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Weekly Selection – Jun 15, 2018

Embedding Machine Learning Models to Web Apps

By Chamin Nalinda – 12 min read

The best way to learn data science is by doing it, and there’s no other alternative. From this post, I am going to reflect my learning on how I developed a machine learning model, which can classify movies reviews as positive or negative, and how I embed this model to a Python Flask web application.


Algorithms in C++

By Vadim Smolyakov – 9 min read

The purpose of this article is to introduce the reader to four main algorithmic paradigms: complete search, greedy algorithms, divide and conquer, and dynamic programming. Many algorithmic problems can be mapped into one of these four categories and the mastery of each one will make you a better programmer.


Machine Learning as a Service

By Sebastian Kwiatkowski – 9 min read

The explosive growth in user-generated content and the digitization of archive material have created massive data sets containing opinions expressed by large numbers of people on just about every single topic.


The curse of "intuition" in Data Science

By Favio Vázquez – 5 min read

We are used to jumping to conclusions really fast, without analyzing all sides. As such, when trying to understand the world, intuition frequently fails. Here I propose a different system for doing Data Science without "trusting your gut".


Introduction to Clinical Natural Language Processing

By Andrew Long – 17 min read

Doctors have always written clinical notes about their patients – originally, the notes were on paper and were locked away in a cabinet. Fortunately for data scientists, doctors now enter their notes in an electronic medical record.


Data Science for Startups: R -> Python

By Ben Weber – 9 min read

One of the pieces of feedback I received for my blog series Data Science for Startups was that Python would be a better choice for data scientists joining a startup. This makes a lot of sense if Python is already your go to language for performing data science tasks.


The Data Science Gap

By Kirill Eremenko – 7 min read

Every other day it seems there is a new article about how data science is the best field for job prospects. Both in demand and well paid, it looks ideal for both students on the hunt for job security and workers seeking better pay.


How to Out-Compete On a Data Science Competition – Insights, Techniques and Tactics

By Christo Zonnev – 6 min read

The last two days I spend quite a lot of my free time on a current data-science competition. A loan prediction problem at Vidhya. And yes, it was less sleep than usual but the learnings were worth it.


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