Top 3 Open Source Libraries to Feed Your Machine Learning Knowledge

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The Scoop: Artificial Intelligence is surely going to be in our futures. If you want to learn more about the future with Artificial Intelligence, here are some open source libraries to feed your machine learning knowledge.

Artificial Intelligence or AI is the evolution of our technology. It has the potential to help with many tasks in the future along with machine learning and deep learning.

Machine learning is one of the ways you can train AIs to be able to learn on the way without bothering to write a series of complex codes. This makes it easier to manage and create an AI that can benefit mankind. However, everyone needs to start at the beginning.

Here are the top three open source libraries where you can get that needed knowledge to get started.

TensorFlow

TensorFlow
Via Wikipedia

Developed by Google Brain Team, you can never go wrong with TensorFlow. This allows the team to handle language understanding and perceptual tasks. It also enables you to conduct research on machine learning and deep neural networks. TensorFlow is Python-based and is used on Google products such as Gmail, photo, search, and speech recognition. Additionally, Google also offers people free AI lessons with TensorFlow APIs.

Amazon Machine Learning

aml
Via Amazon AWS

If you are a developer believing in the saying of learning on the job, Amazon Machine Learning or AML is for you. AML is packed with useful tools and helpful wizards that will guide you on your way to learning about Machine Learning. This enables you to create machine learning models and learning all the complexity of how each function while you work on it.

Shogun

shogun
Via NumFOCUS

Shogun is a very handy tool that includes many state-of-the-art algorithms. What makes this great is that it can run on various platforms such as Windows, Linux, and MacOS. It provides data structures for machine learning problems and is written in C++. Other than that, it supports bindings to vast machine learning libraries such as SLEP, Tapkee, SVMLight, and more.

Supplement Your Machine Learning Knowledge

As another saying goes, knowledge is key. In order to learn what technology is capable of and isn’t, you have to know the ins and outs of it first. These resources will not only give you knowledge by giving you information but also lets you experience how machine learning is incorporated, how it works and more.

So what is your pick from the three resources to boost your machine learning knowledge?

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Featured Image: DigitalOcean

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