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Presentation: Capstone Project on Coursera Data science Specialization
Presentation of works done to build a shiny app to predict most likely words following an input text
Part 1 Capstone Project words Prediction; sampling and Cleaning textsPublish Document
Remove Profanity words, use the textClean to replcace contraction, remove emails and http(s), replace @ to at, and & to and etc
Part 2 capstone project word prediction: dfm
add Kneser-Kney smoothing to the dataset. First we will find bi-gram probabilities and then add smoothing
Clean, Aggregate and gather data
Clean Aggregate and gather data
StormData Analysis by PrSaah
StormData Analysis
Magnitude of earthquake
MultiGraphics with plotly
Milestone Report
Some Exploratory analysis in text mining!
MappingCluster
leaflet package
Pratical Machine Leraning
perform barbell lifts
Machine Learning Case study
Using library(parallel) to perform a random Forest
Analyse of the mtcars datasets
Use anova to find the best linear model to fit a variable
bar plot view
read an zip file, map value, plot barplot, mutate, aggregate
Reproducible Research, personal activity monitoring device
personal activity monitoring device
Use grep and sub R-fonction coursera training
Use grep and sub R-fonction coursera training