For CU Data Science Training
This is material has been used in the Calcutta University - Data Science with Python lecture. Please download or the clone the repo to do the set up in your local system.
Table Of Contensts -
- 1.0 - Why Python?
- 1.1 - Anaconda Distribution and Jupyter Notebook
- 1.2 - Numpy
- 1.3 - Pandas
- 2.0 - Machine Learning with Python - Data Preprocessng
- 2.1 - Supervised - Regression Techniques
- 2.2 - Supervised - Classification Techniques
- 2.3 - Supervised - Model Selection and Model Tuning
- 2.4 - Unsupervised - Clustering Techniques
- 2.5 - Unsupersived - Dimesion Reduction Techniques
Why Python?
Python is a general purpose – open source, easy to learn language which now being used in various field like –
- Data Science - Numpy , Pandas , matplotlib , Sci-Py , Scikit Learn
- Deep Learning - Tensforflow , Pytorch , Keras
- Web development - Django
- Web development - Django
- Web scrapping - BeautifulSoup
- Game development and this list is never ending.
Along with this Python has a number of standard libraries which makes life of a programmer much easier since you don’t have to write all the code yourself. For example to call a web-service in Python you need to write hardly 4/5 lines of code.
Or by using scikit learn library you can create robust data science model very easily.
Getting Started Python for Data Science Tutorials - http://www.aritrasen.com/python-tutorials/
Regards, Aritra Sen
- LinkedIn - https://www.linkedin.com/in/aritrasen/