Developing a solid grasp of machine learning algorithms is fundamental. This includes supervised and unsupervised learning, reinforcement learning, and deep learning techniques. As a machine learning engineer, you need to understand how and when to apply algorithms such as linear regression, decision trees, support vector machines, neural networks, and clustering methods.
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