5 Open Source Libraries to Aid in Your Machine Learning Endeavors

Machine learning is changing the way we do things, and it's becoming mainstream very quickly.

learn more about Michael Georgiou

By Michael Georgiou


Opinions expressed by Entrepreneur contributors are their own.

Machine learning is changing the way we do things, and it's becoming mainstream very quickly.

Related: 5 Strategies From Top Firms on How to Use Machine Learning

While many factors have contributed to this increase in machine learning, one reason is that it's becoming easier for developers to apply it, thanks to open source frameworks.

If you're not familiar with this technology, and feel confused about some of the terms used, such as "framework" and "library," here are the definitions:

Framework. A vague term, to be sure; even those who regularly use it can't agree on its exact definition. However, in most cases, "framework" refers to a bunch of programs, libraries and languages you have built to use in application development. Think of a framework as a base for getting started.

Library. A collection of objects or methods that your application uses. It's a file with re-usable code that can be shared by many applications, so you don't have to write the same code repeatedly. Instead, you link to the library.

As one online user put it: "The key difference between a library and a framework is 'inversion of control.' When you call a method from a library, you are in control. But with a framework, the control is inverted: The framework calls you."

Still confused? Check out this helpful YouTube video about the difference between a framework and a library.

If you're diving into machine learning in a big way, you're probably seeking resources to help guide you. There are many frameworks available, but here are some of our favorites to help you get started.

Related: 5 Reasons Machine Learning Is the Future of Marketing

The machine learning resources you'll use

TensorFlow. TensorFlow was developed by the Google Brain Team to handle perceptual and language understanding tasks. It can also conduct research on machine learning and deep neural networks. TensorFlow has a Python-based interface. It's used in many of Google's products, handling speech recognition, Gmail, photos and search.

What's useful about this framework is that it can perform elaborate mathematical computations and see data flow graphs. TensorFlow is flexible, meaning users can write their own libraries on top of it. It's also portable, able to run in the cloud and on mobile computing platforms as well as with CPUs or GPUs.

Amazon Machine Learning. Amazon Machine Learning (AML) is built for developers, with many tools and wizards to help you create machine learning models without having to learn all the complexities of how machine learning works. With AML, you can generate predictions and use data from Amazon Redshift, the data warehouse Platform as a Service.

Shogun. Shogun has many state-of-the-art algorithms, making it a handy tool. It is written in C++ and provides data structures for machine learning problems. It can run on Windows, Linux and MacOS. Further, Shogun is helpful because it supports bindings to other machine learning libraries. The list is extensive, but they include: SVMLight, LibSVM, libqp, SLEP, LibLinear, VowpalWabbit and Tapkee.

Accord.NET. Accord.NET, a NET machine learning framework, has multiple libraries to handle everything from pattern recognition, image and signal processing to linear algebra, statistical data processing and more. Accord is useful because it has so much to offer, including 40 different statistical distributions, more than 30 hypothesis tests, and more than 38 kernel functions.

Apache Signa, Apache Spark MLlib and Apache Mahout. Apache Signa, Apache Spark MLlib, and Apache Mahout are three frameworks with a lot to offer. Apache Signa is mostly used in natural language processing and image recognition; it can run over a wide range of hardware.

Mahout provides Java libraries and Java collections for various kinds of mathematical operations. Spark MLlib was created with the goal of making machine learning easy. It brings together many learning algorithms and utilities, including classification, clustering, dimensionality reduction and more.

Related: 5 Innovative Uses for Machine Learning

The data sets you'll need

Once you get going, you'll also need some data. If you're just learning and need to practice, here are some useful data sets to try, all available on GitHub:

Michael Georgiou

Co-Founder and CMO of Imaginovation

Michael Georgiou is the the co-founder and CMO of Imaginovation, a full-service digital agency based out of Raleigh, N.C.

Related Topics

Editor's Pick

Everyone Wants to Get Close to Their Favorite Artist. Here's the Technology Making It a Reality — But Better.
The Highest-Paid, Highest-Profile People in Every Field Know This Communication Strategy
After Early Rejection From Publishers, This Author Self-Published Her Book and Sold More Than 500,000 Copies. Here's How She Did It.
Having Trouble Speaking Up in Meetings? Try This Strategy.
He Names Brands for Amazon, Meta and Forever 21, and Says This Is the Big Blank Space in the Naming Game
Thought Leaders

The Collapse of Credit Suisse: A Cautionary Tale of Resistance to Hybrid Work

This cautionary tale serves as a reminder for business leaders to adapt to the changing world of work and prioritize their workforce's needs and preferences.

Green Entrepreneur

A Massive Hole In the Sun May Cause Dazzling Light Show Here On Earth

NASA says the coronal hole could blast the Earth with solar winds as early as Friday. What does this mean?

Business News

These Are the Most and Least Affordable Places to Retire in The U.S.

The Northeast and West Coast are the least affordable, while areas in the Mountain State region tend to be ideal for retirees on a budget.

Business News

The 'Airbnbust' Proves the Wild West Days of Online Vacation Rentals Are Over

Airbnb recently reported that 2022 was its first profitable year ever. But the deluge of new listings foreshadowed an inevitable correction.

Business News

Gen Z Loves the Toyota Camry. Here's What Car Brands Boomers Love Most

S&P Global Mobility provides data on what types of each age group likes the most, based on car registration.