Pattern recognition and machine learning

Working with pattern recognition and machine learning platforms allows organizations to extract information from big data. This core AI technology can be tricky, but extremely beneficial for enterprises. Read about machine learning best practices and techniques to uncover valuable predictive insights.

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Pattern recognition and machine learning News

January 06, 2020 06 Jan'20
U.S. restricts exports of geospatial AI software

The Trump administration's move to limit export of AI-based geospatial imaging software extends U.S. restrictions on technology that foreign countries could use to develop weapons systems.
October 30, 2019 30 Oct'19
The importance of AI for fraud prevention

As fraudsters become increasingly more professional and technologically advanced, financial organizations need to rely on products that use AI for to prevent fraud.
September 25, 2019 25 Sep'19
Cambridge Consultants demos show uses of AI

At a demo event, Cambridge Consultants highlighted some of the applications of AI with a system that can count TB cells in a sputum sample and a system that can fix image distortion.
July 02, 2019 02 Jul'19
Open source machine learning accelerates winemaking

Using open source machine learning, Palmaz Vineyards developed a tool to automatically alert winemakers of environmental conditions. Soon, the data flowed like wine.

Pattern recognition and machine learning Get Started

Bring yourself up to speed with our introductory content

machine teaching

Machine teaching is the emerging practice of infusing context -- and often business consequences -- into the selection of training data used in artificial intelligence (AI) machine learning so that the most relevant outputs are produced by the ... Continue Reading
face detection

Face detection -- also called facial detection -- is an artificial intelligence (AI) based computer technology used to find and identify human faces in digital images. Continue Reading
The peaks and pitfalls of hyper-personalization marketing

As consumers begin to revolt against unlimited personal data collection and usage, the longevity of hyper-personalized communication may be cut short. Continue Reading

Evaluate Pattern recognition and machine learning Vendors & Products

Weigh the pros and cons of technologies, products and projects you are considering.

Comparing semi-supervised machine learning vs. one-shot learning

Machine learning models require massive amounts of data -- labeled or unlabeled. Two new approaches are hoping to curtail the need for large data sets and overarching human interference. Continue Reading
Autonomous retail cuts operational costs, personalizes shopping

Companies are starting to deploy popular AI technologies like RFID, facial recognition and sensor tracking to provide consumers with autonomous shopping experiences. Continue Reading
Data visualization in machine learning boosts data scientist analytics

Data scientists offer practical insights into the role of visualization tools in building, exploring, deploying and monitoring their machine learning models. Continue Reading

Manage Pattern recognition and machine learning

Learn to apply best practices and optimize your operations.

AI in networking helps keep systems running

Network administrators are increasingly using AI tools to help them manage the growing complexity of their network infrastructure, a task that's getting more complicated by the day. Continue Reading
Using small data sets for machine learning models sees growth

While massive data sets allow for easy training, developers are using new techniques to mine and transfer data that allows for training on limited labeled information. Continue Reading
Understand the top 4 use cases for AI in cybersecurity

AI applications in security offers organizations four unique benefits. Learn how machine learning advances can change industry approaches to threat detection and prevention. Continue Reading

Problem Solve Pattern recognition and machine learning Issues

We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.

Brands must allay worries for AI in transportation to take hold

The personal mobility market is turning to emotional analysis and AI to negate fear and trepidation around emerging vehicle technology and the future of transportation. Continue Reading
Collaborative robots' safety stalls enterprise implementation

Cobots are promising big gains, especially in enterprises utilizing manual labor. However, due to a number of safety concerns, human workers are still at risk. Continue Reading
How to solve deep learning challenges through interoperability

The challenges of training and overseeing advanced neural networks is leading to an implementation bottleneck in deep learning technology. Continue Reading