This course, part of the Data Science MicroMasters program, will introduce us to a collection of powerful, open-source, tools needed to analyze data and to conduct data science.
Data science, also known as data-driven science, is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.
Cover some of the most used python packages in the field of Data Science. A very effective overview on Jupyter notebook , Numerical Python , Matplotlib , Pandas , NLTK , Sci-Kit and lots of real time ongoing projects and famous data sets recorder in kaggle.
Downlaod Python 3x from the official website.
pip install numpy
pip install pandas
pip install pillow
pip install matplotlib
pip install -U scikit-learn
pip install nltk
or just download anaconda distribution for get all the necessary pacakges simultaneously.
git clone https://github.com/innat-2k14/Data-Science-In-Python
cd Data-Science-In-Python
jupyter notebook
Go do the desired notebook, files that end with '.ipynb'. To run the model, go to the menu then click on Cell > Run all
|-Python for Data Science
| |-Code with Matplotlib
| | |-Matplotlib_Exercise
| | |-Visualization
| |-Code with Numpy
| | |-Numerical Exercises
| | |-Numerical Python
| | |-Satellite Image Processing
| |-Code with Pandas
| | |-Exercise with Pandas
| | |-Pandas in Data Science
| |-Machine Learning Approach
| | |-European Soccer Regression Analysis using scikit-learn
| | |-K-Means
| | |-Weather Data Classification using Decision Trees
| |-NLP-Databases
| | |-Movie Reviews Using NLTK
| | |-Twitter API for Tweet Analysis
| | |-Working with Databases
| |-Planck
| |-Python Word Count
| |-Soocer Data Analysis - kaggle
Worth Watching The Joy of Stats - BBC Four
- Kaggle | Soccer Data Analysis
- Satellite Image Processing using Numpy package
- World Development Indicators | Data Visualization
- Folium Library for Geographic Overlays
- European Soccer Regression Analysis using scikit-learn
- Weather Data Clustering using k-Means
- Weather Data Classification using Decision Trees
- Twitter API for Tweet Analysis