9.3 Functions in Machine Learning | Calculus & Optimization скачать в хорошем качестве

9.3 Functions in Machine Learning | Calculus & Optimization

In this video, we explore Functions in Calculus & Optimization for Machine Learning—why they matter, how ML models use functions, different types of functions, and how activation functions power deep learning. We also use a House Price Prediction analogy to clearly understand how functions relate to ML models and memory usage. Topics Covered: 1. Motivation to Learn Functions in Calculus & Optimization for ML 2. Introduction to Functions in Calculus and Machine Learning 3. House Price Prediction Analogy: • How a function maps inputs to outputs • How ML models are saved • How model size / memory is calculated 4. Types of Functions: One-to-one, Many-to-one, Onto (surjective), Into (non-surjective) 5. Plotting Basic Functions with intuitive examples 6. Plotting ML Activation Functions: Sigmoid, Tanh, ReLU, Leaky ReLU Helpful For: 1. Cracking AI / ML / Data Science interview rounds at top tech companies 2. Building a deeper understanding of core AI, ML concepts 3. Preparing for GATE (DA / CS / Other streams) and other related competitive exams Our Playlist: Calculus & Optimizations for ML - Hindi:    • 9. Calculus & Optimization for ML | Comple...   #MachineLearning #CalculusForML #FunctionsInML #ActivationFunctions #DeepLearning #MathForML #OptimizationInML #Sigmoid #ReLU #Tanh #DataScience #NeuralNetworks #decodeaiml Tags functions in machine learning, calculus for machine learning, optimization for machine learning, function types, one to one many to one onto into, activation functions ml, sigmoid tanh relu leaky relu, plotting functions, house price prediction analogy, model size memory ml, save model pickle size, ml basics, math for ml, deep learning functions, neural network activations