through the data and see some amazing results. Some of the topics that we will discuss inside include: What data science is all about and why so many companies are using it to give them a competitive edge. Why Python and how to use it to implement Data Science What is the intersection between Machine Learning and Data Science and how to combine them The main Data Structures & Object-Oriented Python, with practical codes and exercises to use Python Functions and Modules in Python The 7 most important algorithms and models in Data Science Data Aggregation and Group Operations 9 important Data Mining techniques in Data Science Interaction with databases and data in the cloud Where most books only focus on how collecting and cleaning the data,this book goes further, providing guidance on how to perform a proper analysis in order to extract precious information that may be vital for a business. Don't miss the opportunity to learn more about these topics. Even if you have never implemented Data Science techniques, learning them is easier than it looks. You just need the right guidance. And Python Data Science provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn, the techniques to manipulate and process datasets, the principles of Python programming, and its most important real-world applications. Would You Like To Know More? Scroll to the top of the page and click the "Buy now" button to get your copy now!

Essential Python De La Ciencia De Datos A La Automatizaci N

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