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Showing posts from 2017

7 ways to reduce your AWS costs

Are you spending more than planned on AWS? Or maybe you just want to spend less? What can you do? With the great variety of services and pricing options that AWS offers, you can build unimaginable networks of servers in the cloud, something very difficult and expensive to do with traditional IT infrastructure. But with that power in your hands it is really easy to go far from what you exactly need, ending up with a lot of underused or overused running resources which are difficult to keep track of.   Most AWS users are initially attracted to the service because of its pay-as-you-use pricing model. Like running water or electricity, you only pay for what you. But as your usage increases so does your billing size. On-demand is great so far as your pockets go. But with careful budget planning you can benefit from other models and save a lot of money on the long run. There are several ways to save yourself from paying high bills on AWS. Once you are able to define or re-define your origina…

What is the difference between AI, ML and deep learning?

The Difference Between Artificial Intelligence, Machine Learning and Deep Learning Once the domain of Sci-Fi geeks and film script writers, Artificial Intelligence or A.I. is considered well above and beyond fantastical subject these days. Anyone with the slightest interest in tech, no doubt knows that corporations like Microsoft and Google are running not just one, but multiple A.I. projects concurrently to address some of the most challenging problems known to mankind. Each approaching the problem from a slightly different angle. And like any emerging technology, the development of working (albeit limited) A.I. has spawned a whole plethora of new buzzwords such as Machine Learning and Deep Learning. But what do these terms mean? A quick and dirty explanation could look like this: Artificial Intelligence – the top-level container for all things related to creating at the very least, a synthetic “mind” able to solve problems in a heuristic manner. Machine Learning – the human mind uses e…

10 AWS security best practices every team MUST implement

I am writing this article at a time where we see more and more companies are migrating to the cloud or starting green field projects directly on the cloud but bad practices remain prevalent amongst teams. So I have decided to outline 10 of the most basic practices teams MUST follow to ensure their AWS environment are secured.
I am sure that by now most people have read or head about AWS' Shared Responsibility Model. It essentially means that AWS ensures you underlying infrastructure and environment in the actual data centres are physically secured and any disposal of the physical hard drives or old servers are made in compliance with various standards.
Customer’s responsibility on the other hand is focused on securing their data in the cloud. Anything uploaded or connected to the cloud is the full responsibility of the customer. For example, patching and hardening a Guest Operating System or enabling encryption or data integrity authentication.
That doesn’t mean AWS will leave you al…

7 Machine Learning Algorithms every Data Engineer and Data Scientist Must know about!

Machine learning has become such a buzz word these days and that is because organisations are collecting more and more data and using these algorithms can help utilise and monetise the data. In this post I will give an overview of seven most common machine learning algorithms and in each subsequent post I will explain each of the algorithms and show you how to implement them using TensorFlow.

Sophisticated Machine Learning algorithms look set to replicate human intelligence and consciousness. Applications of Machine Learning encompass a variety of challenging and complex problems ranging from spam filtering and fraud detection, to marketing personalisation and online search recommendations, to smart cars and healthcare diagnostics. Understanding the algorithms behind these use cases is the first step toward advancement in Machine Learning.

Machine Learning algorithms come in (at least) three major flavours:

Unsupervised Learning: Instead of predicting results, this algorithm helps identi…