Requirements
- Python language
Description
Following topics are covered as part of the course
- Explore building blocks of neural networks
- Data representation, Tensor, Back propagation
- Keras
- Dataset, Applying Keras to cases studies, over fitting / under fitting
- Artificial Neural Networks (ANN)
- Activation functions
- Loss functions
- Gradient Descent
- Optimizer
- Image Processing
- Convnets (CNN), hands-on with CNN
- Text and Sequences
- Text data, Language Processing
- Recurrent Neural Network (RNN)
- LSTM
- Bidirectional RNN
- Gradients and Back Propagation – Mathematics
- Gradient Descent
- Mathematics
- Image Processing / CV – Advanced
- Image Data Generator
- Image Data Generator – Data Augmentation
- Pre-trained network
- Functional API
- Intro to Functional API
- Multi Input Multi Output Model
The videos are concepts and hands-on implementation of topics
Who this course is for:
- Beginner Python developers, Data Science students, Students who have some exposure to Machine Learning
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