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The European Information Technologies Certification Institute - EITCI ASBL

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Questions and answers designated by tag: Machine Learning Applications

Does an unsupervised model need training although it has no labelled data?

Thursday, 29 February 2024 by Bernard

An unsupervised model in machine learning does not require labeled data for training as it aims to find patterns and relationships within the data without predefined labels. Although unsupervised learning does not involve the use of labeled data, the model still needs to undergo a training process to learn the underlying structure of the data

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, First steps in Machine Learning, The 7 steps of machine learning
Tagged under: Anomaly Detection, Artificial Intelligence, Clustering Algorithms, Dimensionality Reduction, Machine Learning Applications, Unsupervised Learning

Besides addressing fall armyworm infestations, what other sectors do Nazirini and her team believe machine learning can revolutionize?

Sunday, 06 August 2023 by EITCA Academy

Nazirini and her team firmly believe that machine learning has the potential to revolutionize several sectors beyond addressing fall armyworm infestations. They recognize the immense power of machine learning algorithms in analyzing large datasets and making accurate predictions, which can be applied to various domains. In the context of crop disease management, machine learning can

  • Published in Artificial Intelligence, EITC/AI/TFF TensorFlow Fundamentals, TensorFlow Applications, Using machine learning to tackle crop disease, Examination review
Tagged under: Agricultural Robotics, Artificial Intelligence, Food Supply Chain Management, Machine Learning Applications, Plant Breeding, Precision Agriculture

How can users analyze GitHub commit data using Datalab and what insights can be obtained?

Wednesday, 02 August 2023 by EITCA Academy

To analyze GitHub commit data using Google Cloud Datalab, users can leverage its powerful features and integration with various Google tools for machine learning. By extracting and processing commit data, valuable insights can be obtained regarding the development process, code quality, and collaboration patterns within a GitHub repository. This analysis can help developers and project

  • Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, Google tools for Machine Learning, Google Cloud Datalab - notebook in the cloud, Examination review
Tagged under: Artificial Intelligence, Code Quality Analysis, Collaboration Analysis, Data Preprocessing, Exploratory Data Analysis, GitHub Commit Data Analysis, Google Cloud Datalab, Machine Learning Applications, Time-based Analysis
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