Start NLP with a Single Neuron

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What Is a Classification Problem?

Classification is an important and central topic in ML, which has to do with training machines how to group together data by particular criteria. Classification is the process where computers group data together based on predetermined characteristics — this is called supervised learning. There is an unsupervised version of classification, called clustering where computers find shared characteristics by which to group data when categories are not specified.

For example:


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Agile Is Still Hot (and 4 Other Things I Learned from Our AMA)

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In case you missed it, last week I hosted an "Ask Me Anything"-style forum here on Atlassian Community. For you statistics fiends out there, we got 60 questions, 49 discussions nested under the questions, and nearly 27,000 views of the thread. Boom!

Not only was it a great time, I learned a ton from all the people who participated and want to share a few gems here.

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Test Before You Patch

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For ERP administrators today, security is always on their mind. But, recent warnings from the US Department of Homeland Security about ERP vulnerabilities make securing your Oracle and SAP applications even more urgent. Data breaches and unauthorized access can disrupt business-critical processes and negatively impact your customers. Staying up-to-date with security patches is the best way to make sure this doesn’t happen to your organization, but good protocol requires that you first test patches against a separate test instance of SAP to confirm that they won’t impact operations of your production instance.

So, how can you speed up testing and implement these important patches as soon as they’re available? Automating the SAP system copy process is one way to clear the path of the obstacles that keep you from better security.

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Deep Learning Drops the Ball and Dribbles

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Of all the major league sports in the United States, basketball is the most balletic…in my humble opinion. Basketball demonstrates a fluidity of complex full-body motion all the while interactively and iteratively guiding and correcting the trajectory of a ball which repeatedly rebounds from the hard court surface. Watching real basketball players drive through the crowd toward the hoop gives us a hint of the artfulness. Watching it in slow motion makes us stare in wonder at the complexity of the performance.

Transitioning to the world of video games (where many sports seem to find their way) the observer has quite a different impression watching today’s state-of-the-art synthetic players. The rendered players go through the motions, but the simulation just doesn’t seem real. Even though the characters themselves look quite good in static poses there is something clearly counterfeit about how they move. No matter how great the skills of the animator are, it seems impossible to specify all of the angular velocities at all of the joints for even the most basic moves. It’s not that we search to find subtle flaws in their movement, but rather that we are instantly struck with how unnatural these players are.


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Getting Started With TensorFlow.js

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With TensorFlow.js, you can not only run machine-learned models in the browser to perform inference, but you can also train them. In this super-simple tutorial, I’ll show you a basic "Hello World" example that will teach you the scaffolding to get you up and running.

Let’s start with the simplest Web Page imaginable:


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How Can AI Turn Our Digital Privacy into a Myth?

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You must have seen videos on Youtube or posts on your news feed in which certain texts or a person’s face is blurred. Well, that’s how our digital privacy is ensured by simplest of technologies.
But think about it, in an age of Machine Learning, can’t your digital privacy be easily breached? The answer is a big "Yes," and a team of researchers at the University of Texas has proven that. They have developed a software that can identify the sensitive content hidden behind blurred or pixelated images. The content can be someone’s house or vehicle number, or simply a human face.

Interestingly, the team hasn’t used some state of the art technology to do it. It has instead used Machine Learning methods to train the neural networks. So instead of being programmed, the computer has been fed with large volumes of sample images. The algorithm used doesn’t actually unblur or restore the image. It identifies the content of the blurred image based on the information it already has.


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Top 25 Amazing Websites to Learn How to Code

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Learning how to code is no longer just for IT professionals and software engineers. As the face of every business has moved online, being able to manipulate what website visitors see and interact with has become treasured. Today, knowing how to program can be one of the most important skills you can learn that will directly affect career advancement. If you can bring value to your online presence, then you can make a positive and measurable impact to any business.

Why Should You Learn Code?

If you are a newcomer to the world of web development and coding, it makes the most sense to start by teaching yourself how to code so that you may discover what you do and don’t like, before investing resources into courses for a particular coding language. Additionally, learning to code doesn’t have to cost a fortune—some resources require low financial investmen, or cost absolutely nothing. The job market for coding specialists and web developers is only getting larger, and top companies around the world are looking for the best and brightest minds to fill these positions. When approached right, you may even find that you will not even have to pay a dime to learn how to code—depending on your learning path. It is a skill that will never be overlooked by potential employers and is valuable.

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Planning, Logistics, and Operations: Modeling the London Tube Network

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We know Grakn can be leveraged to model highly complex data, but how do we go about building a detailed model of a real-world system?

Here, we delve into Transport for London (TFL) data to understand and gain insights into the operation of the London Underground Network.

We go on to build surely the most desirable tool for such a network: a journey planner. (Because who doesn’t want to shave 0.3 minutes off their commute?)


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The Future of Connected Vehicles

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An estimated 21 million connected vehicles are on the road today, gathering endless amounts of data. How does this data impact the way we do business and transform the world around us?

A few decades ago, personal vehicle and fleet navigation was completely dependent on paper road maps that no one ever knew how to fold! Digital maps are one of the many examples of how technology has completely revolutionized our world. Mapping the world on the internet rather than on paper has not only changed the way we navigate but also opened up various new business models like UBER and OLA, which we now take for granted.

Autonomous vehicles are here to stay with most manufacturers investing heavily in this direction to make their vehicles part of a connected world. Whether it is your own car or the truck that your business owns, all these are now becoming part of an expanding connected world.


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Smart Isolation: How AI Sets People Apart

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With global digitalization, technologies are taking over all aspects of our lives. We see the automation of business processes and services, smart homes, and much more. However, what else we see is the gradual isolation of individuals from each other as they have their own small worlds, locked in their smart devices.

In the last few years, people have been investing in social media heavily. The rise of bloggers does not seem strange now, but we did not expect it to be a real job, say, 5 years ago. Today, most millennials dream of becoming a YouTuber or an Instagram blogger (and most of them succeed, to be honest).


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