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Learning analytics - Wikipedia 

Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. The growth of online learning since the 1990s, particularly in higher education, has contributed to the advancement of Learning Analytics as student data can be captured and made ...

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(01/01/1970 01:00)

Machine Learning: What it is and why it matters | SAS 

It might involve traditional statistical methods and machine learning. Data mining applies methods from many different areas to identify previously unknown patterns from data. This can include statistical algorithms, machine learning, text analytics, time series analysis and other areas of analytics. Data mining also includes the study and ...

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(01/01/1970 01:00)

What is Learning Analytics? - Society for Learning Analytics Research ... 

LEARNING ANALYTICS is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs, as defined back in 2011 for the first LAK, this general definition still holds true even as the field has grown. Learning analytics is both an academic field and commercial marketplace ...

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(01/01/1970 01:00)

Azure Machine Learning - ML as a Service | Microsoft Azure 

See why Forrester named Azure Machine Learning a Leader in The Forrester Wave TM: Notebook-Based Predictive Analytics And Machine Learning, Q3 2020. Forrester Total Economic Impact TM (TEI) study The Forrester Consulting Total Economic Impact TM (TEI) study, commissioned by Microsoft, examines the potential return on investment (ROI) enterprises may realize with Azure Machine Learning.

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(01/01/1970 01:00)

What Is Machine Learning and Why Is It Important? - SearchEnterpriseAI 

Machine learning is a type of artificial intelligence ( AI ) that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output value within an acceptable ...

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(01/01/1970 01:00)

Machine Learning and Artificial Intelligence - Amazon Web Services 

Get deeper insights from your data while lowering costs with AWS machine learning (ML). AWS helps you at every stage of your ML adoption journey with the most comprehensive set of artificial intelligence (AI) and ML services, infrastructure, and implementation resources.

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(01/01/1970 01:00)

Image Classification using Machine Learning - Analytics Vidhya 

This article was published as a part of the Data Science Blogathon. Dear readers, In this blog, we will be discussing how to perform image classification using four popular machine learning algorithms namely, Random Forest Classifier, KNN, Decision Tree Classifier, and Naive Bayes classifier.

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(01/01/1970 01:00)

Analytics India Magazine | Artificial Intelligence, Data Science ... 

Analytics India Magazine chronicles technological progress in the space of analytics, artificial intelligence, data science & big data in India

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(01/01/1970 01:00)

Online Learning and Training - O'Reilly Media 

Expertly curated, high-quality content. O’Reilly’s savvy editorial team delivers exclusive books, videos, and learning experiences—including early release titles and case studies from leading organizations—plus resources from more than 200 of the world’s most respected publishers, including Pearson, Packt, Wiley, HarperCollins, and others.

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(01/01/1970 01:00)

Data Science & Business Analytics Course Online in India - Great Learning 

It is an open-source data analytics, reporting, and integration platform, where it incorporates several machine learning and data mining components and provides software for data preprocessing and data analysis. This module will teach you how to use KNIME software to create and increase data science production, enabling you to focus on what you do the best.

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(01/01/1970 01:00)

Dernière mise à jour : 28/11/2022 23:31