Author Archives: Pradeep Pant

About Pradeep Pant

Software Engineer

Deep learning specialization notes

A couple of months back I have completed Deep Learning Specialization taught by AI guru Andrew NG. During the learning process, I have made personal notes from all the 5 courses.  Notes are based on lecture video and supplementary material provided and my own understanding of the topic. I have used lots of diagrams and code snippets which I made from… Read More »

Data Structures and Algorithms in Python – Graphs

Graph Implementation – Adjacency list We’ve used dictionaries to implement the adjacency list in Python which is the easiest way. To implement Graph ADT we’ll create two classes, Graph, which holds the master list of vertices, and Vertex, which will represent each vertex in the graph. Each Vertex uses a dictionary to keep track of… Read More »

Implemeting Data Structures and Algorithms in Python: Problems and solutions

Recently I have started using Python in a lot of places including writing algorithms for MI/data science,  so I thought to try to implement some common programming problems using data structures in Python. As I have mostly implemented in C/C++ and Perl. Let’s get started with a very basic problem. Anagram algorithm An algorithm will… Read More »

Choropleth Maps in Python

Choropleth maps are a great way to represent geographical data. I have done a basic implementation of two different data sets. I have used jupyter notebook to show the plots. World Power Consumption 2014 First do Plotly imports import plotly.graph_objs as go from plotly.offline import init_notebook_mode,iplot init_notebook_mode(connected=True) Next step is to fetch the dataset, we’ll use… Read More »

Stanford Machine learning class slides

Andrew NG Machine learning class is the best class so far which I took online. Apart from the course video sometimes lecture slides are also important for quick reference. For quite some time, I was looking for them as they are not available on course home. Here all the lecture slides available at: https://d396qusza40orc.cloudfront.net/ml/docs/slides/Lecture1.pdf Lecture2.pdf Lecture3.pdf Lecture4.pdf and so… Read More »