Python Workshop, 9th LinuxFest, May 2017
- Basic understanding of programming
- Experience writing code in a modern programming language(C++, Java, JavaScript, Php…)
- A system with Python 3 installed(3.4 is preferred)
- A text-editor or IDE(PyCharm is preferred)
- Basic Knowledge of Machine Learning Concept(Not Necessary)
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Introduction to NumPy:
- Python Data Structures
- Python Containers
- Introduction to NumPy Package
- Working with NumPy Arrays
- Indexing and Slicing
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Introduction to Plotting Tools:
- Plotting Data with Matplotlib
- Smoothing Data in Matplotlib
- Using Seaborn
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Introduction to Pandas:
- Pandas Overview
- Series in Pandas
- DataFrames in Pandas
- Multi Level Indices
- Aggregation
- Working with Large Datasets
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Introduction to Scipy Stats:
- Continuous and Discrete Distributions
- Useful Functions for Statistical Experiments
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Introduction to Scikit:
- Slight Introduction to Machine Learning
- Preprocessing
- Learning a Model with Scikit
- Testing the Model
- Evaluation Methods
- Useful Functions for Model Selection
- Model Persistence
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Examples:
- Word Anagrams with NumPy
- Baby Names with Pandas
- A Statistical Simulation
- Learning and Evaluating Various Models with Scikit