Dive into the world of Loss Functions, a vital component in training machine learning and AI models. Loss functions measure the difference between predicted and actual results — guiding models to learn, improve, and perform better.
In this video, you’ll discover:
🔹 What Are Loss Functions? Understand how loss functions serve as a feedback mechanism, helping models optimize accuracy and reduce errors.
🔹 Types of Loss Functions:
Mean Squared Error (MSE) – Perfect for regression tasks
Cross-Entropy Loss – Essential for classification problems
Hinge Loss – Common in SVMs
Huber Loss – Great for handling outliers
🔹 Applications in AI: See how loss functions power advancements in neural networks, natural language processing (NLP), predictive analytics, and autonomous systems.
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