This post provides an overview of Deep Learning fundamentals, including its applications in various industries, the architecture of Neural Networks, and optimization algorithms like Stochastic Gradient Descent.
Table of contents
Table of ContentsPrerequisitesChapter 1: What is Deep Learning?Chapter 2: Foundations of Neural NetworksChapter 3: How to Train Neural NetworksChapter 4: Optimization Algorithms in AIChapter 5: Regularization and GeneralizationChapter 6: Vanishing Gradient ProblemChapter 7: Combatting Exploding GradientsChapter 8: Sequence Modeling with RNNs & LSTMsChapter 9: Deep Learning Interview PreparationAbout the AuthorConnect with Me and LunarTech14 Impressions