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
- Convolutional Neural Networks (CNN)
- Case Study – Hand written digit recognition
- Quiz
- Recurrent Neural Networks (RNN)
- Long-Short Term Memory (LSTM)
- Introduction to OpenCV package
- Reading and writing images
- Image Processing Techniques
- Object Detection
- Face Recognition
- Master Quiz for Certification
- Capstone Project for Certification
