The Power of Theano: Simplifying Machine Learning and Deep Learning
History of Theano :
It was created by the Montreal Institute for Learning Algorithms (MILA) at the University of Montreal, Theano enables researchers and developers to construct, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.
Important points to Know about Theano :
> Theano is a Python library that allows us to evaluate mathematical operations including multi-dimensional arrays so efficiently.
> It is mostly used in building Deep Learning Projects.
> It works a way more faster on Graphics Processing Unit (GPU) rather than on CPU.
> It is mainly designed to handle the types of computation required for large neural network algorithms used in Deep Learning.
> Theano is a sort of hybrid between numpy and sympy, an attempt is made to combine the two into one powerful library.
How to install Theano :
pip install theano
Why Theano Python library?
Symbolic Expressions: Theano enabled the creation of symbolic expressions, allowing developers to define mathematical operations and functions without evaluating them immediately. This approach facilitated optimization and automatic differentiation crucial for training neural networks.
Efficient GPU Utilization: Theano efficiently utilized Graphics Processing Units (GPUs) to accelerate computation, resulting in faster training times for deep neural networks.
Automatic Differentiation: It provided automatic differentiation, allowing for the computation of gradients required for optimization algorithms like backpropagation in neural networks.
Optimization and Compilation: Theano optimized mathematical expressions and compiled them into efficient code, enhancing performance for both CPU and GPU execution.
Deep Learning Research: Theano was widely used in academia and research for its flexibility in experimenting with various neural network architectures, making it a crucial tool for advancing the field of deep learning.
Foundation for Other Frameworks: The concepts and techniques developed in Theano laid the groundwork for subsequent deep learning frameworks like TensorFlow and PyTorch.
For your reference : https://www.javatpoint.com/tensorflow-vs-theano#:~:text=Theanoisafullypythonbased