Deep Learning is a subset of Machine Learning and it works on the structure and functions of a human brain. It learns from the data that is structured and uses complex algorithms to train a neural net. This is a learning mechanism. Deep learning is a neural network somewhat looks like this there is something known as an input layer and then there is an output layer and in between there are a bunch of hidden layers so typically it would be at least one hidden layer and anything more than one hidden layer is known as a deep neural network so any neural network with more than three layers altogether right based known as a deep neural.
Open source platform like Python play an important role in the Machine learning market. In the recent years Python has gained a lot of attraction in Machine learning. Python has a large collection of libraries. The simplicity of python has attracted many developers to build libraries for Machine learning.
Some of the best Machine Learning libraries for Python are :
- Simple and efficient tools for data mining and data analysis
- It provides efficient solutions to machine learning problems
- NumPy is an acronym for "Numeric Python" or Numerical Library.
- It provides fast precompiled functions for mathematical and numerical routines
- Designed to enable fast experimentation with deep neural networks, it focuses on being user-friendly, modular, and extensible.
- TensorFlow is an open source software library for numerical computation using data flow graphs
- If you are using Google photos or Google voice search then indirectly you are using the models built using Tensorflow.
- It is a numerical computation library for Python
- It allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays
Hence, these are the best open source machine learning libraries written in Python tensor-flow is one of the most popular machine learning frameworks and the tensors are really very handy in terms of keeping the data compact because they are like multi-dimensional arrays so the data is stored in tensors and then it is fed into the neural network.