Genetic Algorithm, Neural Network, Deep Learning, Machine Learning Similarities and Applications?
Here's a quick dictionary:


Machine learning is a very broad subject encompassing mainly algorithms whose goal is classifying inputs to different categories. For example, an automated post system has to be able to read letters and digits. After the characters are segmented into individual characters using techniques from computational geometry, a computerized algorithm converts the images into digits and letters. Such an algorithm is trained using classified examples, that is, many examples of each digit and letter which are shown to the algorithm.
Neural networks are a machine learning algorithm loosely based on the works of the nervous system, including the brain. They are examples of the paradigm of deep learning.
Genetic algorithms are used to solve optimization problems (i.e. find the most stable structure supporting a bridge). They are loosely based on evolutionary biology.