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How to Avoid Common Difficulties in Your Data Science Programming Environment
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How to Avoid Common Difficulties in Your Data Science Programming Environment

Reduce the incidental issues in your programming environment so you can focus on the important data science problems. Consider the following situation: you’re trying to practice your soccer skills, but each time you take to the field, you encounter some problems: your shoes are on the wrong feet, the laces aren’t tied correctly, your socks are...

How to extract online data using Python
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How to extract online data using Python

Basic concepts about HTML, XPath, Scrapy, and spiders Euge Inzaugarat Jul 2 “I would be nice to have all the documents of the website” — One of her colleagues said “Yeah, that could give us a lot of information” — Said another colleague “Can you do the scraper?” — They both turn to look at her “Ehhhh… I could….” — She started mumbling “Perfect” — They...

Serial Promises vs Parallel Promises
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Serial Promises vs Parallel Promises

In javascript we often need to do multiple asynchronous things. I’d like to use this post to show a few examples of doing things serially, and in parallel with promises. Example 1: “Wait a second” x 3 First example, lets define a function where we “wait a second”, three times in a row. This function...

Python for Data Science: From Scratch
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Python for Data Science: From Scratch

Learning about Data Structures and important packages like Numpy and Pandas in Python. This article is the second piece in the Python For Data Science Series. In case you haven’t gone through the introduction of Python(part 1), go ahead and skim through that article here. After knowing about the basics, its time to indulge in more challenging...

The Democratization of Data Science
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The Democratization of Data Science

Want to catch tax cheats? The government of Rwanda does — and it’s finding them by studying anomalies in revenue-collection data. Want to understand how American culture is changing? So does a budding sociologist in Indiana. He’s using data science to find patterns in the massive amounts of text people use each day to express...

Do You Know The Difference Between Data Analytics And AI Machine Learning?
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Do You Know The Difference Between Data Analytics And AI Machine Learning?

The artificial intelligence (AI) industry has been leading the headlines consistently, and for good reason. It has already transformed industries across the globe, and companies are racing to understand how to integrate this emerging technology. Artificial intelligence is not a new concept. The technology has been with us for a long time, but what has...

How components won the “framework wars”
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How components won the “framework wars”

React vs Angular vs Vue: Why it doesn’t matter. 2018 marks the end of JavaScript fatigue and the “framework wars” A typical frontend/JavaScript developer career usually involves some jQuery and associated plugins before moving on to React, Angular or Vue. Having experienced React, Vue and Angular, it seems they solve similar problems in a similar...

Why Data Governance is Crucial for Big Data Environments
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Why Data Governance is Crucial for Big Data Environments

The most significant obstacle preventing organizations from realizing the full potential of their data assets today is the widespread data disorder. Companies have quickly accrued massive amounts of data, and adopted big data environments to store it. And while insights might be buried within all that raw data; if no one knows where it came...

The 3 Vital Ways HR Teams Should Be Using Data
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The 3 Vital Ways HR Teams Should Be Using Data

Any average HR department is rich in data. Personal employee data, recruitment data, and performance KPIsare just a few examples of the kinds of data a typical HR team is sitting on. Now, as our world becomes increasingly ‘datafied’, HR teams have more opportunities than ever before to capture and analyze data, which has given rise...