Articles

Machine Learning and Pattern Recognition

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Introduction

In very simple language, Pattern Recognition is a type of problem while Machine Learning is a type of solution. Pattern recognition is closely related to Artificial Intelligence and Machine Learning. Pattern Recognition is an engineering application of Machine Learning. Machine Learning deals with the construction and study of systems that can learn from data, rather than follow only explicitly programmed instructions whereas Pattern recognition is the recognition of patterns and regularities in data.

  1. Machine Learning

The goal of Machine Learning is never to make "perfect" guesses because Machine Learning deals in domains where there is no such thing. The goal is to make guesses that are good enough to be useful. Machine Learning is a method of data analysis that automates analytical model building. Machine Learning is a field that uses algorithms to learn from data and make predictions. A Machine Learning algorithm then takes these examples and produces a program that does the job. Machine Learning builds heavily on statistics. For example, when we train our machine to learn, we have to give it a statistically significant random sample as training data. If the training set is not random, we run the risk of the Machine Learning patterns that aren’t actually there.

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Graph Algorithms in Neo4j: Use Cases for Graph Transactions and Analytics

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Today’s most pressing data challenges center around connections, not just tabulating discrete data. Graph analytics accelerate breakthroughs across industries with more intelligent solutions.

This article series is designed to help you better leverage graph analytics so you can effectively innovate and develop intelligent solutions faster.

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What Errors Lurk in Infer.NET Code?

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Posting of projects sources by Microsoft is a good reason to perform their analysis. This time is no exception, and today, we will look at suspicious places found in Infer.NET code.

Briefly About the Project and the Analyzer

Infer.NET is a Machine Learning system developed by Microsoft specialists. Project source code has become recently available on GitHub, which gave rise to its check. More details about the project can be found here.


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Guide for Freelancers – Skills to Land a Project In 2019

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In the freelancing industry, excellent skills are always required in order to deliver projects exactly as desired. These skills are constantly changing, and it is imperative that freelancers all over the world evolve accordingly.

Clients demand excellence and anything less is not acceptable. These expectations act as the propellant for the acquisition of the new skills in the market. 

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Comparing bfloat16 Range and Precision to Other 16-bit Numbers

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Deep Learning has spurred interest in novel floating point formats. Algorithms often don’t need as much precision as standard IEEE-754 doubles or even single precision floats. Lower precision makes it possible to hold more numbers in memory, reducing the time spent swapping numbers in and out of memory. Since this where a lot of time goes, low precision formats can speed things up quite a bit.

Here I want to look at bfloat16, or BF16 for short, and compare it to 16-bit number formats I’ve written about previously, IEEE and posit.


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Drowsy Detection Using Facial Landmarks Extraction and Deep Neural Networks

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Introduction

The goal of this article is to explain how you can detect a drowsy person using facial landmarks as an input of a neural network, a 3D convolutional neural network, in this case, to sound an alarm to awake the user and to prevent some kind of accident.

The idea is to extract a group of frames from a webcam and then extract from them the facial landmarks, specifically the position of both eyes, then pass these coordinates to the neural model to get a final classification which will tell us if the user is awake, or falling sleep.


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AWS CEO Believes Facial Recognition Software Benefits Outweigh Potential Dangers

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Despite objections from employees, law enforcement officers, and the ACLU, Amazon Web Services announced last Thursday that it would continue to sell facial recognition software, the AWS Rekognition system.

In an all-hands meeting on Thursday, AWS CEO, Andrew Jassy, explained their reasons for continuing to sell Rekognition to law enforcement, saying, "Rekognition is actively been used to help stop human trafficking, to reunite missing kids with parents for educational applications, for security and multi-factor authentication to prevent theft."


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How AI Can Accurately Spot Fake Restaurant Reviews

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It’s well known that user reviews are a fundamental part of the web economy, with consumers tending to trust the word of their fellow customer above any other form of marketing. Making sure those reviews are truthful and authentic therefore is key, especially as unscrupulous vendors are happy to produce fake reviews to puff up their service. A recent study from Aalto University highlighted how it’s increasingly possible to create fake reviews autonomously.

The authors state that around 40% of us make a decision based upon the feedback received from other people, whilst a good review can boost sales by around 30%. In other words, they’re important to the success of a product, which creates an incentive to create fake reviews to boost your ratings. Are AI-driven technologies increasingly capable of producing accurate reviews?


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Top 10 Machine Learning, Deep Learning, and Data Science Courses for Beginners (Python and R)

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Data Science, Machine Learning, Deep Learning, and Artificial Intelligence are really hot at this moment and offering a lucrative career to programmers with high pay and exciting work. It’s a great opportunity for programmers who are willing to learn these new skills and upgrade themselves. It’s also important from the job perspective because Robots and Bots are getting smarter day by day, thanks to these technologies and most likely will take over some of the jobs which many programmers do today. Hence, it’s important for software engineers and developers to upgrade themselves with these skills. Programmers with these skills are also commanding significantly higher salaries as data science is revolutionizing the world around us. Machine Learning specialist is one of the top paid technical jobs in the world. However, most developers and IT professionals are yet to learn these valuable set of skills.

For those, who don’t know what is a Data Science, Machine Learning, or Deep Learning, they are very related terms with all pointing towards machine doing jobs which is only possible for humans till date and analyzing the huge set of data collected by modern day application.


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Using AI to Speed up the Learning Process

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Technology can be a blessing in disguise. It is especially true in the modern classroom. While the Internet and a host of multimedia tech do make it easier to perform various tasks and deliver educational content, there are always concerns about its overall effectiveness in learning.

In a world where most interactions either begin or, at a minimum, include the use of screens and online content, teachers and students have two choices: avoid the tech and leave it out of the process or embrace it and develop ways to use it to the student’s advantage.


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