English | 2018 | ISBN: 1789950069 | 490 Pages | True PDF, EPUB | 174 MB
Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis.
Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You’ll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You’ll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects.
Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis – pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You’ll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.
What you will learn
- A new toolset that has been carefully crafted to meet for your data analysis challenges
- Full and detailed case studies of the toolset across several of today’s key industry contexts
- Become super productive with a new toolset across Python and Jupyter Notebook
- Look into the future of data science and which directions to develop your skills next