Demystifing Graph Algorithms

Demystifing Graph Algorithms

This is a complete guide to graph algorithms that you can rely on to practice for your next technical interview. No matter how complicated these concepts may seem, repeatedly getting familiar with different techniques and problems will make you more competent at solving them.

Datacast Episode 6: Data Science in the Travel Industry with Ewan Nicolson

Datacast Episode 6: Data Science in the Travel Industry with Ewan Nicolson

Ewan Nicolson has been working professionally with numbers and computers for the past 13 years. During the past 6 years at Skyscanner, he has seen the data team grow from 2 analysts based in Edinburgh to a global team of 25+ data scientists making a global impact.

Datacast Episode 5: Applied Statistics in Data Science with Christopher Peters

Datacast Episode 5: Applied Statistics in Data Science with Christopher Peters

Christopher Peters is a full-stack data scientist at Zapier. He was both Zapier and Treehouse's first data scientist. Prior to his work as a data scientist, he was a research associate at LSU’s Center for Energy Studies where he was an energy economist. He has a real passion for working with, sharing, visualizing and analyzing data of all kinds using statistical, visual and machine learning techniques.

Greedy Algorithm and Dynamic Programming

Greedy Algorithm and Dynamic Programming

In an algorithm design there is no one 'silver bullet' that is a cure for all computation problems. Different problems require the use of different kinds of techniques. A good programmer uses all these techniques based on the type of problem. In this blog post, I am going to cover 2 fundamental algorithm design principles: greedy algorithms and dynamic programming

Divide and Conquer Algorithms

Divide and Conquer Algorithms

A very popular algorithmic paradigm, a typical Divide and Conquer algorithm solves a problem using following three steps:

  • Divide: Break the given problem into subproblems of same type.

  • Conquer: Recursively solve these subproblems

  • Combine: Appropriately combine the answers

Datacast Episode 3: How to Be a Social Media Data Whiz with Leni Krsova

Datacast Episode 3: How to Be a Social Media Data Whiz with Leni Krsova

Leni Krsová is social media data analyst from the Czech Republic, currently based in Prague. At the beginning of her career, she worked for Czech TV, a public broadcaster in the country, as a social media editor but switched quickly from marketing to the path of a data analyst. Since then she is interested more and more in data analysis of social media and online news media data with R, data privacy and academic research in these fields. She is planning to start her Ph.D. studies in near future.

Datacast Episode 2: Becoming a Deep Learning Expert with Deep Narain Singh

Datacast Episode 2: Becoming a Deep Learning Expert with Deep Narain Singh

Deep Narain Singh is Data Scientist with specialization in machine learning and deep learning. He has extensive work experience in building NLP/Computer Vision products using AI/ML/DL. He has spent 12 years in industry working with startups and large scale companies. He holds a Master’s degree in Data Science from the University Of New Haven/Galvanize and completed his undergraduate in Civil Engineering from NIT Jaipur.