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Bioinformatics: Where code meets biology

A brief introduction to the future of healthcare You and I have 3 billion things in common. Or close to it anyway. And it’s not just you and I, everyone else is the same. What could all these things be? I like sports. Do you? How about machine learning? I’m

6 concepts of Andrew NG’s book: “Machine Learning Yearning”

“Technical Strategy for AI Engineers, In the Era of Deep Learning” Machine Learning Yearning is about structuring the development of machine learning projects. The book contains practical insights that are difficult to find somewhere else, in a format that is easy to share with teammates and collaborators. Most technical AI

When Identity Becomes an Algorithm

Meditations on AI, Reinforcement Learning and the Extended Phenotype Discussions on the interplay of humans and Artificial Intelligence tend to pose the issue in the language of opposition. However, according to the thinking of evolutionary biologist Richard Dawkins, tools such as AI can be better thought of as part of

How to Install OpenAI Gym in a Windows Environment

A step by step guide for getting OpenAI Gym up and running This is the second in a series of articles about reinforcement learning and OpenAI Gym. The first part can be found here. Introduction OpenAI Gym is an awesome tool which makes it possible for computer scientists, both amateur and

Data Science foundations: Know your data. Really, really, know it

Know your data, where it comes from, what’s in it, what it means. It all starts from there. If there is one piece of advice that I consistently give to every data person that’s starting out, whether they are going to be an analyst, scientist, or visualizer, this is it.

Image Segmentation using Python’s scikit-image module

Supervised segmentation Thresholding is a very basic segmentation process and will not work properly in a high-contrast image for which we will be needing more advanced tools. For this section, we will use an example image which is freely available and attempt to segment the head portion using supervised segmentation

Monte Carlo Without the Math

Okay, maybe a little math Monte Carlo Casino and Garden, Monaco Monte Carlo simulations are extremely common methods in the world of data science and analytics. They can be used for everything from business process optimization to physics simulation. Unfortunately, the math of Monte Carlo simulations is often unwieldy and can

Demystifying — Deep Image Prior

Introduction to image restoration using deep image prior. In this post, I will mainly be focusing on task of image restoration and how deep image prior can be used to solve this task. Introduction to Image Restoration Image restoration refers to the task of recovery of an unknown true image from

Explain Python classes and objects to my nephew (+advanced use)

It is common secret that Python programming language has a solid claim to being the fastest-growing major programming language witnessing an extraordinary growth in the last five years, as seen by Stack Overflow traffic. Based on data describing the Stack Overflow question views which go to late 2011, the growth

One Language Model to Rule Them All

OpenAI Masters Many Natural Language Tasks with a Single Unsupervised Model Natural language understanding(NLU) is one of the richest areas in deep learning which includes highly diverse tasks such as reaching comprehension, question-answering or machine translation. Traditionally, NLU models focus on solving only of those tasks and are useless when

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