Recommendations_Personas

Recommendations_Personas

Recommendation

Naive Bayes Classifier for Discrete Predictors

K-Means Clustering The process by which objects are classified into a number of groups so that they are as much dissimilar as possible from one group to another group, but as much similar as possible within each group.

ARIMA models provide another approach to time series forecasting. Exponential smoothing and ARIMA models are the two most widely-used approaches to time series forecasting, and provide complementary approaches to the problem. While exponential smoothing models were based on a description of trend and seasonality in the data, ARIMA models aim to describe the autocorrelations in the data. Before we introduce ARIMA models, we need to first discuss the concept of stationarity and the technique of differencing time series. -->Stationarity and differencing --> Backshift notation --> Autoregressive models --> Moving average models --> Non-seasonal ARIMA models --> Estimation and order selection --> ARIMA modelling in R --> Forecasting --> Seasonal ARIMA models --> ARIMA vs ETS

sales per market segment-Students' Union Bar ('Mooch')

Univariate Analysis/ Descriptive Analysis

sda

Practice session

Intro to "R"