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Machine Learning Introduction session 1.
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- 2. Difference between AI,ML, DL and NN Artificial intelligenc e Machine learning Deep learning is the overarching field that includes all aspects of making machines intelligent. is a subset of AI focused on algorithms that learn from data. is a specialized subset of machine learning involving deep neural networks.
- 3. DL Vs NN DeepLearning can recognize data patterns like complex pictures, text, and sounds to produce accurate insights and predictions. Neural Networks the underlying technology in deep learning. It consists of interconnected nodes or neurons in a layered structure.
- 16. Overfitting vs Underfitting Overfitting ●Fitting the data too well ○ Features are noisy / uncorrelated to concept ○ Modeling process very sensitive (powerful) ○ Too much search Underfitting ● Learning too little of the true concept ○ Features don’t capture concept ○ Too much bias in model ○ Too little search to fit model -0.1 0.1 0.3 0.5 0.7 0.9 -0.2 -5.55111512312578E-17 0.2 0.4 0.6 0.8 1
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- 21. What Is GradientDescent in Machine Learning? Gradient Descent is an optimization algorithm for finding a local minimum of a differentiable function. Gradient descent in machine learning is simply used to find the values of a function's parameters (coefficients) that minimize a cost function as far as possible.
- 24. What Is LearningRate in Machine Learning? In machine learning and statistics, the learning rate is a tuning parameter in an optimization algorithm that determines the step size at each iteration while moving toward a minimum of a loss function.
- 25. In order forGradient Descent to work, we must set the learning rate to an appropriate value. This parameter determines how fast or slow we will move towards the optimal weights.
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