If you are familiar with machine learning, you must know that the development of machine learning models, which is done with the Python programming language, has many complications. For this reason, this process is done slowly and it is necessary to use tools that have high computing power and speed. Deep learning is used to facilitate this process and increase its speed. In other words, deep learning is a part of machine learning and both of them are done with Python programming language.
The Python programming language has many libraries to perform complex mathematical calculations that are needed in machine learning and deep learning. One of these libraries is Theano, which is discussed in this article.
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What is Theano library?
Theano library is one of the Python libraries, which is also known as the grandfather of deep learning libraries among programmers. The MILA (formerly LISA) group developed the Theano library in 2007 at the University of Montreal in Quebec, Canada. The name of this library is derived from a Greek philosopher and mathematician who is said to have been the wife of Pythagoras.
The Theano library allows you to simplify and optimize mathematical expressions involving multidimensional arrays used in machine learning. Theano was one of the first libraries that worked in this way (simplifying mathematical expressions). Therefore, it was introduced as a standard in this type of library for many programmers. After its release, the Theano library found many competitors despite its high popularity; So that the last version of Theano library 1.0.0 was released in 2017 and it was announced that it will no longer be upgraded.
Theano library and neural networks
Today, in the development of machine learning models, instead of using traditional statistical techniques, neural networks (inspired by the structure of the brain) are used. Neural networks are layered models used to process large amounts of data at high speed.
Since the process of processing this volume of data in the neural network may take days, it is necessary to optimize the codes. This is exactly what the Theano library does.
Features of Theano library
- Theano library can be run on both CPU and GPU architectures, that’s why it has high speed.
- The Theano library is compatible with NumPy and some other native Python libraries.
- Theano organizes and optimizes your calculations internally. This makes the calculations faster and more numerically stable.
- Theano tries to compile some operations without C code to speed up calculations.
- Theano includes a testing and validation unit that leads to the detection of various types of errors.
If you are wondering whether the Theano library is related to machine learning or not, I must say that although this library is not directly used in machine learning, it provides the necessary computational tools and methods for machine learning. The Theano library is the basis of many machine learning tools including Keras, Lasagne, PyLearn2 and Blocks.