Author: admin
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A Trivial Theano Expression
Let us begin our journey of Theano by defining and evaluating a trivial expression in Theano. Consider the following trivial expression that adds two scalars − c = a + b Where a, b are variables and c is the expression output. In Theano, defining and evaluating even this trivial expression is tricky. Let us understand the steps to evaluate…
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Installation
Theano can be installed on Windows, MacOS, and Linux. The installation in all the cases is trivial. Before you install Theano, you must install its dependencies. The following is the list of dependencies − The optional packages that you may choose to install depending on your needs are − We shall discuss the steps to…
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Introduction
Have you developed Machine Learning models in Python? Then, obviously you know the intricacies in developing these models. The development is typically a slow process taking hours and days of computational power. The Machine Learning model development requires lot of mathematical computations. These generally require arithmetic computations especially large matrices of multiple dimensions. These days…
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SciPy Statistical Significance Tests
What is Statistical Significance Test? In statistics, statistical significance means that the result that was produced has a reason behind it, it was not produced randomly, or by chance. SciPy provides us with a module called scipy.stats, which has functions for performing statistical significance tests. Here are some techniques and keywords that are important when performing…
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SciPy Interpolation
What is Interpolation? Interpolation is a method for generating points between given points. For example: for points 1 and 2, we may interpolate and find points 1.33 and 1.66. Interpolation has many usage, in Machine Learning we often deal with missing data in a dataset, interpolation is often used to substitute those values. This method…
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SciPy Matlab Arrays
Working With Matlab Arrays We know that NumPy provides us with methods to persist the data in readable formats for Python. But SciPy provides us with interoperability with Matlab as well. SciPy provides us with the module scipy.io, which has functions for working with Matlab arrays. Exporting Data in Matlab Format The savemat() function allows us to export…
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SciPy Spatial Data
Working with Spatial Data Spatial data refers to data that is represented in a geometric space. E.g. points on a coordinate system. We deal with spatial data problems on many tasks. E.g. finding if a point is inside a boundary or not. SciPy provides us with the module scipy.spatial, which has functions for working with spatial…
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SciPy Graphs
Working with Graphs Graphs are an essential data structure. SciPy provides us with the module scipy.sparse.csgraph for working with such data structures. Adjacency Matrix Adjacency matrix is a nxn matrix where n is the number of elements in a graph. And the values represents the connection between the elements. Example: For a graph like this, with elements A, B and C,…
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SciPy Sparse Data
What is Sparse Data Sparse data is data that has mostly unused elements (elements that don’t carry any information ). Sparse Data: is a data set where most of the item values are zero. Dense Array: is the opposite of a sparse array: most of the values are not zero. In scientific computing, when we are dealing with partial…
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SciPy Optimizers
Optimizers in SciPy Optimizers are a set of procedures defined in SciPy that either find the minimum value of a function, or the root of an equation. Optimizing Functions Essentially, all of the algorithms in Machine Learning are nothing more than a complex equation that needs to be minimized with the help of given data.…