Data Science Investment Counter —Funding raised by UK data science companies in 2018.
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Amazon introduces 13 new machine learning capabilities and services

Amazon Web Services is offering machine learning algorithms and model packages on their AWS Marketplace, the company announced at the AWS re:Invent conference last week.

Users will be able to choose from free and paid algorithms and models from various categories such as computer vision (CV), natural language processing (NLP), speech recognition, text, data, voice, image, video analysis, and predictive analysis.

The company also announced new Amazon SageMaker features, which makes it easier for developers to create, train, and deploy machine learning models, including automatic, low-cost data labelling as well as reinforcement learning (RL).

SageMaker aims at eliminating the hardest parts of the machine learning process. It also makes it easier for developers to create, train, refine, and deploy machine learning models.

Swami Sivasubramanian, Vice President at Amazon Machine Learning, said, “Today’s announcements remove significant barriers to the successful adoption of machine learning.

“By reducing the cost of machine learning training and inference, introducing new SageMaker capabilities that make it easier for developers to build, train, and deploy machine learning models in the cloud and at the edge, and delivering new AI services based on our years of experience at Amazon.”

SageMaker uses MXNet, TensorFlow, PyTorch, and Chainer machine learning and deep learning frameworks and covers the machine learning workflow: label and prepare your data, choose an algorithm, train the algorithm, tune and optimise it for deployment, make predictions, and take action.

The AWS Marketplace Machine Learning now offers 150+ algorithms and model packages with a selection for different industries like retail, media, manufacturing, and HCLS. Customers can find solutions to a variety of use cases like breast cancer prediction, loan risk prediction, vehicle recognition, botnet attack detection, automotive telematics, motion detection, demand forecasting, and speech recognition.

Developers can browse the list of algorithms, select and subscribe to a machine learning solution, and deploy it using one of the following tools:
  • SageMaker console
  • Jupyter Notebook
  • SageMaker SDK
  • AWS Command Line Interface (AWS CLI)

The news comes after Amazon announced last week that the machine learning courses used to train engineers at Amazon are now available to all developers through AWS.

Writing on the company’s blog, Dr Matt Wood said that “Regardless of where they are in their machine learning journey, one question I hear frequently from customers is: ‘how can we accelerate the growth of machine learning skills in our teams?’ These courses, available as part of a new AWS Training and Certification Machine Learning offering, are now part of my answer.”

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