Python is a popular programming language that has been widely used in the field of machine learning.. There are a lot of Python libraries for machine learning available, and in this guide, Let's take a look at some of the best.
Scikit-learn
Scikit-learn is one of the most popular Python libraries for machine learning. Offers a large number of machine learning algorithms, as well as methods for preprocessing and evaluating models. It's also easy to use, and can be up and running in a few minutes.
Keras
Keras is an open source deep learning library written in Python. It is easy to use and can be integrated with Scikit-learn and other machine learning frameworks. Keras also supports various neural network architectures, making it ideal for developing deep learning models.
TensorFlow
TensorFlow is an open source library for machine learning from Google. Supports building and training machine learning models using high-dimensional data. TensorFlow can also be integrated with Keras, allowing you to take advantage of the capabilities of both libraries.
PyTorch
PyTorch is an open-source library for Facebook's machine learning. Similar to TensorFlow in building and training machine learning models, but PyTorch has a more research-oriented approach. PyTorch is also easy to use and can be up and running in a few minutes.
Theano
Theano is an open source library for machine learning written in Python. It was developed by the LISA research team at the University of Montreal. Theano is similar to TensorFlow in building and training machine learning models, but focuses more on efficiency and performance.
These are just a few of the best Python libraries for machine learning available.. If you're interested in machine learning, It's important to take a look at all the libraries available and find the one that best suits your needs..
NumPy
NumPy is a fundamental package for scientific computing with Python. Provides an object ndarray Efficient multidimensional for homogeneous data storage. It also provides advanced mathematical functions to operate with that data..
Pandas
Pandas is a Python library that provides high-quality data structures and data analysis tools. Pandas makes working with tabular data easy and enjoyable.
Matplotlib
Matplotlib is a library for generating graphics in Python. Matplotlib can generate publication-quality graphics in a variety of output formats, Including PNG, JPG, EPS, SVG y PDF. Can also integrate with IPython Notebook and other Python environments.
SciPy
SciPy is a Python package for scientific computing. SciPy contains modules for optimization, integration, interpolation, spectroscopy, linear algebra, Special features, signal processing, image processing and probability.
Scikit-learn
Scikit-learn is a Python package for machine learning. Scikit-learn provides a uniform interface for a wide variety of machine learning algorithms. It also includes functions for data evaluation and preprocessing.
State models
State models is a Python package for statistical analysis. Statsmodels provides functions to estimate different statistical models, as well as to do regression analysis, Contingency tables and statistical tests.
Seaborn
Seaborn is a Python library for data visualization. Seaborn makes the graphics of statistical data are more attractive and easier to interpret. It also provides functions for multivariate data analysis.