JNTUK B.Tech 3-2 R20 Machine Learning Material for all 5 units are now available. The materials provided here is prepared in an easy for read and understating.
Here you can get all JNTUK R20 Materials for your exam preparation. For all latest updates on materials please visit us regularly
Unit I:
Introduction- Artificial Intelligence, Machine Learning, Deep learning, Types of Machine Learning
Systems, Main Challenges of Machine Learning.
UNIT-I Chapter-I Download Here
Statistical Learning: Introduction, Supervised and Unsupervised Learning, Training and Test Loss,
Tradeoffs in Statistical Learning, Estimating Risk Statistics, Sampling distribution of an estimator,
Empirical Risk Minimization
Unit II
Supervised Learning(Regression/Classification):Basic Methods: Distance based Methods, Nearest
Neighbours, Decision Trees, Naive Bayes
Linear Models: Linear Regression, Logistic Regression, Generalized Linear Models, Support Vector Machines
Binary Classification: Multi class/Structured outputs, MNIST, Ranking.
Unit III
Ensemble Learning and Random Forests: Introduction, Voting Classifiers, Bagging and Pasting,
Random Forests, Boosting, Stacking.
Support Vector Machine: Linear SVM Classification, Nonlinear SVM Classification SVM Regression,
Naïve Bayes Classifiers.
Unit IV
Unsupervised Learning Techniques: Clustering, K-Means, Limits of K-Means, Using Clustering for
Image Segmentation, Using Clustering for Preprocessing, Using Clustering for Semi-Supervised
Learning, DBSCAN, Gaussian Mixtures.
Dimensionality Reduction: The Curse of Dimensionality, Main Approaches for Dimensionality
Reduction, PCA, Using Scikit-Learn, Randomized PCA, Kernel PCA
Unit V
Neural Networks and Deep Learning: Introduction to Artificial Neural Networks with Keras,
Implementing MLPs with Keras, Installing TensorFlow 2, Loading and Preprocessing Data with
TensorFlow.
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