Machine Learning (Unit 1 to 5) Detailed Module
Description
Length: 108 Pages
Diagrams + Based on Previous Year Questions
Topics Include in Machine Learning (Unit 1 to 5) Detailed Module:
Unit-1
Introduction to machine learning, Applications, Classification; Supervised Learning: Linear Regression: Cost function, Gradient descent; Logistic Regression, Nearest-Neighbors, Gaussian function.
Unit-2
Overfitting and Underfitting, Regularization, Bias and Variance, Decision Trees, Naı̈ ve Bayes, Support Vector Machines, Kernel Methods.
Unit-3
Unsupervised Learning: Clustering: K-means, Dimensionality Reduction: PCA, Matrix Factorization and Matrix Completion, Ranking, Recommender System.
Unit-4
Introduction to Neural Network, Perceptron, Feed forward, Back Propagation, Recurrent Neural Network. Introduction to Python machine learning libraries: Keras, Tensorflow and Theano.
Unit-5
Evaluating Machine Learning algorithms and Model Selection, Ensemble Methods: Boosting, Bagging, Random Forests, Deep learning Semi-supervised Learning, Reinforcement Learning.
Note : If you are placing an order for a hardcopy module, it will be delivered to the address you provided to us.
Premium Modules
Explore Machine Learning Modules Repository
Explore Medicaps Modules: Short, Detailed, and Expertly Crafted for Easy Learning - Available in Hard Copy and Soft Copy Formats.
