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Self Driven Data Science — Issue #30
Here’s this weeks lineup of data-driven articles, stories, and resources delivered faithfully to your inbox for you to consume. Enjoy!
30 Amazing Machine Learning Projects for the Past Year
This is an extremely competitive list and it carefully picks the best open source Machine Learning libraries, datasets and apps published between January and December 2017. Mybridge AI evaluates the quality by considering popularity, engagement and recency. Check it out.
Clustering Using K-Means Algorithm
K-means is a powerful, intuitive algorithm to have at your disposal. This article begins with an example to help the reader understand the objective of this powerful technique in machine learning before getting into how the algorithm does what it does.
Build a Taylor Swift Detector with the TensorFlow Object Detection API, ML Engine, and Swift
The TensorFlow Object Detection API demos lets you recognize the location of objects in an image, which can lead to some super cool applications. For instance, this article follows the process of building a Taylor Swift facial recognition detector.
Wrangling Data with Pandas
Pandas is a popular tool used to manipulate datasets and set them up for machine learning. This overview does a good job guiding you through getting starting wrangling data with the Pandas Python library.
How to Break a CAPTCHA System with Machine Learning
Everyone hates CAPTCHAs — those annoying images that contain text you have to type in before you can access a website. CAPTCHAs were designed to prevent computers from automatically filling out forms by verifying that you are a real person. But with the rise of deep learning and computer vision, they can now often be defeated easily.
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Self Driven Data Science — Issue #30 was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.
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