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Course Curriculum

  • Deep Learning Foundations (Beginner)
  • Deep Learning Intermediate
    • Optimization Techniques
      •  Gradient Descent Variants
      • Learning Rate Tuning
      • Optimizers (Adam, SGD, RMSprop)
      •  Batch Normalization
      • Dropout Regularization
    • Convolutional Neural Networks (CNNs)
    • Computer Vision Projects
    • Recurrent Neural Networks (RNNs)
    •  Natural Language Processing (NLP)
    •  Model Improvement
  • Advanced Deep Learning
  • Industry & Real-World Projects

Optimization Techniques

Home » Deep Learning Intermediate > Optimization Techniques

Lessons in this Module

  •  Gradient Descent Variants →
  • Learning Rate Tuning →
  • Optimizers (Adam, SGD, RMSprop) →
  •  Batch Normalization →
  • Dropout Regularization →
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