What you will Learn
- Basics of the python programming
- Python programming fundamental techniques such as lambdas, reading and manipulating csv files, and the numpy library.
- Data manipulation and cleaning techniques using the popular python pandas data science library
- How to use functions such as groupby, merge, and pivot tables effectively
- Information visualization basics, with a focus on reporting and charting using the matplotlib library
- How to realize design decisions in the framework
- Variety of basic statistical charts
- Structuring and visualizing data
- How machine learning is different than descriptive statistics
- learn toolkit through a tutorial
- learn predictive modelling methods
- Advanced techniques, such as building ensembles, and practical limitations of predictive models
- Text mining and text manipulation basics
- How text is handled by python, the structure of text both to the machine and to humans
- Overview of the nltk framework for manipulating text
- Regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processesnetwork analysis through tutorials using the NetworkX library
- Basic natural language processing methods to text
- Network analysis through tutorials using the NetworkX library
- Concept of connectivity and network robustness
- Importance of a node in a network
- Evolution of networks over time and cover models of network generation and the link prediction problem.
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