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Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data
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Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data
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.
Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data
Artículo nº.: 43287399

Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data

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Artículo nº.: 43287399

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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.
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Lo que más destaca

Hands-On Approach
Engages learners through practical exercises, ensuring users gain real-world skills in data analysis that are directly applicable in various professional scenarios.
Comprehensive Coverage
Covers a wide array of data science techniques, making it suitable for both beginners and experienced professionals looking to deepen their knowledge in Python-based data analysis.
Insightful Analysis
Focuses on generating meaningful insights from data, empowering users to not only analyze but also interpret data effectively to inform decision-making processes.

Detalles del producto

Discover tools, techniques, and insights to extract meaningful data with hands-on examples. Explore Practical Data Science with Python at Ubuy Aruba.
  • Comprehensive guide for learning data science with Python
  • Hands-on examples to learn tools and techniques for data extraction
  • Focuses on extracting insights from data
  • Ideal for practical application of Python in data science
  • Useful for gaining proficiency in data analysis and interpretation
  • Written to facilitate learning through real-world examples
Publisher Packt Publishing
Publication date September 30, 2021
Language English
Print length 534 pages
ISBN-10 1801071977
ISBN-13 978-1801071970
Item Weight 2.53 pounds (1.15 kg)
Dimensions 7.5 x 1.4 x 9.25 inches (19.1 x 3.6 x 23.5 cm)

¿Quién debería comprarlo?

Suitable For
  • Aspiring Data Scientists

    Ideal for beginners aiming to learn practical data analysis techniques using Python in a hands-on manner.

  • Industry Professionals

    Useful for professionals looking to upskill in data science methods and enhance their analytical capabilities.

  • Students in STEM

    Beneficial for students studying science, technology, engineering, or mathematics who want to gain practical data skills.

Not Suitable For
  • Experienced Data Scientists

    May not offer advanced insights or techniques for those with extensive experience in data science and Python.

DESCRIPCIÓN DEL PRODUCTO

Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data

Aviso sobre suplementos dietéticos

Statements regarding dietary supplements have not been evaluated by the Food and Drug Administration and are not intended to diagnose, treat, cure, or prevent any disease or health condition.


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Preguntas y respuestas de los clientes

  • Pregunta: What is the primary focus of 'Practical Data Science with Python'?

    Respuesta: The primary focus of 'Practical Data Science with Python' is to equip readers with practical skills needed to extract insights from data using Python. The book covers essential tools and techniques, emphasizing hands-on examples that make concepts easier to grasp. By going through real-world scenarios, readers can see how to apply data science principles in various fields, such as finance, healthcare, and marketing, enhancing their ability to analyze and interpret data effectively.
  • Pregunta: Who is this book intended for?

    Respuesta: 'Practical Data Science with Python' is targeted toward aspiring data scientists, analysts, and students familiar with Python programming who want to apply it in data analysis. The book is also suitable for professionals looking to deepen their understanding of data science principles. By providing practical examples, it caters to various experience levels, making it an ideal resource for anyone eager to leverage data for decision-making and business insights.
  • Pregunta: What tools and techniques can I learn from this book?

    Respuesta: Readers of 'Practical Data Science with Python' will learn a variety of tools and techniques, including data manipulation with pandas, data visualization using matplotlib and seaborn, machine learning with scikit-learn, and more. The practical approach allows readers to implement these tools in real projects, thereby reinforcing their learning through application. This hands-on experience is invaluable for those looking to build a solid foundation in data science and analytics.
  • Pregunta: Does the book cover machine learning concepts?

    Respuesta: Yes, 'Practical Data Science with Python' delves into machine learning concepts, illustrating how to apply supervised and unsupervised learning techniques. Readers will explore regression models, classification algorithms, and clustering, all backed by practical examples. Understanding these concepts allows data practitioners to make informed predictions and analysis based on historical data, which is crucial for businesses looking to leverage machine learning for growth.
  • Pregunta: Is prior programming knowledge required to benefit from this book?

    Respuesta: While basic familiarity with Python is helpful, 'Practical Data Science with Python' is designed to guide readers through the necessary concepts at a manageable pace. Readers with some foundational knowledge can easily follow along and enhance their skills. As the book progressively builds upon concepts, it also serves as a resource for those eager to strengthen their programming and data handling abilities in practical applications.
  • Pregunta: What types of data analyses are covered in this book?

    Respuesta: 'Practical Data Science with Python' covers a range of data analyses, from exploratory data analysis to more complex predictive modeling techniques. Readers learn to conduct data cleaning, visualization, and statistical analysis, enabling them to draw insightful conclusions from varied datasets. This broad spectrum allows practitioners to tackle real-world data scenarios across industries, improving their analytical decision-making capabilities.
  • Pregunta: Are there exercises or projects included for practice?

    Respuesta: Yes, the book includes exercises and projects designed to reinforce the knowledge and skills acquired from each chapter. These practical applications provide valuable opportunities for readers to implement what they have learned in a hands-on manner, making the learning experience engaging and effective. Such exercises are beneficial for solidifying concepts and ensuring readers can transfer their knowledge to real-world situations.
  • Pregunta: Can I enhance my career prospects by learning from this book?

    Respuesta: Absolutely! By mastering the content of 'Practical Data Science with Python', readers can significantly enhance their career prospects in the field of data science and analytics. The skills acquired from the book are highly sought after across various industries, with companies looking for professionals who can interpret and utilize data effectively. This practical knowledge positions readers to take on roles such as data analyst, data scientist, or business intelligence specialist.
  • Pregunta: What areas of data science does this book emphasize?

    Respuesta: 'Practical Data Science with Python' emphasizes a rich blend of data manipulation, analysis, and visualization techniques, which are foundational in the field of data science. It also showcases the integration of data collection, preprocessing, and interpreting results through real-life examples. This focus helps readers gain a comprehensive understanding of the data science lifecycle, making it easier to apply these principles in various projects and job roles.
  • Pregunta: Where can I buy 'Practical Data Science with Python' in Aruba?

    Respuesta: You can purchase 'Practical Data Science with Python' from Ubuy in Aruba. Ubuy offers a wide selection of books and educational resources, making it a great option for those looking to enhance their knowledge in data science and analytics.

Intelligence & Semantics Editorial Review

Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data is an excellent introduction for those new to data science and Python. The author, Nathan George, engages readers by starting with the basics and gradually moving to more complex concepts, making it ideal for beginners. The book covers essential Python libraries such as Pandas and NumPy, and delves into vital data science techniques like machine learning, data wrangling, and ethics surrounding data use. Readers appreciate the practical coding examples while having access to a GitHub repository for further exploration, ensuring comprehensive learning throughout the process.

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Ventajas

  • Thorough coverage of Python basics and data science tools
  • Practical examples enhance understanding of concepts
  • Focus on ethical use of data science
  • Incorporates a variety of essential Python libraries
  • Includes GitHub resources for hands-on practice

Desventajas

  • May require basic Python knowledge for best results

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Características y beneficios

  • Learn core data science concepts with real-world examples
  • Strengthen your grip on basic and advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming
  • Build a solid foundation to become proficient in data science
  • Learn to perform data analysis using key data science Python packages
  • Learn text analytics techniques and create automated data science reports using Python
  • Intended for beginners, college graduates, and professionals who want to learn hands-on data science techniques in Python

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