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CMake
Wandering through the field of study that gives computers the ability to learn without being explicitly programmed. Mainly based on Machine Learning course @ Coursera.
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The probability that a random variable X will be found to have a value less than or equal to x.
The most famous kind of distribution and its relationship with the real world.
Measuring the variability!
An overview of basic probability concepts, histograms, discrete/continuous variables.
How do they work, the differences between discrete and continuous ones, how to use them in probability.
Or the variability from an average value.
How do those relate to each other?
Basic tools to split and analyze data sets.
Basic statistical concepts.
A collection of practical tips and tricks to improve the gradient descent process and make it easier to understand.
How to upgrade a linear regression algorithm from one to many input variables.
It's time to put together the gradient descent with the cost function, in order to churn out the final algorithm for linear regression.
How to find the minimum of a function using an iterative algorithm.
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A bird's-eye view on the art of resource sharing from one computer to another.
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