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
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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.
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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.
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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.
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May 08, 2019
08
May'19
Google adds Firebase AI tools to make ML mobile dev easier
A new Google Firebase update simplifies machine learning app development. The update is part of a trend of making machine learning more accessible for developers to create and deploy.
Pattern recognition and machine learning Get Started
Bring yourself up to speed with our introductory content
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artificial neural network (ANN)
In information technology (IT), a neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Continue Reading
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Machine learning platform architecture demands deep analysis
This handbook offers advice on choosing machine learning platforms and using them to get accurate and meaningful information from analytics applications. Continue Reading
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How pattern matching in machine learning powers AI
Pattern matching may sound like a simple idea, but it's being used to create some highly advanced AI tools, powering everything from image recognition to natural language applications. Continue Reading
Evaluate Pattern recognition and machine learning Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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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
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5 types of machine learning algorithms you should know
Machine learning can assist enterprises by quickly modeling large data sets. Choosing the right algorithm depends on the desired outcome and the makeup of your data science team. Continue Reading
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3 GAN use cases that showcase their positive potential
GANs' ability to create realistic images and deepfakes have caused industry concern. But, if you dig beyond fear, GANs have practical applications that are overwhelmingly good. Continue Reading
Manage Pattern recognition and machine learning
Learn to apply best practices and optimize your operations.
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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
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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
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AI network security tool autonomously does microsegmentation
To ensure network security, a U.S. law firm has turned to automated network microsegmentation vendor Edgewise. The startup uses machine learning to deploy microsegmentation. 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.
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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
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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
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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