JNTUK Deep Learning Important Questions
UNIT 1:
- Overview of AI, ML, and DL
(Example question: Comparison/Difference Between AI, ML, and DL? - frequently asked question) - Branches of Machine Learning
(Example question: Explain the Four Branches of Machine Learning - Important Question) - Underfitting and Overfitting
(Example question: Differences between Underfitting and Overfitting or What is Underfitting or Overfitting?) - Decision Trees and Kernel Methods
(Example question: Brief Introduction about Decision Trees or Explain about Kernel Methods) - Gradient Boosting Models & Machine Learning Models
(Learn basic information, as it’s a backup option. In some cases, questions will be asked about these.)
UNIT 2:
- Artificial Neural Networks (ANN)
(Example question: Give a Brief Introduction about ANN - very important topic in exams and real-time) - Back Propagation Networks
(Example question: Describe/Explain Back Propagation Networks in Detail - very important) - Deep Networks
(Example question: Procedure to Train Deep Networks - In some cases, they will ask indirectly) - Additional Sub-topics
(In Unit 2, most questions are asked indirectly, so try to learn their sub-topics, as it can help you. For this reason, try to learn about machine language or softmax type questions.)
UNIT 3:
- Binary and Multi-Class Classification
(Frequently asked in exams, and sometimes indirectly) - Setting Up a Deep Learning Workstation
(Example question: Explain/How to Set Up a Deep Learning Workstation in Detail) - Keras and its Features
(Example question: Explain about Keras and its Features - sometimes asked indirectly) - Additional Topic
(If you have enough time, learn about the "Anatomy of a Neural Network")
UNIT 4: RNN vs CNN and PyTorch
- RNN vs CNN
(Basic Information, helpful for exams - Sometimes asked as "Differences/Comparison Between RNN and CNN") - PyTorch (Features, Operations)
(very important - Sometimes asked differently) - Schematic Diagram of RNN
(Often asked in exams as "Explain or Draw the Schematic Diagram of RNN") - Additional Topic
(If you have time, learn about "Convolutional Layers")
UNIT 5: Advanced Topics
- AutoEncoders
(Example question: Explain/Give a Brief Introduction about Auto Encoders - important topic from Unit - 5 second part) - Boltzmann Machines
(Example question: Explain the Implementation of Boltzmann Machines - very important question) - Generative Adversarial Networks
(Example question: Explain in Detail about Generative Adversarial Networks - important question) - Deep Reinforced Learning
(very important) - Additional Topic
(If you have time, learn about "Natural Language Processing")