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Applied Machine Learning With R
Introduction
Introduction (1:42)
Starting up- Machine learning with R (8:03)
What is Artificial Intelligence and machine learning (4:32)
Flow of machine learning (5:04)
Machine Learning vs Deep Learning (5:14)
R programming tool
R tool and installation (5:07)
R data structures (10:54)
H2O Package
Basics of Machine learning (4:33)
Supervised and unsupervised learning (10:54)
Case study- K means clustering (6:33)
Installation of H2O package (5:57)
Performing Regression with H2O (14:55)
Analysing the regression with H2O (11:09)
TensorFlow Package
Tensorflow package (5:14)
Performing Regression with TensorFlow (9:37)
Analysing the regression with TensorFlow (14:16)
Performance of model using TensorFlow (9:56)
First Machine Learning
Caret Package for Machine Learning (14:05)
Machine Learning with dataset (11:54)
Iris dataset Implementation (7:16)
Evaluation of Algorithms with models (8:54)
Selecting Best Model in Machine Learning (6:17)
Artificial Neural Networks
Creating and Visualizing Neural networks (5:32)
Demonstration of sample neural network (12:45)
Prediction Analysis of neural network (10:45)
Cross Validation Box plot (10:16)
Activity- Dataset to Neural Network (10:04)
Cluster Generation
Cluster Generation (6:30)
Cluster Generation Output Analysis (8:32)
Decision Trees
Decision Trees of Machine Learning (5:18)
Car Evaluation Problem Statement (12:52)
Plotting a Decision Tree (10:45)
Prediction Analysis- Decision Tree (6:35)
Text Mining
Introduction to Text Mining (9:38)
Text Mining with R (9:55)
Performing Regression with H2O
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