Data science is a relatively new knowledge domain which is
used by various organizations to make data driven decisions. Data
scientists have to wear various hats to work with data and to derive
value from it. The Python programming language, beyond having conquered
the scientific community in the last decade, is now an indispensable
tool for the data science practitioner and a must-know tool for every
aspiring data scientist. Using Python will offer you a fast, reliable,
cross-platform, and mature environment for data analysis, machine
learning, and algorithmic problem solving.
This comprehensive guide helps you move beyond the hype and transcend
the theory by providing you with a hands-on, advanced study of data
science.
Beginning with the essentials of Python in data science, you will
learn to manage data and perform linear algebra in Python. You will move
on to deriving inferences from the analysis by performing inferential
statistics, and mining data to reveal hidden patterns and trends. You
will use the matplot library to create high-end visualizations in Python
and uncover the fundamentals of machine learning. Next, you will apply
the linear regression technique and also learn to apply the logistic
regression technique to your applications, before creating
recommendation engines with various collaborative filtering algorithms
and improving your predictions by applying the ensemble methods.
Finally, you will perform K-means clustering, along with an analysis
of unstructured data with different text mining techniques and
leveraging the power of Python in big data analytics.
