Search all library resources for data science topics limited to books and Ebooks.
Featured titles include:
Cleaning Data for Effective Data Science: Doing the Other 80% of the Work with Python, R, and Command-line Tools by
Think about your data intelligently and ask the right questionsKey FeaturesMaster data cleaning techniques necessary to perform real-world data science and machine learning tasksSpot common problems with dirty data and develop flexible solutions from first principlesTest and refine your newly acquired skills through detailed exercises at the end of each chapterBook DescriptionData cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way.
Data Science Fundamentals Pocket Primer by
As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data science using Python 3 and other computer applications. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, linear algebra, and regular expressions. The book includes numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available. FEATURES: Includes a concise introduction to Python 3 and linear algebra. Provides a thorough introduction to data visualization and regular expressions. Covers NumPy, Pandas, R, and SQL. Introduces probability and statistical concepts. Features numerous code samples throughout. Companion files with source code and figures.
Data Science in Societal Applications: Concepts and Implications by
Includes contributions from academia and industry experts. Provides an insight into the practical applications and theoretical foundations of data science. Covers techniques for data analytics, future research directions, and guidance on data analytics.
The Data Science Workshop: Learn How You Can Build Machine Learning Models and Create Your Own Real-world Data Science Projects by
Where there's data, there's insight. With so much data being generated, there is immense scope to extract meaningful information that'll boost business productivity and profitability. By learning to convert raw data into game-changing insights, you'll open new career paths and opportunities.
The Data Visualization Workshop: A Self-paced, Practical Approach to Transforming Your Complex Data Into Compelling, Captivating Graphics by
Explore a modern approach to visualizing data with Python and transform large real-world datasets into expressive visual graphics using this beginner-friendly workshop. Key Features: Discover the essential tools and methods of data visualization. Learn to use standard Python plotting libraries such as Matplotlib and Seaborn. Gain insights into the visualization techniques of big companies.
Interactive Data Visualization with Python: Present Your Data As an Effective and Compelling Story by
Create your own clear and impactful interactive data visualizations with the powerful data visualization libraries of Python. Key Features: Study and use Python interactive libraries, such as Bokeh and Plotly. Explore different visualization principles and understand when to use which one. Create interactive data visualizations with real-world data.
Unmasking AI: My Mission to Protect what is Human in a World of Machines by
Unmasking AI goes beyond the headlines about existential risks produced by Big Tech. It is the remarkable story of how Buolamwini uncovered what she calls “the coded gaze”—the evidence of encoded discrimination and exclusion in tech products—and how she galvanized the movement to prevent AI harms by founding the Algorithmic Justice League. Applying an intersectional lens to both the tech industry and the research sector, she shows how racism, sexism, colorism, and ableism can overlap and render broad swaths of humanity “excoded” and therefore vulnerable in a world rapidly adopting AI tools. Computers, she reminds us, are reflections of both the aspirations and the limitations of the people who create them.
Search online journals for data science topics or browse online journals related to computer science or statistics.