## Recently Published

##### ASTHMA MANAGEMENT

Characteristics of asthma good management

##### Customers at an Auto_Insurance Company

Build multiple linear regression and binary logistic regression models on the training data to predict the probability that a person will crash their car and also the amount of money it will cost if the person does crash their car.

##### Plot

Content correlation plots of crime dataset

##### Time Series Forecasting

Looking for the best forecast model

##### Time Series Forecasting

Looking for the best model to forecast.
Using Naive method, Arima and ETS

##### Time Series Forecasting

Forecast time series and evaluate the accuracy

##### Homework KJ31 and KJ32

Preprocessing Missing Data

##### Evaluation of Recommender Systems

Evaluate Users Ratings and Recommender Models

##### Evaluation of Recommenders Systems

Ratings Evaluations and Models Evaluations

##### Document

Recommender Sysytem
Evaluation and Comparison

##### Unsupervised Learning

Applying K-mean Clustering and SVM

##### Computation of Taylor Series

Inverse function
Exponential
Logarithm

##### Taylor Series

Integration of Taylor Series

##### Logistic Regression

Interpret of slope and intercept
R-square and R-square adjusted
logistic model

##### Connection Between DataBases

MySQL ----> R ----> MongoDB

##### Multiple Linear Model

Backward Elimination with p-value approach

##### Linear Model

Murder prediction

##### DATA607 Project 4 Part 2

Document Classifiers

##### Project4

Spam and Ham training and test

##### Recommendations

User Base Recommendations
Items Base Recommendations

##### Numerical Variables

Confidence Interval
Minimun required Sample
Difference of average, Hypothesis
ANOVA

##### Numerical Variables

Hypothesis
Inferences
Confidence interval

##### scraping the web with Apis

Using New York Time APIs

##### Project 3

Most demand data sciences skills.

##### Central Limit Theorem and Moment Generating Function

Exercise 11 p.343

##### Inference for Categorical Data

Exercises
6..48 p.248
6.10 p.216
6.16 p.216
6.22 p.226
6.34 p.239
6.50 p.248

##### Assignment 8

Exercise 11 p303
Exercise 14 p304
Exercise 1 320-321

##### Transfer web table to R

HTML
JSON
XML

##### Table in json

Json table in html script

##### HTML Table

Table and attributes in html

##### Project 2B

Malaria (incompleted)

##### Uniform Distribution

Probability Distribution in an Area

##### Tidying and Transforming Dataset

Using gather() and spread() from Tidyr and dplyr

##### project1Alain

UUsing Regular Expression in R

##### Linear Transformation

Injective, Surjective, Invertible Transformation

##### Using Regular Expression

Using stringr library to extract and clean strings

##### Linear Algebra

Eigenvalues and eigeinvectors

##### Data605 Discussion Board 2

System lineary independent

##### The Mushroom Dataset

Assignment1 DATA607
Renaming and sub setting the mushroom dataset

##### Cybersecurity Breaches in Health Care

Study of Cyber Security Breaches in Health Care
Number of People Affected by Month and Year
Number of People Affected by State and Region

##### Cybersecurity Breaches dataframe

Using ggplot2

##### Summer Bridge R SummAssignment Week 2

Function: summary, data.frame, subset, median, mean, renames
colnames, rownames

##### Summer Bridge Assignment R11

Loop
Function
sequence

##### Summer Bridge R Assignment 1

Using for loop
Function seq()
Quadratic Function

##### Summer Bridge Assignment R1

For loop for to compute factorial 12
using seq function
Solutions of a quadratic equation