600+ Deep Learning Interview Questions (MAANG)

Partner: Udemy
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Description: This course is designed to help you crack deep learning interviews with confidence. It features over 600 carefully curated multiple-choice questions covering everything from data preprocessing and model training to supervised and unsupervised learning algorithms. Each question includes detailed explanations to deepen your understanding and help you avoid common pitfalls. Whether you're preparing for a job interview or looking to reinforce your knowledge, this course will give you the edge needed to succeed in any deep learning discussion.Topics Covered are :-1. Fundamentals of Neural Networks (Difficulty: Easy to Medium)Total MCQs: ~701.1. Introduction to Deep LearningDefinition of Deep Learning, Machine Learning, and AI.Differences and overlaps between ML and DL.Why Deep Learning is popular now (data, computational power, algorithms).Applications of Deep Learning (e.g., Computer Vision, NLP, Speech Recognition, Reinforcement Learning).MCQs: 101.2. Perceptron and Artificial Neural Networks (ANNs)Biological vs. Artificial Neurons.Perceptron: Architecture, working, limitations (linear separability).Multi-layer Perceptron (MLP): Structure (input, hidden, output layers), feedforward mechanism.Weights and Biases: Role, initialization (random, zeros, ones, Xavier, He).MCQs: 151.3. Activation FunctionsPurpose of activation functions (non-linearity, introducing decision boundaries).Types: Sigmoid, Tanh, ReLU, Leaky ReLU, PReLU, ELU, Softmax.Pros and cons of each, when to use them (e.g., Softmax for multi-class classification).Vanishing Gradient Problem: Explanation, h
Category: Development > Data Science > Deep Learning
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Price: 24.99
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Source: Impact
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