Weight is the parameter within a neural network that transforms input data within the network's hidden layers. As an input enters the node, it gets multiplied by a weight value and the resulting output is either observed, or passed to the next layer in the neural network.| DeepAI
Backpropagation, short for backward propagation of errors, is a widely used method for calculating derivatives inside deep feedforward neural networks.| DeepAI
Probability Theory describes probabilities in terms of a probability space, typically assigning a value between 0 and 1, known as the probability measure, and a set of outcomes known as the sample space.| DeepAI
An artificial neural network learning algorithm, or neural network, or just neural net, is a computational learning system that uses a network of functions to understand and translate a data input of one form into a desired output, usually in another form.| DeepAI
In simple words, Natural Language Processing is a field which aims to make computer systems understand human speech. NLP is comprised of techniques to process, structure, categorize raw text and extract information.| DeepAI
Deep learning is a machine learning method using multiple layers of nonlinear processing units to extract features from data. Find out more on DeepAI.| DeepAI
A decision tree is a supervised learning technique that has a pre-defined target variable and is most often used in classification problems.| DeepAI
The application of rapid data processing, machine learning, predictive analysis, and automation to simulate intelligent behavior and problem solving capabilities with machines and software.| DeepAI
Pattern recognition is a technique to classify input data into classes or objects by recognizing patterns or feature similarities.| DeepAI
Bayesian inference refers to the application of Bayes’ Theorem in determining the updated probability of a hypothesis given new information.| DeepAI
