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CodeSignal

Gradient Descent: Building Optimization Algorithms from Scratch

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Overview

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Delve into the intricacies of optimization techniques with this immersive course that focuses on the implementation of various algorithms from scratch. Bypass high-level libraries to explore Stochastic Gradient Descent, Mini-Batch Gradient Descent, and advanced optimization methods such as Momentum, RMSProp, and Adam.

Syllabus

  • Lesson 1: Stochastic Gradient Descent: Theory and Implementation in Python
  • Lesson 2: Optimizing Machine Learning with Mini-Batch Gradient Descent
  • Lesson 3: Accelerating Convergence: Implementing Momentum in Gradient Descent Algorithms
  • Lesson 4: Understanding and Implementing RMSProp in Python
  • Lesson 5: Advanced Optimization: Understanding and Implementing ADAM

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