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Improving Nudity Detection and NSFW Image Recognition
This post discussed improvements made in a tricky machine learning classification problem: nude and/or NSFW, or not?
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Machine Learning Trends and the Future of Artificial Intelligence
The confluence of data flywheels, the algorithm economy, and cloud-hosted intelligence means every company can now be a data company, every company can now access algorithmic intelligence, and every app can now be an intelligent app.
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Political Data Science: Analyzing Trump, Clinton, and Sanders Tweets and Sentiment
This post shares some results of political text analytics performed on Twitter data. How negative are the US Presidential candidate tweets? How does the media mention the candidates in tweets? Read on to find out!
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Thinking About Analytics Readiness
This article touches upon an important but under-discussed topic of analytics readiness, including whether and when organizations should engage in analytics.
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Mining Twitter Data with Python Part 1: Collecting Data
Part 1 of a 7 part series focusing on mining Twitter data for a variety of use cases. This first post lays the groundwork, and focuses on data collection.
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10 Data Acquisition Strategies for Startups
An interesting discussion of the myriad methods in which startups may choose to acquire data, often the most overlooked and important aspect of a startup's success (or failure).
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Machine Learning Classic: Parsimonious Binary Classification Trees
Get your hands on a classic technical report outlining a three-step method of construction binary decision trees for multiple classification problems.
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Apache Spark Key Terms, Explained
An overview of 13 core Apache Spark concepts, presented with focus and clarity in mind. A great beginner's overview of essential Spark terminology.
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Where are the Opportunities for Machine Learning Startups?
Machine learning has permeated data-driven businesses, which means almost all businesses. Here are a few areas where it’s possible that big corporations haven’t already eaten everybody’s lunch.
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Data Science of Variable Selection: A Review
There are as many approaches to selecting features as there are statisticians since every statistician and their sibling has a POV or a paper on the subject. This is an overview of some of these approaches.
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