Description

This is what you will be learning in the course:

• Introduction to ANN (Artificial Neural Networks)
  • Architecture of Neural Networks
  • Perceptrons
  • Weights and Bias
  • Hidden Layers
  • Forward and Backward Propagation
  • Optimisers
  • Loss Functions
  • Quiz
• Deep Learning with sklearn
  • MLP Regressor
  • MLP Classifier
  • Kernel parameters and tuning
  • Case Study – Regression
  • Case Study – Classification
  • Quiz
• Introduction to Tensor Flow 2.0 & Keras
  • Quiz
• Convolutional Neural Networks (CNN)
  • Case Study – Hand written digit recognition
  • Quiz
• Recurrent Neural Networks (RNN)
  • Case Study – 1
  • Quiz
• Long-Short Term Memory (LSTM)
  • Case Study – 1
  • Quiz
• Introduction to OpenCV package
  • Reading and writing images
  • Image Processing Techniques
  • Object Detection
  • Face Recognition
• Master Quiz for Certification
• Capstone Project for Certification