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Get ready to dive into the world of Machine Learning (ML) by using Python! Beginning with a gentle introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning, linear & non-linear regression, simple regression and more.
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We'll then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression and also learn about the importance and different types of clustering such as k-means, hierarchical clustering, and DBSCAN.
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A big emphasis will be placed on hands-on learning working with Python libraries like SciPy and scikit-learn. Finnlay apply the skills by building, evaluating and comparing several Machine Learning models using different algorithms.
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