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Machine Learning with Python Machine Learning (ML) empowers systems to learn from data and improve their performance over time without explicit programming. Algorithms in ML identify patterns and make decisions, which is crucial for applications like predictiveanalytics and recommendation systems.
Both PyTorch and TensorFlow/Keras are still the go-to machine learning frameworks for a number of tasks, largely thanks to their ability to scale and be used for more resource-intensive tasks like deep learning; these two frameworks arent limited to just basic ML.
Underfitting happens when a model is too simplistic and fails to capture the underlying patterns in the data, leading to poor predictions. Common Applications of Machine Learning Machine Learning has numerous applications across industries. How Do I Choose the Right Machine Learning Model? For a regression problem (e.g.,
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