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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Get started with machine learning in this Amazon SageMaker tutorial
Watch this Amazon SageMaker demo on how to deploy machine learning models on AWS. From setting up IAM roles to sorting your data, this tutorial will guide you through the process. Continue Reading
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Data visualization process yields 360 AI-driven analytics view
Data visualization tools find increasing uses as part of AI processes to explore data in the initial stages of model development and make outputs easier to digest. Continue Reading
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3 in-demand AI skills that boost data scientists' development
AI encompasses a wide range of disciplines, from advanced math to application development, and building a strong AI team starts with incredibly skilled data scientists. 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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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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How the top open source AI software drives innovation
In the world of AI, open source software is driving most of the innovation. But with vendor tools largely sidelined, what does this mean for things like security and technical support? 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
Manage Machine learning modeling
Learn to apply best practices and optimize your operations.
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How to achieve explainability in AI 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
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AI and climate change: The mixed impact of machine learning
While AI can play a role in helping researchers and conservationists address the impacts of climate change, it can also contribute to carbon emissions, making it a mixed blessing. Continue Reading
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How to create a data set for machine learning with limited data
A shortage of data for machine learning training sets can halt a company's AI development in its tracks. Turning to external sources and hidden data can solve the problem. 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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Serverless machine learning reduces development burdens
Getting started with machine learning throws multiple hurdles at enterprises. But the serverless computing trend, when applied to machine learning, can help remove some barriers. Continue Reading
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How to solve the black box AI problem through transparency
Ethical AI black box problems complicate user trust in the decision making of algorithms. As AI looks to the future, experts urge developers to take a glass box approach. Continue Reading
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March Madness analytics, AI help data scientist fill bracket
To create his March Madness bracket predictions, the head of data science at DataRobot uses a host of machine learning algorithms and some predictive analytics. Continue Reading