Data Science Interview Question 10
Most Favorable Data Science Interview Questions and Answers for Beginners
Greetings.
I am a machine learning engineer based in India, possessing a sustained interest in machine learning since my undergraduate studies. I have completed Stanford University's machine learning course (Andrew Ng) via Coursera, and IBM's machine learning and deep learning curriculum. My current focus is on machine learning and data science projects, aiming to leverage my expertise for impactful, real-world problem-solving.
What are different types of Neural Networks?
Neural Networks are classified according to their architectures.
There are 7 types of neural networks that you need to know:
1. Perceptron
- A Perceptron is an Artificial Neuron. It is the simplest possible Neural Network. Neural Networks are the building blocks of Machine Learning.
2. Artificial Neural Networks
- Artificial Neural Network Tutorial provides basic and advanced concepts of ANNs.
3. Multilayer Perceptron
- Multilayer perceptron (MLP) is a supplement to the feed-forward neural networks. It consists of three types of layers—the input layer, output layer, and hidden layer.
4. Radial Networks
- The radial basis function network is one of the most widely used artificial neural networks for the Approximation of functions.
5. Convolutional Neural Networks
- Convolutional Neural Networks are a special type of feed-forward artificial neural network in which the connectivity pattern between its neuron is inspired by the visual cortex.
6. Recurrent Neural Networks
- A recurrent neural network (RNN) is a type of artificial neural network that uses sequential data or time series data.
7. Long-term Short-term Memory
- Long-Term Short-Term Memory (LSTM) networks are a type of recurrent neural network capable of learning order dependence in sequence prediction problems.
