Название: Data Science Essentials For Dummies Автор: Lillian Pierson Издательство: For Dummies Год: 2025 Страниц: 195 Язык: английский Формат: pdf (true), epub Размер: 10.1 MB
Feel confident navigating the fundamentals of Data Science.
Data Science Essentials For Dummies is a quick reference on the core concepts of the exploding and in-demand Data Science field, which involves data collection and working on dataset cleaning, processing, and visualization. This direct and accessible resource helps you brush up on key topics and is right to the point—eliminating review material, wordy explanations, and fluff—so you get what you need, fast.
Although popular programming languages like Java and C++ are good for developing stand-alone desktop applications, Python’s versatility makes it an ideal programming language for processing, analyzing, and visualizing data. For this reason, Python has earned a reputation of excellence in the Data Science field, where it has been widely adopted over the past decade. Python’s status as one of the more popular programming languages out there can be linked to the fact that it’s relatively easy to learn and it allows users to accomplish several tasks using just a few lines of code.
Though this book wasn’t designed to teach readers either the mechanics of programming or the implementation of Machine Learning algorithms, I have included plenty of helpful coding demonstrations and course recommendations over on this book’s companion website. If you want to learn to get started with using Python to implement Data Science, you may want to check it out. You can use Python to do anything, from simple mathematical operations to data visualizations and even Machine Learning and predictive analytics.
In Python, a library is a specialized collection of scripts that were written by someone else to perform specialized sets of tasks. To use specialized libraries in Python, you must first complete the installation process. After you install your libraries on your local hard drive, you can import any library’s function into a project simply by using the import statement. Though you can choose from countless libraries to accomplish different tasks in Python, the Python libraries most commonly used in Data Science are Matplotlib, NumPy, Pandas, Scikit-learn, and SciPy. The NumPy and SciPy libraries were specially designed for scientific uses, pandas was designed for optimal data analysis performance, and Matplotlib was designed for data visualization. Scikit-learn is Python’s premiere Machine Learning library.
• Strengthen your understanding of Data Science basics • Review what you've already learned or pick up key skills • Effectively work with data and provide accessible materials to others • Jog your memory on the essentials as you work and get clear answers to your questions
Perfect for supplementing classroom learning, reviewing for a certification, or staying knowledgeable on the job, Data Science Essentials For Dummies is a reliable reference that's great to keep on hand as an everyday desk reference.