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$25 USD / hour
Flag of MOROCCO
laayune, morocco
$25 USD / hour
It's currently 3:25 PM here
Joined August 2, 2013
4 Recommendations

Mohamed R.

@mohamedrdait

monthly-level-three.svg
verified.svg
preferred-freelancer-v2.svg 4.8 (104 reviews)
7.8
7.8
93%
93%
$25 USD / hour
Flag of MOROCCO
laayune, morocco
$25 USD / hour
96%
Jobs Completed
20%
On Budget
20%
On Time
23%
Repeat Hire Rate

Data analyst & Operational Research engineer

***********************I shall either find a way or make it one******************** I'm an Engineer in Operational Research , I've got many skills and expertise that will allow me to achieve perfectly all the projects and missions. I have advanced knowledge's in: Vba Excel Optimization Queuing Theory Linear Programming Economics modeling, Data Mining: Factor analysis, Principal Component Analysis, Regression (Simple, Multiple, logistic, hierarchical, Poisson), Anova, Clustering, Hierarchical Clustering... I master Lingo, Ampl, Spss, Stata, R, Eviews, I'll provide you perfect reporting using MsWord. Also I have a huge experience / Knowledge with creating software for scraping/extracting data from web site with VBNET ------------------------------------------------------------------------------------------------
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Portfolio

5516316
Linear Regression in R. Linear regression is used to predict the value of a continuous variable Y based on one or more input predictor variables X. The aim is to establish a mathematical formula between the the response variable (Y) and the predictor variables (Xs).
Linear Regression / GLM
5516287
Time series In R : Check if the time series is a Stationary Time Series ? 1) The mean value of time-series is constant over time, which implies, the trend component is nullified. 2) The variance does not increase over time. 3) Seasonality effect is minimal. See This means it is devoid of trend or seasonal patterns, which makes it looks like a random white noise irrespective of the observed time interval. extract the trend, seasonality and error Prediction using arma arima sarima neural network
Time Series
5516275
Clustering is the process of making a group of abstract objects into classes of similar objects. Points to Remember. A cluster of data objects can be treated as one group. While doing cluster analysis, we first partition the set of data into groups based on data similarity and then assign the labels to the groups. The k-means clustering algorithm is a data mining and machine learning tool used to cluster observations into groups of related observations without any prior knowledge of those relationships. The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems.
Clustring - Classification (Kmeans- Knn)
Clustering is the process of making a group of abstract objects into classes of similar objects. Points to Remember. A cluster of data objects can be treated as one group. While doing cluster analysis, we first partition the set of data into groups based on data similarity and then assign the labels to the groups. The k-means clustering algorithm is a data mining and machine learning tool used to cluster observations into groups of related observations without any prior knowledge of those relationships. The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems.
Clustring - Classification (Kmeans- Knn)
Clustering is the process of making a group of abstract objects into classes of similar objects. Points to Remember. A cluster of data objects can be treated as one group. While doing cluster analysis, we first partition the set of data into groups based on data similarity and then assign the labels to the groups. The k-means clustering algorithm is a data mining and machine learning tool used to cluster observations into groups of related observations without any prior knowledge of those relationships. The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems.
Clustring - Classification (Kmeans- Knn)
Clustering is the process of making a group of abstract objects into classes of similar objects. Points to Remember. A cluster of data objects can be treated as one group. While doing cluster analysis, we first partition the set of data into groups based on data similarity and then assign the labels to the groups. The k-means clustering algorithm is a data mining and machine learning tool used to cluster observations into groups of related observations without any prior knowledge of those relationships. The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems.
Clustring - Classification (Kmeans- Knn)
3054930
An example of my work with R a statistics problem : Regression Simulation histogram Confidence Interval
Statistics with R
An example of my work with R a statistics problem : Regression Simulation histogram Confidence Interval
Statistics with R
An example of my work with R a statistics problem : Regression Simulation histogram Confidence Interval
Statistics with R
2398944
ADD IN EXCEL
2398933
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
5516316
Linear Regression in R. Linear regression is used to predict the value of a continuous variable Y based on one or more input predictor variables X. The aim is to establish a mathematical formula between the the response variable (Y) and the predictor variables (Xs).
Linear Regression / GLM
5516287
Time series In R : Check if the time series is a Stationary Time Series ? 1) The mean value of time-series is constant over time, which implies, the trend component is nullified. 2) The variance does not increase over time. 3) Seasonality effect is minimal. See This means it is devoid of trend or seasonal patterns, which makes it looks like a random white noise irrespective of the observed time interval. extract the trend, seasonality and error Prediction using arma arima sarima neural network
Time Series
5516275
Clustering is the process of making a group of abstract objects into classes of similar objects. Points to Remember. A cluster of data objects can be treated as one group. While doing cluster analysis, we first partition the set of data into groups based on data similarity and then assign the labels to the groups. The k-means clustering algorithm is a data mining and machine learning tool used to cluster observations into groups of related observations without any prior knowledge of those relationships. The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems.
Clustring - Classification (Kmeans- Knn)
Clustering is the process of making a group of abstract objects into classes of similar objects. Points to Remember. A cluster of data objects can be treated as one group. While doing cluster analysis, we first partition the set of data into groups based on data similarity and then assign the labels to the groups. The k-means clustering algorithm is a data mining and machine learning tool used to cluster observations into groups of related observations without any prior knowledge of those relationships. The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems.
Clustring - Classification (Kmeans- Knn)
Clustering is the process of making a group of abstract objects into classes of similar objects. Points to Remember. A cluster of data objects can be treated as one group. While doing cluster analysis, we first partition the set of data into groups based on data similarity and then assign the labels to the groups. The k-means clustering algorithm is a data mining and machine learning tool used to cluster observations into groups of related observations without any prior knowledge of those relationships. The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems.
Clustring - Classification (Kmeans- Knn)
Clustering is the process of making a group of abstract objects into classes of similar objects. Points to Remember. A cluster of data objects can be treated as one group. While doing cluster analysis, we first partition the set of data into groups based on data similarity and then assign the labels to the groups. The k-means clustering algorithm is a data mining and machine learning tool used to cluster observations into groups of related observations without any prior knowledge of those relationships. The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems.
Clustring - Classification (Kmeans- Knn)
3054930
An example of my work with R a statistics problem : Regression Simulation histogram Confidence Interval
Statistics with R
An example of my work with R a statistics problem : Regression Simulation histogram Confidence Interval
Statistics with R
An example of my work with R a statistics problem : Regression Simulation histogram Confidence Interval
Statistics with R
2398944
ADD IN EXCEL
2398933
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R
I have developed many R script Markov chain Simulation Regression
Programming With R

Reviews

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Showing 1 - 5 out of 50+ reviews
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5.0
£200.00 GBP
R optim -- 2
Takes time but, does quality work.
Excel
Web Scraping
Statistics
R Programming Language
+1 more
N
Flag of Pac C.
@Nitmah007
•
1 year ago
5.0
€350.00 EUR
Project for Mohamed R. -- 3
I appreciate working with Mohamed. I've worked with him a couple of times now. It may take a bit longer than anticipated, but his work is always worth the wait. He's very good, detail-oriented, and is far more capable than he acknowledges. Would highly recommend him to anyone of any discipline.
Excel
Web Scraping
Statistics
R Programming Language
+1 more
H
Flag of Heather H.
@Hhuf
•
1 year ago
5.0
$70.00 USD
Project for Mohamed R.
10/10 he did a great job
Excel
Web Scraping
Statistics
R Programming Language
+1 more
S
Flag of Sara A.
@Sumou96
•
1 year ago
5.0
$430.00 USD
Project 35069874 has been deleted
The quality of the work is amazing and he always delivers on this time.
D
Closed User
@dmariama1999
•
2 years ago
5.0
$150.00 USD
Project for Mohamed R. -- 6
Dude's good.
Excel
Web Scraping
Statistics
R Programming Language
+1 more
User Avatar
Flag of David C.
@dcvengros
•
2 years ago

Education

Ingénieur d\'etat en Recherche Operationnelle et aide à la décision

Morocco 2012 - 2015
(3 years)

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Verifications

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Certifications

preferredfreelancer-1.png Preferred Freelancer Program SLA 1 89%
us_eng_1.png US English 1 83%

Top Skills

R Programming Language 99
Statistics 74
Statistical Analysis 71
Excel 55
Web Scraping 48

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