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Weekly Selection – Feb 16, 2018

Bayes' Rule Applied


by William Koehrsen – 9 min read

The fundamental idea of Bayesian inference is to become "less wrong" with more data. The process is straightforward: we have an initial belief, known as a prior, which we update as we gain additional information.


Automatic feature engineering using Generative Adversarial Networks

by Hamaad Shah – 8 min read

The purpose of deep learning is to learn a representation of high dimensional and noisy data using a sequence of differentiable functions, i.e., geometric transformations, that can perhaps be used for supervised learning tasks among other tasks.


How to write a production-level code in Data Science?

by Venkatesh Pappakrishnan, Ph.D. – 11 min read

Ability to write a production-level code is one of the sought-after skills for a data scientist role – either posted explicitly or not. For a software engineer turned data scientist this may not sound like a challenging task as they might have already perfected their skill at developing production level codes and deployed into production several times.


10 things every aspiring data scientist needs to know

by Ayo Oluleye – 6 min read

The Harvard article "Data Scientist: The Sexiest Job of the 21st Century" first sparked my interest in the data science field. At the time, I had spent 3.5 years in management consulting and had built a great reputation building models and developing projections in MS Excel.


Generalized Linear Models

by Semih Akbayrak – 7 min read

It has been long time since I wrote the first machine learning for everyone article. From now on, I will try to publish articles more frequently.


Blockchains versus Traditional Databases

by Shaan Ray – 4 min read

Traditional databases use client-server network architecture. Here, a user (known as a client) can modify data, which is stored on a centralized server.


Building a Deep Neural Net In Google Sheets

by blake west – 7 min read

I want to show you that Deep Convolutional Neural Nets are not nearly as intimidating as they sound. And I’ll prove it by showing you an implementation of one that I made in Google Sheets. It’s available here.


Deep Learning with Python

by Vihar Kurama – 8 min read

The main reason behind deep learning is the idea that, artificial intelligence should draw inspiration from the brain. This perspective gave rise to the "Neural Network" terminology.


Fighting Cancer with Artificial Intelligence

by Andrew DeCotiis-Mauro – 9 min read

This August, I heard the words that no one wants to hear from their doctor: "You have cancer." I was diagnosed with a rare non-Hodgkin’s lymphoma. After a tumultuous couple of weeks of testing and second opinions it was clear that my prognosis was good.


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