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Books > Computing & IT > Applications of computing > Databases > Data mining
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Python Data Science Essentials - (Paperback, 2nd Revised edition)
Loot Price: R1,290
Discovery Miles 12 900
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Python Data Science Essentials - (Paperback, 2nd Revised edition)
Expected to ship within 10 - 15 working days
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Become an efficient data science practitioner by understanding
Python's key concepts About This Book * Quickly get familiar with
data science using Python 3.5 * Save time (and effort) with all the
essential tools explained * Create effective data science projects
and avoid common pitfalls with the help of examples and hints
dictated by experience Who This Book Is For 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. What You Will Learn * Set
up your data science toolbox using a Python scientific environment
on Windows, Mac, and Linux * Get data ready for your data science
project * Manipulate, fix, and explore data in order to solve data
science problems * Set up an experimental pipeline to test your
data science hypotheses * Choose the most effective and scalable
learning algorithm for your data science tasks * Optimize your
machine learning models to get the best performance * Explore and
cluster graphs, taking advantage of interconnections and links in
your data In Detail Fully expanded and upgraded, the second edition
of Python Data Science Essentials takes you through all you need to
know to suceed in data science using Python. Get modern insight
into the core of Python data, including the latest versions of
Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the
fundamentals with beautiful data visualizations with Seaborn and
ggplot, web development with Bottle, and even the new frontiers of
deep learning with Theano and TensorFlow. Dive into building your
essential Python 3.5 data science toolbox, using a single-source
approach that will allow to to work with Python 2.7 as well. Get to
grips fast with data munging and preprocessing, and all the
techniques you need to load, analyse, and process your data.
Finally, get a complete overview of principal machine learning
algorithms, graph analysis techniques, and all the visualization
and deployment instruments that make it easier to present your
results to an audience of both data science experts and business
users. Style and approach The book is structured as a data science
project. You will always benefit from clear code and simplified
examples to help you understand the underlying mechanics and
real-world datasets.
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