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Data Science

While the field of data science is not tied directly to Big Data, advances in one tends to produce advances in the other. Big Data increases our ability to harvest and process data, while data science allows us to dig into it for insights.

Data ScienceMachine Learning

This article is part of a media partnership with PyData Berlin, a group helping support open-source data science libraries and tools. To learn more about this topic, please consider attending our fourth annual PyData Berlin conference on June 30-July 2, 2017. Matti Lyra and other experts will be giving talks

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Data ScienceResources

This is the continuation of the Frequency Distribution Analysis using Python Data Stack – Part 1 article. Here we’ll be analyzing real production business surveys for your review. Application Configuration File The configuration (config) file config.py is shown in Code Listing 3. This config file includes the general settings for

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fintech business intelligence
BI & AnalyticsData ScienceFinTech

Fintech is becoming an increasingly competitive market. A KPMG analysis saw investments decline in 2016 and investors are now more cautious about betting on segments that are becoming saturated. Lending and payments are two segments that saw increased participation over the past two years. Competitors come in all forms. We

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Data Science Career
Data ScienceEducationIndustryNews

Springboard is a leader in data science education. Thousands of data science learners complete their education in Springboard’s mentored data science courses and they’ve given Springboard courses an average rating of 4.9/5 on CourseReport and Switchup. Springboard is the proven option in data science training you’ve been looking for if

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Data ScienceResources

During my years as a Consultant Data Scientist I have received many requests from my clients to provide frequency distribution reports for their specific business data needs. These reports have been very useful for the company management to make proper business decisions quickly. In this paper I would like to

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Data ScienceMachine Learning

R is ubiquitous in the machine learning community. Its ecosystem of more than 8,000 packages makes it the Swiss Army knife of modeling applications. Similarly, Apache Spark has rapidly become the big data platform of choice for data scientists. Its ability to perform calculations relatively quickly (due to features like in-memory

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Big DataData Science

Data processing today is done in form of pipelines which include various steps like aggregation, sanitization, filtering and finally generating insights by applying various statistical models. Amazon Kinesis is a platform to build pipelines for streaming data at the scale of terabytes per hour. Parts of the Kinesis platform are

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Data ScienceResources

Welcome to Part 2 of How to use Elasticsearch for Natural Language Processing and Text Mining. It’s been some time since Part 1, so you might want to brush up on the basics before getting started. This time we’ll focus on one very important type of query for Text Mining.

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Data ScienceData Science 101Resources

The R language is often perceived as a language for statisticians and data scientists. Quite a long time ago, this was mostly true. However, over the years the flexibility R provides via packages has made R into a more general purpose language. R was open sourced in 1995, and since

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Data ScienceEventsMachine Learning

For people in the know, machine learning is old hat. Even so, it’s set to become the data buzzword of the year — for a rather mundane reason. When things get complex, people expect technology to ‘automagically’ solve the problem. Whether it’s automated financial product consultation or shopping in the supermarket of

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