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Data ScienceData Science 101Resources

In recent years’ evidence has been mounting that points to a crisis in the reproducible results of scientific research. Reviews of papers in the fields of psychology and cancer biology found that only 40% and 10%, respectively, of the results, could be reproduced. Nature published the results of a survey of

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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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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 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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time series
Data ScienceMachine LearningResources

The Estimators API in tf.contrib.learn (See tutorial here) is a very convenient way to get started using TensorFlow. The really cool thing from my perspective about the Estimators API is that using it is a very easy way to create distributed TensorFlow models. Many of the TensorFlow samples that you

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Cybersecurity
Case StudiesCybersecurityResources

In today’s world of never ending cybersecurity threats, companies must be more diligent than ever in protecting their data from external and internal threats. The question of dealing with cybersecurity incidents is not a matter of if but WHEN. How a company responds to a breach is vital – the

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Data ScienceData Science 101Resources

Categorical data is a kind of data which has a predefined set of values. Taking “Child”, “Adult” or “Senior” instead of keeping the age of a person to be a number is one such example of using age as categorical. However, before using categorical data, one must know about various

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BI & AnalyticsFeaturedinfographicsResources

The world is increasingly digital, and this means big data is here to stay. In fact, the importance of big data and data analytics is only going to continue growing in the coming years. It is a fantastic career move and it could be just the type of career you

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Data ScienceFeaturedMachine LearningResourcesTopics

In the last few months, I have had several people contact me about their enthusiasm for venturing into the world of data science and using Machine Learning (ML) techniques to probe statistical regularities and build impeccable data-driven products. However, I’ve observed that some actually lack the necessary mathematical intuition and

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