Subject Details
Dept     : ECE
Sem      : 5
Regul    : 2019
Faculty : JAGADESH.M
phone  : NIL
E-mail  : jagade.m.ece@snsct.org
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  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:
    Convolutional Networks,
    Recurrent Neural Networks,
    Bidirectional RNNs,
    Deep Recurrent Networks,
    Recursive Neural Networks

  • Assignment

    Assignment topic is 1.Explain the Reinforcement learning with real world examples 2.Explain Natural Language Processing (NLP) for text generation. and due date is .

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:
    Definition of learning systems-Goals and applications of machine learning,
    Types of Machine Learning,
    Machine Learning Process-,
    Terminology-Weight Space,
    The Curse of Dimensionality,
    Testing Machine Learning Algorithms

  • Youtube Video

    Dear Students the Youtube Video has been uploaded for the following topics:
    Fundamentals of Artificial Intelligence
    Introduction to AI
    Problem Solving as State Space Search
    Uniformed Search
    Introduction to Machine Learning
    Learning Decision Trees
    inear Regression
    Unsupervised Learning
    Reinforcement Learning

  • Question Bank

    Dear Students the Question Bank has been uploaded for the following topics:
    IAE,
    IAE

  • Resource Link

    Dear Students the Resource Link has been uploaded for the following topics:
    Artificial Intelligence and Machine Learning(AIML)

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:
    Regression: Linear Regression –Parametric Models,
    Multivariate Regression,
    Classification: Bayesian Decision Theory-parametric and non-parametric methods,
    Multivariate Classification - Logistic Regression,
    K-Nearest Neighbor classifier,
    Decision Tree based methods for classification and Regression- Ensemble methods.,
    Introduction-Clustering,
    K-means clustering,
    EM algorithm,
    Hierarchical Clustering,
    Principal Component ,
    Probabilistic PCA,
    The Brain and The Neuron,
    Neural Networks,
    Perceptron-Training the perceptron ,
    Perceptron Learning Algorithm,
    Multilayer Perceptron,
    Back Propagation -Dimensionality Reduction

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