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June 2019 Blog Posts (94)

Basics of Hive and Impala for Beginners

Data Science is the field of study in which large volumes of data are mined, analysed to build predictive models, and help the business in the process. The data used over here is often unstructured, and it’s huge in quantity. Such data which encompasses the definition of volume, velocity, veracity, and variety is known as Big Data.

Hadoop and Spark are two of the most popular open-source framework used to deal with big data. The Hadoop architecture includes the following…


Added by Divya Singh on June 6, 2019 at 9:30pm — No Comments

Data Science Central Thursday Digest, June 6

Here is our selection of featured articles and technical resources posted since Monday:



Added by Vincent Granville on June 6, 2019 at 9:30am — No Comments

Hunting for Data: a Few Words on Data Scraping

No matter how intelligent and sophisticated your technology is, what you ultimately need for Big Data Analysis is data. Lots of data. Versatile and coming from many sources in different formats. In many cases, your data will come in a machine-readable format…


Added by Max Ved on June 6, 2019 at 1:29am — No Comments

How to Make Machine Learning Models for Beginners


Data science is one of the hottest topics in the 21st century because we are generating data at a rate which is much higher than what we can actually process. A lot of business and tech firms are now leveraging key benefits by harnessing the benefits of data science. Due to this, data science right now is really booming.

In this blog, we will deep dive into the world of machine learning. We will walk you…


Added by Divya Singh on June 4, 2019 at 8:30pm — No Comments

Neuromorphic Chips and the Future of Your Cell Phone

Summary:  The ability to train large scale CNNs directly on your cell phone without sending the data round trip to the cloud is the key to next gen AI applications like real time computer vision and safe self-driving cars.  Problem is our current GPU AI chips won’t get us there.  But neuromorphic chips look like they will.



Added by William Vorhies on June 4, 2019 at 9:00am — No Comments

Unleashing Artificial Intelligence in Government Services and Operations

A significant sector with direct influence on our lives is the role Government plays in terms of the services it offers to citizens and operations of the government.

In view of the penetration of a data-driven approach to all businesses, there is a clear need to adopt a data-driven approach to government services and operations. Hence the penetration of AI is a case of positive influence on Govt products and services.

Some key areas where government operations and services can…


Added by Mahesh Kumar CV on June 4, 2019 at 6:23am — No Comments

Why Every Hadoop Professional Needs Data Science Skills?

Value of adopting Data Science Skills

Data Science is responsible to provide meaning to the large amounts of complex data called big data. It involves different fields of work in statistics and computation to interpret data for decision-making.

Advances in the internet and social media is increasing access to big data. Extraction of meaningful information requires the use of AI and ML by data science. Big data is used in every…


Added by Yoey Thamas on June 4, 2019 at 2:33am — No Comments

NLP vs. NLU: from Understanding a Language to Its Processing

As artificial intelligence progresses and technology becomes more sophisticated, we expect existing concepts to embrace this change — or change…


Added by Max Ved on June 4, 2019 at 12:30am — No Comments

Discrimination, Data Science and a Call to Action

Four years ago, the software engineer Jack Alciné caused a storm by pointing out to Google that their algorithm had the unsavoury tendency to classify his black friends as Gorillas. Following a public outcry for blatant racism, the giant apologised and diligently ‘fixed’ the problem. Last year Amazon got into hot water by finding its advanced AI hiring software heavily favoured men for technical positions. Again, retraction followed the outcry. In a more newsworthy style, an unfortunate…


Added by Dany Majard on June 3, 2019 at 3:10am — 2 Comments

Simple Trick to Normalize Correlations, R-squared, and so on

Many statistics, such as correlations or R-squared, depend on the sample size, making it difficult to compare values computed on two data sets of different sizes. Here, we address this issue.

Below is an example with 20 observations. The 10 last observations (the second half of the data set) is a mirror of the first 10, and the two correlations, computed on each subset, are identical and equal to  0.30. The full correlation computed on the 20 observations is 0.85.…


Added by Vincent Granville on June 2, 2019 at 7:30am — 1 Comment

The Call for a New Device for Data Scientists

My first computer was a Commodore Vic-20 in 1981. I bought the device because of this incredible urge to program in BASIC as a result of Mr. Ted Becker’s course on computer programming. I vaguely remember the leap from the pain-staking process of programming using punch cards to writing code and watching your program run immediately, once you resolved all of the syntax errors of course. Nonetheless, it was thrilling and addictive! In hindsight, a…


Added by Richard Charles, PhD on June 2, 2019 at 12:00am — No Comments

The Homogeneity and Location Index: An open-source Statistical Framework for the classification of ordinal categorical data

The analysis and classification of ordinal categorical data are central in most scientific domains and ubiquitous in governments and businesses.

Examples of ordinal data are either found in questionnaires for measuring opinions or self-reported health status. A well-known example of ordinal data is the Likert Scale [1]



Added by Ludovico Pinzari on June 1, 2019 at 3:35pm — No Comments

Data Science Central Monday Digest, June 3

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. To subscribe, follow this link.  


  • The NEW M.S.…

Added by Vincent Granville on June 1, 2019 at 3:00pm — No Comments

How DevOps Drives Analytics Operationalization and Monetization

I recently wrote a blog "Interweaving Design Thinking and Data Science to Unleash Economic Value of Data"  that discussed the power of interweaving Design Thinking and Data Science to make our analytic efforts more effective.  Our approach was validated by a recentMcKinsey article titled “Fusing data and…


Added by Bill Schmarzo on June 1, 2019 at 9:35am — No Comments

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