SKU/Artículo: AMZ-B0DVPPWH8M
Pandas for Machine Learning [Hands-on]
Format:
Kindle
Detalles del producto
Disponibilidad:
Fuera de stock
Fuera de stock
Peso con empaque:
0.15 kg
0.15 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- This Book as a comprehensive and beginner-friendly guide for anyone looking to master essential concepts in Pandas, a fundamental library for data manipulation and analysis in Python. It covers a structured learning path, starting from the very basics of data structures like Series and DataFrames to more advanced topics such as data cleaning, transformation, and visualization.The discussion is tailored to readers who are new to Pandas or data analysis in general, ensuring that every concept is explained in a clear, step-by-step manner. Each topic is introduced with detailed explanations and followed by practical examples, making it easier for learners to not just understand the theory but also apply it in real-world scenarios.Key Features of This Book:Beginner-Friendly ApproachConcepts are broken down into simple, digestible parts, focusing on clarity. No prior experience with Pandas or advanced Python programming is required, making it accessible for everyone.Practical Examples with OutputEach concept is reinforced with multiple examples and their outputs to show how the code works in practice. This hands-on approach bridges the gap between learning and implementation.Step-by-Step Coverage of TopicsThe chat follows a logical progression, covering:Data Structures: Series and DataFramesData Manipulation: Filtering, selecting, and modifying dataData Cleaning: Handling missing data, removing duplicates, and type conversionsExploratory Data Analysis (EDA): Descriptive statistics, grouping, aggregation, and sortingData Transformation: Merging, reshaping, and working with time-series dataData Visualization: Quick and effective visualizations using .plot()Focus on Machine Learning ApplicationsThe content emphasizes how these Pandas concepts are directly applicable to the machine learning workflow, such as preprocessing data, handling missing values, feature engineering, and exploratory data analysis.Interactive and EngagingThe conversational style keeps the reader engaged, providing insights and tasks to practice independently. It encourages active learning by guiding readers to try out the examples on their own.Encourages Independent LearningWith challenges and additional tasks suggested throughout the discussion, readers are empowered to explore further, deepening their understanding of the concepts.Who Is This For?Students or beginners in data science and machine learning.Developers transitioning into data analysis.Anyone seeking a solid foundation in Pandas to prepare for more advanced topics like NumPy, Scikit-learn, or deep learning frameworks like TensorFlow or PyTorch.What Makes It Unique?The focus on real-world scenarios and how these concepts are directly applicable to solving practical problems in data analysis and machine learning sets this guide apart. Readers will not only gain technical skills but also learn how to think critically about data and its structure, which is an invaluable skill in the tech industry.By the end of this Book, readers will have the confidence to work with Pandas on their own, handle complex datasets, and make meaningful insights—setting the stage for further exploration into machine learning and AI.
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