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Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. Visualisation Tools Familiarity with tools such as Tableau, Power BI, and D3.js Students should learn how to train and evaluate models using large datasets.
Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and supportvectormachines.
Luckily, nothing too complicated is needed, as Tableau is user-friendly while matplotlib is the popular Python library for data visualization. Classification techniques like random forests, decision trees, and supportvectormachines are among the most widely used, enabling tasks such as categorizing data and building predictive models.
Machine Learning Supervised Learning includes algorithms like linear regression, decision trees, and supportvectormachines. Unsupervised Learning techniques such as clustering and dimensionality reduction to discover patterns in data.
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