- Trending Categories
Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
What are the various useful components of the Python ecosystem for Machine Learning?
The Python ecosystem, growing at a rapid pace day by day, became the dominant platform for machine learning. Here we will discover the most useful components of the Python ecosystem for machine learning. Let’s get started.
SciPy
SciPy, pronounced as “Sigh Pie”, is an ecosystem of Python open-source libraries for performing Mathematical, Scientific, and Engineering computations. SciPy is comprised of the following core packages relevant to machine learning −
NumPy − NumPy is a base N-dimensional array package for SciPy that allows us to efficiently work with data in arrays.
Matplotlib − Matplotlib is used to create comprehensive 2-D charts and plots from data.
Pandas − Pandas is an open-source Python package used to organize and analyze our data.
How to install SciPy
There are many ways to install SciPy, but followings are the two most popular ways −
- Using package management on your platform.
- Using Pip-a Python package management tool
You can also check how-to instructions for various platforms on the page https://www.tutorialspoint.com/scipy/scipy_environment_setup.htm
Scikit-learn
Scikit-learn (Sklearn) is the most useful and robust Python ecosystem for machine learning. Scikit-learn, built upon and requires SciPy ecosystem, provides us efficient tools for machine learning and statistical modeling including classification, regression, clustering, and dimensionality reduction. It is also open source and commercially usable under the BSD license. You can learn more about Scikit-learn at ttps://www.tutorialspoint.com/scikit_learn/index.htm
How to install Scikit-learn
It is recommended to use the same methods to install Scikit-learn as you used install SciPy above. Apart from that, another easiest method to install Scikit-learn is to use conda. The command is given below −
conda install scikit-learn
Installing the ecosystem − an easier way
One of the easiest ways to install the ecosystem is to use a distribution called Anaconda
. It includes Python, Scipy, and scikit-learn i.e., everything one needs to learn, practice, and use machine learning with Python environment.
- Related Articles
- What are the various challenges for machine learning practitioners?
- What are different components of a machine learning algorithm?
- What are Some Good Python Packages for Machine Learning?
- What are the various Components of Selenium?
- What are the applications of Machine Learning?
- What are the Classifications of Machine Learning?
- Is python the best choice for machine learning?
- What are the different learning styles in machine learning algorithms?
- What are the various components of blood ? State their functions.
- What are business benefits of machine learning?
- What are Some Great Examples of Machine Learning?
- Is python necessary to learn for machine learning
- Best Open-source Python Libraries for Machine Learning
- Machine Learning – The Intelligent Machine
- What are the different kinds of gradient descent algorithms in Machine Learning?
