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Quickly get familiar with data science using Python
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Save tons of time through this reference book with all the essential tools illustrated and explained
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Create effective data science projects and avoid common pitfalls with the help of examples and hints dictated by experience
The book starts by introducing you to setting up your essential data science toolbox. Then it will guide you across all the data munging and preprocessing phases. This will be done in a manner that explains all the core data science activities related to loading data, transforming and fixing it for analysis, as well as exploring and processing it. Finally, it will complete the overview by presenting you with the main machine learning algorithms, the graph analysis technicalities, and all the visualization instruments that can make your life easier in presenting your results.
In this walkthrough, structured as a data science project, you will always be accompanied by clear code and simplified examples to help you understand the underlying mechanics and real-world datasets.
If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills.
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Set up your data science toolbox using a Python scientific environment on Windows, Mac, and Linux
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Get data ready for your data science project
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Manipulate, fix, and explore data in order to solve data science problems
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Set up an experimental pipeline to test your data science hypothesis
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Choose the most effective and scalable learning algorithm for your data science tasks
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Optimize your machine learning models to get the best performance
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Explore and cluster graphs, taking advantage of interconnections and links in your data