Practical Data Science with Python
Practical Data Science with Python
About the Book
Build a solid foundation for your career in data science efficiently! This book teaches you a variety of essential skills, quickly cuts into key topics, and clearly presents several modern data science projects.
About the Author
Table of Contents
-
Command Line Interpreter
- Software Preparation
- Getting used to a Unix shell
- Octothorpe
- pwd
- ls
- Some general tips
- ln
- cd
- mkdir
- touch
- cp
- mv
- cat
- head/tail
- less
- sort
- rm
- wc
- piping and redirection
- uniq
- grep
- tar
- locate
- find
- man
- sudo
- chmod
- nano/emacs/vi
- Exercises
-
Introducing the Python Programming Language
- Python Installation: Anaconda
- Where do I write?
- IPython
- Executing your first code
- What is Python?
- Variables
- Operators
- if/else
- Modules
- List and Dictionary
- Loops
- Functions
- Class
- Some Advanced Modules
- Exercises
-
Python Data Formats
- Standard Data Types
- How Data Types Work
- More on Data Types
- Serialization
- Further Reading
- Exercises
-
Data Visualization using Python
- Data Distribution
- Data Comparison
- Data Relationships
- Data Composition
- Advanced Graphing
- Google Map
- Exercises
-
Predictive Modelling using Python
- Supervised learning
- Unsupervised learning
- Example: Clustering of Stocks
- Exercises
-
SQL in Python
- MySQL
- SQLite
- SQL commands
- More about SQLite
- Other Select Database Topics
- Exercises
-
Web API
-
The
requestsmodule - Towards Web Scraping and Crawling
- Further Reading
- Exercises
-
The
-
Regular Expressions
- Metacharacters
- Grouping
- Further Reading
- Exercises
-
A/B Testing
- The Statistical Model of A/B tests
- Testing procedure
- Type I Error
- Type II Error
- Confidence Interval
- Sample size
- More on A/B testing
- References
- Exercises
-
Distributed Processing, MapReduce, and Hadoop
- The Definitions
- Installing VMware and CDH
- MySQL on CDH
- Python on Hadoop
- HDFS
- Exploring the Hadoop Ecosystem
- Further Reading
-
Apache Hadoop MapReduce
- Introduction to MapReduce
- Writing code for Distributed MapReduce Processing
- How MapReduce Works
- MapReduce Application Examples
- References
- Exercises
-
Spark
- Spark on YARN
- Spark Components
- Start Spark Shell
- Get data to RDD
- RDD operations: transformation and action
- Shared variables
- Spark Programming and Execution
- Further Reading
-
Capstone Project: Movie Recommendation System
- Problem Description
- Algorithms
- Project Steps
- References
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