This repo contains small projects related to the coding of algorithm functions and their applications in datasets:

• Clustering: DBSCAN_Notebook
• Deep Learning functions (.py files mostly): GradientDescent (notebook), Keras Architecture, Perceptron, Tensorflow_network, cross_entropy_function, perceptron_logical_operator, softmax_function
• Deep Learning mini-projects (notebooks): IMDB_In_Keras, StudentAdmissionsKeras

This project requires Python 2.7 and the following Python libraries installed:

• Python
• NumPy
• Pandas
• matplotlib
• scikit-learn
• keras
• tensorflow

It will also need to have software installed to run and execute a Jupyter Notebook

Download the files to a folder directory in your computer.

Codes are in notebook files with extensions .ipynb or Python files .py.

In a terminal or command window, run one of the following commands:

ipython notebook

or

jupyter notebook

This will open the Jupyter Notebook software. Select the notebook in your directory so it can appear in your browser.

To see the Python files, open Anaconda Spyder, open a Python file in your directory, select Run All

The datasets used in the notebooks have extensions .csv. Python files use mini sample datasets that are randomly generated.