By Dmitry Zinoviev
Go from messy, unstructured artifacts kept in SQL and NoSQL databases to a neat, well-organized dataset with this fast reference for the busy info scientist. comprehend textual content mining, laptop studying, and community research; procedure numeric info with the NumPy and Pandas modules; describe and research information utilizing statistical and network-theoretical tools; and notice genuine examples of knowledge research at paintings. This one-stop answer covers the basic info technology you would like in Python.
Data technological know-how is without doubt one of the fastest-growing disciplines when it comes to educational study, scholar enrollment, and employment. Python, with its flexibility and scalability, is readily overtaking the R language for data-scientific initiatives. maintain Python data-science thoughts at your fingertips with this modular, fast connection with the instruments used to procure, fresh, study, and shop data.
This one-stop resolution covers crucial Python, databases, community research, traditional language processing, parts of computing device studying, and visualization. entry established and unstructured textual content and numeric facts from neighborhood documents, databases, and the net. manage, rearrange, and fresh the information. paintings with relational and non-relational databases, facts visualization, and straightforward predictive research (regressions, clustering, and choice trees). See how general info research difficulties are dealt with. and take a look at your hand at your individual strategies to numerous medium-scale initiatives which are enjoyable to paintings on and glance stable in your resume.
Keep this useful fast consultant at your facet even if you are a scholar, an entry-level info technological know-how expert changing from R to Python, or a professional Python developer who does not are looking to memorize each functionality and option.
What You Need:
You want a first rate distribution of Python 3.3 or above that comes with no less than NLTK, Pandas, NumPy, Matplotlib, Networkx, SciKit-Learn, and BeautifulSoup. an outstanding distribution that meets the necessities is Anaconda, on hand at no cost from www.continuum.io. when you plan to establish your individual database servers, you furthermore mght want MySQL (www.mysql.com) and MongoDB (www.mongodb.com). either applications are loose and run on home windows, Linux, and Mac OS.
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Extra resources for Data Science Essentials in Python: Collect - Organize - Explore - Predict - Value (The Pragmatic Programmers)
Data Science Essentials in Python: Collect - Organize - Explore - Predict - Value (The Pragmatic Programmers) by Dmitry Zinoviev