April 29, 2019 in Python
In the previous article, we looked at how to construct a very simple artificial neural network to model our chicken-or-beef meal decision. However, this is overly simplistic for most 'real-world' problems. In this final article, we'll look at how to extend this basic network, and how to deal with that ever-present bugbear in machine learning: over-fitting.
April 21, 2019 in Python
The important objective functions for ANNs are referred to as cost or loss functions. These functional measures of error are the important metrics with which we determine the success of our algorithm. The goal of machine learning algorithms is to optimize such a function.
April 15, 2019 in Python
Here we try to give a simple illustration of what the fuss is all about, and even show you how to cast your own Artificial Neural Network spells — using the popular Python programming language along the way.
January 22, 2019 in Python
In Part 1, we explored some of the power offered by the pandas framework. Now we'll dive deeper into the tools such as grouping, aggregation, joins, advanced string methods and other functions.
October 25, 2018 in Python
Tired of your fellow humans being probed by aliens? It’s time to probe back! Well, at least, probe the data on UFO sightings. To do this, we’ll show-case one of the most popular open source tools for analyzing data: the pandas package.
October 09, 2018 in Python
Most working definitions of Big Data do not have an explicit reference to the size of the data set. This is because the associated conceptual, software, and hardware shifts derive from several important factors aside from actual size of the data.
September 17, 2018 in Python
We can apply machine learning to help detect credit card fraud, but there is a bit of a problem in that the vast majority of transactions are perfectly legitimate, which reduces a typical model’s sensitivity to fraud.
September 05, 2018 in Python
If you ask four practitioners in the data space, you’ll get five opinions on what a data scientist is and does.
August 15, 2018 in Python
The very field of statistics and probability theory was ploughed and sown from attempts to better understand games of chance.
June 18, 2018 in Python
Whether you are fairly new to data science techniques or even a seasoned veteran, interpreting results from a machine learning algorithm can be a trying experience. The challenge is making sense of the output of a given model.
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