Biological Neuron

Machine Learning
Machine learning deals with computational methods for acquiring new knowledge , new skills, and new ways to organize existing knowledge.
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases. Machine learning is concerned with the development of algorithms allowing the machine to learn via inductive inference based on observing data that represents incomplete information about statistical phenomenon and generalize it to rules and make predictions on missing attributes or future data. An important task of machine learning is classification, which is also referred to as pattern recognition, in which machines “learn” to automatically recognize complex patterns, to distinguish between exemplars based on their different patterns, and to make intelligent predictions on their class.
In machine learning, pattern recognition is the assignment of some sort of output value (or label) to a given input value (or instance), according to some specific algorithm. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes (for example, determine whether a given email is "spam" or "non-spam")

Definition: A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.

The Biological Neuron
The brain is a collection of about 10 billion interconnected neurons. Each neuron is a cell [right] that uses biochemical reactions to receive process and transmit information.
A neuron's dendritic tree is connected to a thousand neighbouring neurons. When one of those neurons fire, a positive or negative charge is received by one of the dendrites. The strengths of all the received...