Machine Learning Tools You Should Know About

Print Friendly, PDF & Email

Artificial intelligence, big data, and hybrid cloud computing have made a significant impact on the business industry. Joining this list is machine learning. This new advancement in business technology provides machines with the ability to learn data and store information without being specifically programed to do so. Machine learning tends to focus on developing computer programs that are able to make the necessary adjustments when new data presents itself.

Every new development in the technological industry is followed by new tools. These tools work to help businesses and users stay up to date with all the technological advancements. Some specific tools that will help businesses as they incorporate and work with machine learning are Amazon Machine Learning, Tensor Flow, Azure Machine Learning Studio, H20, Caffe, MLlib, and Torch.

Amazon Machine Learning

The Amazon Machine Learning program originates from the same technology Amazon’s internal data scientist community has used for years. Amazon uses advanced algorithms and formulas to create machine learning models that help find patterns in existing data. These models are then used to process the new data and help generate predictions.

Amazon Machine Learning is able to generate millions of predictions daily in addition to providing those predictions quickly and accurately. Businesses that incorporate Amazon Machine Learning are able to purchase this hardware or software upfront and pay as they go. This means businesses are able to start small and save money while their company is still developing.

Tensor Flow

Tensor Flow is an open source software library used mainly for numerical computations that use data flow graphs. Google developed Tensor Flow to help build machine learning into its own system and aid with neural networks research. After it was developed, researchers discovered that the system can be applicable to a wide variety of other domains. Tensor Flow is known for being faster, smarter, and more flexible, making it more easily adaptable to different products and research, both old and new. Tensor Flow is a highly scalable machine learning system that is able to be run on a variety of systems, from one single source or hundreds of computers in a data center.

Azure Machine Learning Studio

Azure Machine Learning Studio, or AMLS, functions as an as-a-service framework. It is aimed at enabling organizations and businesses to adjust to machine learning solutions in the Azure cloud. It is used as a collaborative, drag-and-drop tool that can aid in building, testing, and deploying predictive analytics solutions for a business’s data. AMLS develops models as web services that can easily be applied to custom apps or businesses. The Machine Learning Studio is where customers can store and use their research, predictive analytics, cloud resources and data.


H2O, also known as H2O,ai, is developing mission critical data products for some of the world’s most influential companies across the country. In fact, H2O is the world’s most used open source deep learning platform. It is utilized by more than 80,000 data scientists and researchers and over 9,000 businesses and organizations around the world. H2O offers a web-based user interface alongside access to a library of machine learning software designed to aid in the process of starting or switching to machine learning.


This extensive platform encourages application and innovation to the businesses and organizations that use it. The extensive code Caffe uses leads to a more active development. Over a thousand developers helped make significant changes that contributed to the development of machine learning. Caffe aids academic research projects, startup prototypes, and large-scale industrial applications in vision, speech, and multimedia.


MLlib is Apache Spark’s machine learning library that contains common learning algorithms and utilities that include classification, regression, clustering, collaborative filtering, dimensionality reduction and underlying optimization primitives. MLlib is easy to deploy and runs on existing clusters of data. MLlib has yielded better results than the one-pass approximations often used by other softwares.


Torch is an open source machine learning development framework that is widely used across the country. It allows neural net based algorithms to be run across GPU hardware without the need for coding at hardware level. Torch is easy to use and efficient due to its easy and fast scripting language. Torch’s goal is to have maximum flexibility and speed in building scientific algorithms without making the process difficult.

Amazon Machine Learning, Tensor Flow, Azure Machine Learning Studio, H20, Caffe, MLlib, and Torch are just an introduction to the most popular tools, extensions and resources for using machine learning solutions. With the growth of artificial intelligence and machine learning, it’s anticipated that there will be more advancements in the technological and business world.

Contributed by: Linda Gimmeson, a tech writer with a focus in big data, machine learning, & IoT. Linda discusses big data, emerging technologies, and how companies can get real value out of their data.


Sign up for the free insideBIGDATA newsletter.

Speak Your Mind