Data science projects have many flexible parts, and it takes practice and skill to get all the code, algorithms, datasets, formats, and visualizations to work together. This book guides you through five real-world projects, including tracking disease outbreaks based on news headlines, analyzing social networks, and finding patterns in ad click data.
"Python Data Science Projects in Action" goes beyond superficial theory and simple examples. As you work through each project, you'll learn how to solve common problems such as missing data, messy data, and algorithms that don't fit the model you built. You'll learn detailed setup instructions and comprehensive solutions to common failures. Finally, by completing these projects, you will gain confidence in your skills.
This book not only provides rich cases, but also introduces the knowledge required for data science work with Python through a very rigorous and complete structure. This book is explained through 5 cases. The first case introduces how to deal with content related to probability theory in Python, which is not available in many other books. If you study professional books related to probability theory, it must be very painful, after all, you do not intend to become a probability expert. On the subject of experts. The content introduced in the first case of this book can meet most of the needs related to probability theory involved in your work. The second case introduces how to use statistical knowledge in Python to process data. Here, a lot of boring statistical knowledge is explained in a very clever way, so that you can have a deeper understanding of these contents. The third case introduces how to use Python to process data related to geographic information, and introduces how to use the scikit-learn library to achieve efficient clustering. The fourth case introduces how to use today's popular natural language processing technology to deal with practical problems. The fifth case introduces the content related to network theory and supervised learning. Through the study of these 5 cases, I believe that you will have a deeper understanding of Python and data science, and apply these technologies to your work and study.
Excerpted from the translator's preface of "Python Data Science Project Combat"
