We have previously through the process of recognizing numbers utilizing our artificial neural network (ANN). If you haven’t gone through that post on, you can do so now. However, we ran the recognition task on images from the MNIST dataset. Even though we used the test data, it’s still cannot be considered real-world. It’s clean, well-labeled, and structured, with a lot of the noise and ambiguity removed.
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We have previously created and trained a basic artificial neural network (ANN). If you haven’t gone through that post on, you can do so now. In this post, we’ll continue and go through the process of recognizing numbers utilizing the ANN model that we created.
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Artificial Neural Networks (ANN) can be complex but it has become much easier to implement, thanks to frameworks and libraries, the past few years. In this post, we’ll walk through the process of creating a basic ANN. We’ll be using Python, TensorFlow, and Keras to create an ANN for recognizing handwritten digits. This is kind of the “Hello World” of AI.
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Artificial intelligence or AI is all the rage these days, driving amazing innovations across multiple industries and transforming how we interact with technology. Machine learning, a subset of AI, plays a crucial role in this transformation by enabling systems to learn from data and improve over time. Among the most powerful techniques in machine learning are Artificial Neural Networks (ANNs), which are modeled after the human brain and have become essential for solving complex problems in fields like image recognition, voice recognition, natural language processing, and predictive analytics. In this post, we will explore the basics of ANNs and how they work.
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If you’ve been around a while, you’d remember there was a time when you can rest quietly assured that your Linux box is safe from viruses and other malware. Or rather, few bad actors bother to target Linux. Most target Windows. That was then. But today, with the increase in the popularity of Linux not just on servers but even on desktops, Linux is no longer under the radar of bad actors.
So a few days ago, I was alerted to abnormal CPU utilization on one of my servers. I logged in to check and saw that there’s a process called perfctl that was using up CPU time. I killed it but it respawned after a while. It looked like my Linux server had malware.
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