Explain the following terms: 1. Hyper Parameters 2. Gradient Descent 3. Activation Function
[3 marks]Explain the application of Deep Learning.
[7 marks]Differentiate between Deep Learning and Machine Learning.
[7 marks]What is Neural Networks and Shallow Neural Networks?
[7 marks]How to Read and save images using OpenCV?
[7 marks]What is CNN? Discuss advantages and challenges of CNN.
Explain in brief LSTM.
[7 marks]What is RNN? Discuss types of RNN?
[7 marks]Explain Terms : Theano, PlaidML and Keras.
[7 marks]What is GAN? How it is differ from other machine learning model?
[7 marks]Explain search algorithm for sequential decision process.
[7 marks]Explain Q-Learning Algorithm with example.
[7 marks]Explain in brief Bellman’s Equation for Decision process.
[7 marks]Explain step-by-step DQNS algorithm.
[7 marks]What is NLP? Explain elements of NLP. How does NLP work?
[7 marks]Explain Corpus, Vocabulary, bag of words with example.
[7 marks]Explain different methods for calculating Text Similarity.
[7 marks]