Introducing Data Science: Big Data, Machine Learning, and more using Python tools is a comprehensive introduction to the field of data science, aimed at beginners with little or no background in statistics or programming. The book covers a wide range of topics, from data collection and cleaning to data visualization and machine learning. The book is divided into four parts. Part one covers the basics of data science, including data structures and algorithms, statistical analysis, and programming with Python.
Part two focuses on data collection and cleaning, covering topics such as web scraping, database management, and data preprocessing. Part three covers data visualization, exploring techniques for creating effective charts and graphs using Python and other tools. Part four focuses on machine learning, including supervised and unsupervised learning, neural networks, and deep learning. Overall, “Introducing Data Science” is an excellent resource for beginners looking to learn the basics of data science. The book is well-written, easy to understand, and covers a wide range of topics in a concise and accessible way. If you’re looking to get started with data science, this book is a great place to start.
Table of contents
1 Data science in a big data world
2 The data science process
3 Machine learning
4 Handling large data on a single computer
5 First steps in big data
6 Join the NoSQL movement
7 The rise of graph databases
8 Text mining and text analytics
9 Data visualization to the end user