Tabla de Contenidos: “…Unconstrained Optimization -- [Advanced Section] Reducing a Constrained Problem to an Unconstrained Optimization Problem -- Absolute and Local Minima of a Function -- Optimization Algorithms -- Line Search and Trust Region -- Steepest Descent -- The Gradient Descent Algorithm -- Choosing the Right Learning Rate -- Variations of GD -- Mini-Batch GD -- Stochastic GD -- How to Choose the Right Mini-Batch Size -- [Advanced Section] SGD and Fractals -- Exercises -- Conclusion -- Chapter 2: Hands-on with a Single Neuron -- A Short Overview of a Neuron's Structure -- A Short Introduction to Matrix Notation -- An Overview of the Most Common Activation Functions -- Identity Function -- Sigmoid Function -- Tanh (Hyperbolic Tangent) Activation Function -- ReLU (Rectified Linear Unit) Activation Function -- Leaky ReLU -- The Swish Activation Function -- Other Activation Functions -- How to Implement a Neuron in Keras -- Python Implementation Tips: Loops and NumPy -- Linear Regression with a Single Neuron -- The Dataset for the Real-World Example -- Dataset Splitting -- Linear Regression Model -- Keras Implementation -- The Model's Learning Phase -- Model's Performance Evaluation on Unseen Data -- Logistic Regression with a Single Neuron -- The Dataset for the Classification Problem -- Dataset Splitting -- The Logistic Regression Model -- Keras Implementation -- The Model's Learning Phase -- The Model's Performance Evaluation…”

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