Machine Learning Course
Designed for those new to the field, this course covers essential concepts like algorithms, data preprocessing, and model evaluation.Learn to create predictive models and uncover patterns in data using popular machine learning libraries.
5 Weeks
38H
4.5
COURSE OUTLINE :
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What is Machine Learning (ML)?Machine Learning (ML) is a subset of Artificial Intelligence (AI) that focuses on developing algorithms and statistical models that enable computers to learn and make decisions from data without being explicitly programmed.
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What are the main types of Machine Learning?
Supervised Learning: The model is trained on labeled data.
Unsupervised Learning: The model is trained on unlabeled data.
Reinforcement Learning: The model learns by interacting with an environment to maximize cumulative reward.
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What is overfitting in ML?Overfitting occurs when a model learns the training data too well, capturing noise and details that do not generalize to new, unseen data, resulting in poor predictive performance.
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What is underfitting in ML?Underfitting occurs when a model is too simple to capture the underlying structure of the data, resulting in poor performance on both the training data and new, unseen data.
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What is deep learning?Deep learning is a subset of ML that uses neural networks with many layers (deep neural networks) to model complex patterns in large datasets. It is particularly effective in tasks such as image and speech recognition.
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What is gradient descent in ML?Gradient descent is an optimization algorithm used to minimize the loss function in ML models. It iteratively adjusts the model's parameters by moving in the direction of the steepest descent of the loss function.
