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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July 15, 2020
15
Jul'20
Care provider uses automated machine learning in healthcare
An assisted living and transitional care provider uses DataRobot to automate the process of building and deploying machine learning models, enabling it to deploy models quickly.
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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.
Machine learning modeling Get Started
Bring yourself up to speed with our introductory content
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unsupervised learning
Unsupervised learning refers to the use of artificial intelligence (AI) algorithms to identify patterns in data sets containing data points that are neither classified nor labeled. Continue Reading
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supervised learning
Supervised learning is an approach to creating artificial intelligence, where the program is given labeled input data and the expected output results. Continue Reading
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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
Evaluate Machine learning modeling Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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Explore the foundations of artificial neural network modeling
Dive into Giuseppe Bonaccorso's recent book 'Mastering Machine Learning Algorithms' with a chapter excerpt on modeling neural networks. Continue Reading
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Bias in machine learning examples: Policing, banking, COVID-19
Human bias, missing data, data selection, data confirmation, hidden variables and unexpected crises can contribute to distorted machine learning models, outcomes and insights. Continue Reading
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14 best machine learning platforms for 2020
Turn ever-growing volumes of data into enterprise insights with the right platform for machine learning. Learn more about the vendors and products in this cutting-edge market. Continue Reading
Manage Machine learning modeling
Learn to apply best practices and optimize your operations.
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Machine learning and bias concerns weigh on data scientists
Data scientists are forever vigilant in their desire to identify and eliminate the many forms of bias that can compromise the credibility of machine learning models. Continue Reading
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Responsible AI champions human-centric machine learning
Encompassing ethics, transparency and human centricity, responsible AI is an effective approach to deploying machine learning models and achieving actionable insights. Continue Reading
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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
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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Data science's ongoing battle to quell bias in machine learning
Machine learning expert Ben Cox of H2O.ai discusses the problem of bias in predictive models that confronts data scientists daily and his techniques to identify and neutralize it. Continue Reading
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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