Day 2

Statistical and analytical methods dealing with data, Implementation of Recommenders using Apache Mahout and Transforming Data

Correlation b/w Nominal Variables
Contingency Table
What is Expected Value?
What is Mean?
How Expected Value is different from Mean
Experiment – Controlled Experiment, Uncontrolled Experiment
Degree of Freedom
Dependency b/w Nominal Variable & Continuous Variable
Linear Regression
Extrapolation and Interpolation
Univariate Analysis for Linear Regression
Building Model for Linear Regression
Patternof Data means?
Data Processing Operation
What is sampling?
Sampling Distribution
Stratified Sampling Technique
Disproportionate Sampling Technique
Balanced Allocation-part of Disproportionate Sampling
Systematic Sampling
Cluster Sampling
2 angels of Data Science-Statistical Learning, Machine Learning

Testing and Assessment, Production Deployment and More

Multi Variable analysis
Linear regration
Simple linear regration
Hypothesis testing
Speculation vs. claim(Query)
Sample
Step to test your hypothesis
performance measure
Generate null hypothesis
Alternative hypothesis
Testing the hypothesis
Threshold value
Hypothesis testing explanation by example
Null Hypothesis
Alternative Hypothesis
Probability
Histogram of mean value
Revisit CHI-SQUARE independence test
Correlation between Nominal Variable

Business Algorithms, Simple approaches to Prediction, Building model, Model deployment

Machine Learning
Importance of Algorithms
Supervised and Unsupervised Learning
Various Algorithms on Business
Simple approaches to Prediction
Predict Algorithms
Population data
sampling
Disproportionate Sampling
Steps in Model Building
Sample the data
What is K?
Training Data
Test Data
Validation data
Model Building
Find the accuracy
Rules
Iteration
Deploy the model
Linear regression

Getting started with Segmentation of Prediction and Analysis

Clustering
Cluster and Clustering with Example
Data Points, Grouping Data Points
Manual Profiling
Horizontal & Vertical Slicing
Clustering Algorithm
Criteria for take into Consideration before doing Clustering
Graphical Example
Clustering & Classification: Exclusive Clustering, Overlapping Clustering, Hierarchy Clustering
Simple Approaches to Prediction
Different types of Distances: 1.Manhattan, 2.Euclidean, 3.Consine Similarity
Clustering Algorithm in Mahout
Probabilistic Clustering
Pattern Learning
Nearest Neighbor Prediction
Nearest Neighbor Analysis