Tuning the learning rate in Gradient Descent

Tuning the learning rate in Gradient Descent

In most Supervised Machine Learning problems we need to define a model and estimate its parameters based on a training dataset. A popular and easy-to-use technique to calculate those parameters is to minimize model’s error with Gradient Descent. The Gradient Descent estimates the weights of the model in many iterations by minimizing a cost function […]

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Coding Brain Neurons by using Hodgkin-Huxley model

Coding Brain Neurons by using Hodgkin-Huxley model

Understanding how the human brain works is a topic of active research and several scientists from various fields publish numerous of papers every year. Why is it important? Because knowing how our brain works will enable us to understand how we operate/think and perhaps enable us build truly intelligent machines in the future. The first […]

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Machine Learning Tutorial: The Naive Bayes Text Classifier

Machine Learning Tutorial: The Naive Bayes Text Classifier

In this tutorial we will discuss about Naive Bayes text classifier. Naive Bayes is one of the simplest classifiers that one can use because of the simple mathematics that are involved and due to the fact that it is easy to code with every standard programming language including PHP, C#, JAVA etc. Update: The Datumbox […]

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Using Datumbox API with Python and R languages

Using Datumbox API with Python and R languages

The Datumbox API can be used by any modern computer language which enables you to generate web requests. Our Machine Learning API can easily be implemented within minutes because it uses REST and JSON technologies and because all the requests are authenticated simply by passing your API Key. To test the API all you need […]

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