RocketML is a HPC software infrastructure built from ground up to optimize every millisecond so that data scientists can iterate on their machine learning experiments faster at lower Total Cost.

In computer architecture, Amdahl's law is used to predict the theoretical speedup when using multiple processors. RocketML is built to scale by eliminating weak links. Every component is tuned so that the system is pushed to the limits of Amdahl's law. As a result RocketML outperforms all existing Distributed Machine Learning systems by orders of magnitude.

To build models with superior accuracy Data Scientists and Researchers need to iterate on their ideas. If a single iteration takes hours and days, training time becomes a deterrent to experimentation. Slow training is not an experience that is conducive to research and development of models. In light of increasing data sizes, flat computer performances, Distributed Machine Learning is an indispensable tool for researchers to get their job done. RocketML is THE most efficient distributed machine learning system in the market. It save researchers time & money with no limits on data sizes.

Subscribing to RocketML is easy. With no software to install, RocketML is available on AWS marketplace on a “pay as you go” service — where you don't have to worry about long term contracts. Take it for a test drive! Contact us at support@rocketml.net if you like longer free trial duration or support. We are absolutely thrilled to hand hold and make you successful.

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RocketML helps convert your ideas and big data into your very own AI application is just 4 steps. With RocketML engine, you not only buy a technology, you also get access to our development know-how. Together with your team, we put in place a state of the art set of technologies for a variety of AI solutions. With almost all customers we take concepts to deployed AI models in less than 3 months.

Step 1: Technology Introduction

Intended for a mixed audience of business and technical experts, this onsite presentation sheds light on the theoretical background, the functionalities and the application spectrum of machine learning technology and RocketML in specific. The technology introduction is free of charge and aims at establishing a common language.

Step 2: Exploration Workshop

In this workshop, business owners and technical implementers will take a deep dive into how RocketML technology can be applied to their domain or business-specific use cases. The workshop covers technical implementation aspects and analyzes the business potential of the solutions discussed.

Step 3: Proof of Concept

The goal of this short project is to demonstrate the capabilities and effectiveness of the RocketML technology for a specific business case.

Step 4: Pilot Project & Rollout

The objective of a pilot project is to deliver a solution for a complete business case and facilitate its integration into a production environment. This phase ends with the involvement of the first end users in the agile development cycle and potential into production environment depending on type of company/project.

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