Machine Learning is an Artificial Intelligence that includes a number of technologies. Deep Learning (for instance Convolutional Neural Networks and Recurrent Neural Networks) and Reinforcement Learning are among the technologies often mentioned in connection to AI and Machine Learning.
Convolutional Neural Networks (CNNs) are most often used in the field of image analysis, in order to make the computer automatically learn the features needed to interpret images. As soon as a neural network contains more than one hidden layer, the concept Deep Learning is used. CNNs for images often have several hidden convolutional layers.
Recurrent Neural Networks (RNNs) are used to model interdependencies between terms in a series of data, and it is useful for, for instance, text interpretation. There are several types of RNNs (for instance Long Short-Term Memory, LSTM), intended for specific purposes.
Reinforcement Learning is used for training a computer to carry out a specific task. The computer is trained by completing the same task again and again. For each repetition, feedback is given, and this reward is used to update the algorithm. A combination of CNNs with Reinforcement Learning is called Deep Reinforcement Learning and is used to make the computer be able to use a camera as a sensor when it is carrying out its task (cf. Robotics).