Neural Networks - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit V: Neural Networks
Activation functions also known as transfer function is used to map input nodes to output nodes in certain fashion. The activation function is the most important factor in a neural network which decided whether or not a neuron will be activated or not and transferred to the next layer.
Neural Networks - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit V: Neural Networks
The perceptron is a feed-forward network with one output neuron that learns a separating hyper-plane in a pattern space. The "n" linear Fx neurons feed forward to one threshold output Fy neuron.
Ensemble Techniques and Unsupervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit IV: Ensemble Techniques and Unsupervised Learning
In an unsupervised learning, the network adapts purely in response to its inputs. Such networks can learn to pick out structure in their input.
Ensemble Techniques and Unsupervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit IV: Ensemble Techniques and Unsupervised Learning
Gaussian Mixture Models is a "soft" clustering algorithm, where each point probabilistically "belongs" to all clusters. This is different than k-means where each point belongs to one cluster.
Ensemble Techniques and Unsupervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit IV: Ensemble Techniques and Unsupervised Learning
K-Nearest Neighbour is one of the only Machine Learning algorithms based totally on supervised learning approach. K-NN algorithm assumes the similarity between the brand new case/facts and available instances
Ensemble Techniques and Unsupervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit IV: Ensemble Techniques and Unsupervised Learning
Given a set of objects, place them in groups such that the objects in a group are similar (or related) to one another and different from (or unrelated to) the objects in other groups.
Ensemble Techniques and Unsupervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit IV: Ensemble Techniques and Unsupervised Learning
The idea of ensemble learning is to employ multiple learners and combine their predictions. If we have a committee of M models with uncorrelated errors, simply by averaging them the average error of a model can be reduced by a factor of M.
Ensemble Techniques and Unsupervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit IV: Ensemble Techniques and Unsupervised Learning
When designing a learning machine, we generally make some choices like parameters of machine, training data, representation, etc. This implies some sort of variance in performance.
Supervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit III: Supervised Learning
Learning is a phenomenon and process which has manifestations of various aspects. Learning process includes gaining of new symbolic knowledge and development of cognitive skills through instruction and practice.
Supervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit III: Supervised Learning
Random forest is a famous system learning set of rules that belongs to the supervised getting to know method. It may be used for both classification and regression issues in ML.
Supervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit III: Supervised Learning
A decision tree is a simple representation for classifying examples. Decision tree learning is one of the most successful techniques for supervised classification learning.
Supervised Learning - Artificial Intelligence and Machine Learning
Subject and UNIT: Artificial Intelligence and Machine Learning: Unit III: Supervised Learning
Support Vector Machines (SVMs)are a set of supervised learning methods which learn from the and used for dataset classification. SVM is a classifier derived from statistical learning theory by Chervonenkis.