Machine learning modeling
There are a number of ways to tackle machine learning modeling. Find content on supervised and unsupervised machine learning algorithm training and modeling processes, including expert tips to help you evaluate, choose and use the right machine learning model to deliver accurate predictive outputs to solve business problems.
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Machine learning modeling News
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November 07, 2019
07
Nov'19
Booz Allen releases Modzy AI platform and marketplace
Booz Allen Hamilton introduced an AI platform and marketplace made for uploading, deploying and managing AI models across a scalable environment.
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October 30, 2019
30
Oct'19
Google releases TensorFlow Enterprise for enterprise users
With the new TensorFlow for enterprises, organizations running previous versions of TensorFlow can get long-term support, including security updates and select bug fixes.
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August 09, 2019
09
Aug'19
IBM interprets machine models with AI Explainability kit
IBM's open source AI Explainability 360 toolkit packages algorithms and training examples to help humans better understand the decision-making process of machine learning models.
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June 20, 2019
20
Jun'19
DataRobot acquisition of ParallelM to enhance AI management
DataRobot machine learning tools should see a boost following the company's acquisition of ParallelM, a startup with tools for deploying, managing and monitoring AI.
Machine learning modeling Get Started
Bring yourself up to speed with our introductory content
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Learn the business value of AI's various techniques
To drive business value from AI, business managers need to distinguish between the various AI techniques, starting with the many flavors of machine learning. Continue Reading
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machine learning
Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Continue Reading
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4 main types of AI explained
The emergence of artificial superintelligence will change humanity, but it's not happening soon. Here are the types of AI leading up to that new reality. Continue Reading
Evaluate Machine learning modeling Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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Explore common machine learning use cases in IT operations
Machine learning is a hot topic with use cases that span IT and the business. Learn how IT operations teams most commonly apply the technology -- from help desk response to gauging end-user satisfaction. Continue Reading
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Deep learning's role in the evolution of machine learning
Machine learning has continued to evolve since its beginnings some seven decades ago. Learn how deep learning has catalyzed a new phase in the evolution of machine learning. Continue Reading
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Comparing supervised vs. unsupervised learning
Learn how LinkedIn, Zillow and others choose between supervised learning, unsupervised learning and semi-supervised learning for their machine learning projects. Continue Reading
Manage Machine learning modeling
Learn to apply best practices and optimize your operations.
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How to build a machine learning model in 7 steps
Building a viable, reliable and agile machine learning model that streamlines operations and bolsters business planning takes patience, preparation and perseverance. Continue Reading
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MLOps tools hope to boost enterprise model implementation
Taking notes from DevOps lifecycle management, machine learning operations tools and platforms seek to improve accuracy, ease integration problems and keep models trained. Continue Reading
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4 explainable AI techniques for machine learning models
At its core, AI is a complex modeling process with layers of information. In order to be able to explain the algorithm's decision-making process, start with its input data. Continue Reading
Problem Solve Machine learning modeling 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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Understanding how deep learning black box training creates bias
Bias in AI is a systematic issue that derails many projects. Dismantling the black box of deep learning algorithms is crucial to the advancement and deployment of the technology. Continue Reading
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6 ways to reduce different types of bias in machine learning
As adoption of machine learning grows, companies must become data experts -- or risk results that are inaccurate, unfair or even dangerous. Here's how to combat ML bias. Continue Reading
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The future state of machine learning needs improved frameworks
Utilizing machine learning in the collection and processing of data would most likely lead to more widespread adoption of AI based on the technology. Continue Reading