personal Impression and Experience

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Medical Imaging with Deep Learning Conference (MIDL 2019), held at the Imperial College London, from 8th to 10th July 2019 was one of the few conferences I attended that will always be memorable. I mean it rings a rather special kind of bell.

As Ben Glocker puts it;

If you’re wondering where you are currently, you are right in the ‘MIDL’ between Medical Imaging and Deep Learning

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There was a bit of a pun intended there, but I could not have said it in a better way than he did. MIDL 2019 focused specifically on how Deep Learning(D.L) is applied to Medical Imaging. …

Difference and Essence

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Some terms in Machine Learning (ML) are quite easy to misunderstand or mix up.

But why ?

My observation is that, most ML books or tutorials may not have necessarily dedicated time to explain them as much as they would for major topics, hence the confusion for most people.

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In this short article I will take time to briefly explain the main difference between Epoch and Iteration of ML model training. This article assumes the reader has some previous knowledge or experience in training artificial neural networks and is not specific to any particular ML framework. Before I explain, let’s start with a very relatable example. …

…motivation comes from seeing the applicability of mathematics…

When a group of University teachers of Complex Algebra and differential equations were asked,

“Why do we need to learn all these complex mathematical techniques if we may never use it for work?” They replied; “The purpose of learning Maths is not the final application in your daily life. But to develop analytical skills in your brain, and those skills are very useful for many job positions”

This article is primarily aimed at Engineers, Math students or enthusiasts who wish to gain a better understanding of Algebraic techniques such as the Laws of Indices and how it is practically applied in real life to solve engineering problems. At the end of the article, readers are expected to be able to explain basic concepts behind the Laws of indices with practical applications in everyday life activities such as the World Cup. …

If you have not already seen my article explaining the Laws of Indices as algebraic techniques, feel free to check it out now. This article below explains how the Indices Laws can be applied to designing FIFA World Cup Fixtures, using the case of Russia 2018. There is also a brief user challenge at the end to get you thinking about how you may apply Indices Laws yourself.

The World Cup starts off with about 32 countries. …

This is article is meant to give a practical demonstration of Machine Learning with a small data-set. For a basic explanation of MAE, do check my other article on Mean Absolute Error ~ MAE in Machine Learning(ML).

In this article, I will give a working example of how to calculate the Mean Absolute Error using a model that predicts cost price of houses with different sizes.

The calculation in this article is explicitly based on maths/statistics. There are other programming libraries (Especially for python: NumPy, Scikit-learn, etc…) which equally implements this and can be imported for the same function.

This prediction error is calculated for each record of the test data set. After, we convert each error to a positive figure if negative. This is achieved by taking Absolute value for each error. Finally we calculate the mean value for all recorded absolute errors. (Average sum of all absolute errors). …

This article is intended to give practical advice on one of the metrics for measuring accuracy of Machine Learning models. At the end of this article, you will be able to understand the Mean Absolution Error and how it measures model accuracy.

Have you ever built a machine learning model ? For prediction, classification or any other purpose? But how accurate is your model and how do you measure its accuracy?

Yes, this is the trillion dollar question every Machine Learning Developer or Engineer must answer for every model built. …


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