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May 2018 Blog Posts (100)

Top 7 Data Science Use Cases in Finance

In recent years, the ability of data science and machine learning to cope with a number of principal financial tasks has become an especially important point at issue. Companies want to know more what improvements the technologies bring and how they can reshape their business strategies.

To help you answer these questions, we…

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Added by Igor Bobriakov on May 14, 2018 at 4:30am — No Comments

Six Core Aspects of Semantic AI

  1. Hybrid approach: Semantic AI is the combination of methods derived from symbolic AI and statistical AI. Virtuously playing the AI piano means that for a given use case various stakeholders, not only data scientists, but also process owners or subject matter experts, choose from available methods and tools, and collaboratively develop workflows that are most likely a good fit to tackle the underlying problem. For example, one can combine entity extraction based on…
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Added by Andreas Blumauer on May 14, 2018 at 4:30am — 2 Comments

What is Bitcoin ?

Bitcoin is known as the very first decentralized digital currency, they’re basically coins that can send through the Internet. 2009 was the year where bitcoin was born. The creator’s name is unknown, however the alias Satoshi Nakamoto was given to this person.

Advantages of Bitcoin.

Bitcoin transactions are made directly from person to person trough the internet. There’s no need of a bank or clearinghouse to act as the middle…

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Added by Venkatesan M on May 13, 2018 at 9:30pm — 1 Comment

How Python fares as a data science language?

Originally posted by Vaishnavi Agrawal.

Did you know that Python’s usage in data science applications rose 51% in 2015? Did you know that youtube is heavily built on Python language consisting of over a million lines of code? Tech visionaries are predicting that it might soon overtake R and may well be the most popular language in data science industry. R is a language dedicated to statistics and data…

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Added by Vincent Granville on May 13, 2018 at 2:59pm — No Comments

Weekly Digest, May 14

Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week.

Announcements
  • SQL + Notebooks + Charts. All in one platform. …
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Added by Vincent Granville on May 13, 2018 at 5:00am — No Comments

From Software Testing to Data Science

Roles are evolving and nowhere is this more evident than in the workplace. People are beginning to drift away from work that took 4 years of university to learn to take up jobs that took 3 months of Udacity to master. And It is now extremely common to see people make dramatic 180-degree career switches towards jobs they feel are either more profitable or more interesting.



As a Software Tester, you are doing work…

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Added by VAMSI NELLUTLA on May 12, 2018 at 5:15pm — No Comments

Selection of Great Data Science Articles still Worth Reading

These articles are between 3 and 5 year old, but are still valuable today. The methodology used in these articles is modern, and still state-of-the-art today. Some discuss immense data sets still available to the public, and that resulted in designing new machine learning techniques to handle them. 

I am in the process of organizing these articles (written by myself) to eventually self-publish data science tutorials, in a few separate booklets, that are easy to understand for the…

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Added by Vincent Granville on May 12, 2018 at 4:30pm — No Comments

Markov Chains

I've recently spent a bit of time getting to grips with Markov Chains. I've created a jupyter notebook which attempts to give an "intuition" into the basic concepts; an overview of some of the maths involved and a idea to use "social mobility" probability density functions with Markov Chains to estimate long term "social class" proportions.

This…

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Added by John Smethurst on May 12, 2018 at 7:00am — 1 Comment

Machine Learning and Its Algorithms to Know – MLAlgos

Describing and picturing MLAlgos and Machine Learning is the main idea of this post. I will attempt to answer few basic questions as well. Though these questions have been answered many a times in the past and are widely available. Answering them again here from my very own experience on the ground may makes the difference though rather then simply answering from phd or scholar books material prospective.…

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Added by Vinod Sharma on May 10, 2018 at 10:30pm — No Comments

What is DevOps ?

In earlier days, solutions were associated with getting the technology right. The key was technology, the solution was technology and the business expected and paid for technology. Times have changed. Well, at least for those of us taking notice. Today technology is hardly ever a significant problem. Technically, we have a less complicated world. Over the years we have come to understand that technology…

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Added by Venkatesan M on May 10, 2018 at 8:30pm — No Comments

Deep Dive into Polynomial Regression and Overfitting

In this article, we show that the issue with polynomial regression is not over-fitting, but numerical precision. Even if done right, numerical precision still remains an insurmountable challenge. We focus here on step-wise polynomial regression, which is supposed to be more stable than the traditional model. In step-wise regression, we estimate one coefficient at a time, using the classic least square technique. …

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Added by Vincent Granville on May 9, 2018 at 5:30pm — 4 Comments

An Intro to Natural Language Processing in Python: Framing Text Classification in Familiar Terms

Natural language processing (NLP) is a broad field encompassing many different tasks such as text search, translation, named entity recognition, and topic modeling. On a daily basis, we use NLP whenever we search the internet, ask a voice assistant to tell us the weather forecast, or translate web pages written in another language. Businesses use NLP to understand how their…

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Added by Civis Analytics on May 9, 2018 at 1:30pm — No Comments

A guide to manipulating, analyzing, and visualizing data in R

R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. 

Learn the fundamentals of data analysis in the second edition of Data Analysis with R, authored by data scientist…

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Added by Packt Publishing on May 8, 2018 at 10:30pm — No Comments

Deep Learning Infrastructure for Extreme Scale with 
the Apache Kafka Open Source Ecosystem

I had a new talk presented at "Codemotion Amsterdam 2018" this week. I discussed the relation of Apache Kafka and Machine Learning to build a Machine Learning infrastructure for extreme scale.

Long version of the title:

"Deep Learning at Extreme Scale (in the Cloud) 
with the Apache Kafka Open Source Ecosystem - How to Build a Machine Learning Infrastructure with Kafka, Connect, Streams, KSQL, etc."

As always, I want to share the slide deck. The talk was…

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Added by Kai Waehner on May 8, 2018 at 9:30pm — No Comments

GraphQL & gRPC (Part 2)

The original intent of this post was to take a real-life project with GraphQL and to see the performance of gRPC against HTTP. Instead, we ended up using the awesome GraphCool…

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Added by Jesus Ramos on May 8, 2018 at 10:00am — No Comments

A “quick” introduction to PyMC3 and Bayesian models

A “quick” introduction to PyMC3 and Bayesian models, Part I

In this post, I give a “brief”, practical introduction using a specific and hopefully relate-able example drawn from real data.…

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Added by Jesus Ramos on May 8, 2018 at 10:00am — No Comments

AI Strategies – Incremental and Fundamental Improvements

Summary:  Before starting to develop an AI strategy, make sure your team understands the limits of what is reasonable today, as well as incremental improvements that might be overlooked.  Focus should be on your LOB leaders who understand the business.  Make sure they are also able to recognize AI opportunities.

 

 

I…

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Added by William Vorhies on May 8, 2018 at 9:30am — No Comments

GraphQL & gRPC (Part 1)

GraphQL & gRPC (Part 1)…





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Added by Jesus Ramos on May 8, 2018 at 9:30am — No Comments

A Note on Numerical Modality in Large Datasets

Numerical Modality

The mode is one of the basic statistics which is defined as the most common value over an array. When the values of the array are categorical, the mode is easy to detect by selecting the one with the most occurrence. The problem of identifying the modes on a numerical array is harder since the values…

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Added by Jesus Ramos on May 8, 2018 at 9:30am — No Comments

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