AWS announces Amazon ML Solutions Lab to accelerate application of machine learning within organizations



Amazon Web Services Inc. (AWS), an Amazon.com company, announced Wednesday the Amazon ML Solutions Lab, a new program that connects machine learning experts from across Amazon with AWS customers to help identify practical uses of machine learning inside customers’ businesses, and guide them in developing new machine learning-enabled features, products, and processes.

The Amazon ML Solutions Lab combines hands-on educational workshops with brainstorming sessions to help customers “work backwards” from business challenges, and then go step-by-step through the process of developing machine learning-based solutions. Customers will work with Amazon machine learning experts to prepare data, build and train models, and put models into production.

At the end of the program, customers will be able to take what they have learned through the process and use it elsewhere in their organization.

The Amazon ML Solutions Lab pairs the team with Amazon machine learning experts to prepare data, build and train models, and put models into production. It combines hands-on educational workshops with brainstorming sessions and advisory professional services to help ‘work backwards’ from business challenges, and then go step-by-step through the process of developing machine learning-based solutions.

The Amazon ML Solutions Lab Express is a four to five week accelerated program which brings developers on-site with Amazon machine learning experts for an intensive boot camp (typically one week), followed by guidance and hands-on implementation with custom modeling for around three to four weeks.

It has been designed for organizations which have already established a relevant data lake and data catalog, and who already have a large volume of high quality, trusted, labeled data available for modeling. The primary goal of ML Solutions Lab Express is to work on feature engineering and building models quickly.

While AWS customers across various industries are moving quickly to adopt machine learning, relatively few organizations have machine learning expertise, and many are challenged in taking the first steps to introduce machine learning and artificial intelligence into their products and processes.

Amazon has been investing in machine learning for 20 years, using machine learning and deep learning to make product recommendations, optimize robotic picking routes in fulfillment centers, sharpen algorithms that inform Amazon’s supply chain, forecasting, and capacity planning, provide the intelligence in Amazon Alexa’s natural language understanding (NLU) and automated speech recognition (ASR), and support Amazon’s drone delivery initiative (Prime Air). Thousands of engineers across Amazon are working on machine learning.

The Amazon ML Solutions Lab provides customers access to the same talent that built many of these machine learning-powered products and services. Amazon ML Solutions Lab engagements (which range from weeks to months depending on the nature of the solution) are designed to take customers through the full process of implementing machine learning, combining educational workshops and boot camps, advisory professional services, and hands-on help building custom models with a customer’s own data.

For organizations who already have data prepared for machine learning, AWS offers the ML Solutions Lab Express. This four-week intensive program starts with a boot camp hosted at Amazon, and is followed by three weeks of intensive problem-solving and machine learning model building with Amazon machine learning experts.

“We can’t wait for developers to start their journeys into machine learning with the Amazon ML Solutions Lab,” said Swami Sivasubramanian, Vice President of Amazon AI. “By combining the expertise of the best machine learning scientist and practitioners at Amazon with the deep business knowledge of our customers, the Amazon ML Solutions Lab will help customers get up to speed on machine learning quickly, and start putting machine learning to work inside their organizations.”

Janssen, the pharmaceutical companies of Johnson & Johnson, is committed to collaborating with the world for the health of everyone in it. “We recently reached out to the Amazon ML Solutions Lab to collaborate with our data scientists on a deep learning initiative,” said Jesse Heap, Senior IT Manager, Data Sciences at Janssen Inc. “We are pleased to state that the Amazon ML Solutions Lab quickly kicked off a deep learning workshop through which machine learning experts from Amazon have been brainstorming with and training our data scientists on applying deep learning to pharma-related use cases.”

The Washington Post is one of the leading daily newspapers in the United States. “At The Washington Post, we are continually working to improve the experience of our readers using machine learning algorithms,” said Dr. Sam Han (PhD), director of data science at The Washington Post. “We are pleased to collaborate with the Amazon ML Solutions Lab to build models in application areas such as comment moderation, keyword tagging, and headline generation. Through our joint sessions, we have already developed a much better understanding of the challenges involved, and a path to solution, and we look forward to partnering with the Amazon ML Solutions Lab to build out cutting-edge machine learning models to improve the accuracy of our existing models.”

With 189 member countries, staff from more 170 countries, and offices in over 130 locations, the World Bank Group is a unique global partnership. “We are excited to collaborate with Amazon ML Solutions Lab folks to leverage machine learning in our mission to end extreme poverty and promote shared prosperity, ” Misha Lokshin, World Bank, Development Economics Group.

The Amazon ML Solutions Lab is launching globally; however, the ML Solutions Lab Express will not be currently supported outside the United States as the Express program requires scientists to have more frequent touchpoints, and in that regard, AWS is currently restricted by its limited on-site presence outside the US. This page will be updated when the ML Solutions Lab Express becomes available outside the US.

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