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- Data Analysis with Python. A Modern Approach
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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.
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.
- 1. Programming and Data Science – A New Toolset
- 2. Python and Jupyter Notebooks to Power your Data Analysis
- 3. Accelerate your Data Analysis with Python Libraries
- 4. Publish your Data Analysis to the Web - the PixieApp Tool
- 5. Python and PixieDust Best Practices and Advanced Concepts
- 6. Analytics Study: AI and Image Recognition with TensorFlow
- 7. Analytics Study: NLP and Big Data with Twitter Sentiment Analysis
- 8. Analytics Study: Prediction - Financial Time Series Analysis and Forecasting
- 9. Analytics Study: Graph Algorithms - US Domestic Flight Data Analysis
- 10. The Future of Data Analysis and Where to Develop your Skills
- Title: Data Analysis with Python. A Modern Approach
- Author: David Taieb
- Original title: Data Analysis with Python. A Modern Approach
- ISBN: 9781789958195, 9781789958195
- Date of issue: 2018-12-31
- Format: Ebook
- Item ID: e_15f9
- Publisher: Packt Publishing