Mohamed D. Profile | Freelancer

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Artificial Intelligence

Electrical Engineering

Machine Learning (ML)

Matlab and Mathematica

5,0

(13 Bewertungen)

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$20 USD / Stunde

Flagge von YEMEN

amanat al-alsamah,

$20 USD / Stunde

Es ist derzeit 3:21 PM hier

Beigetreten am März 22, 2016

1 Recommendation

Mohamed D.

@MohamedDoba

5,0

(13 Bewertungen)

4,2

4,2

85%

85%

$20 USD / Stunde

Flagge von YEMEN

amanat al-alsamah,

$20 USD / Stunde

100 %

Abgeschlossene Arbeiten

100 %

Budgetgerecht

100 %

Pünktlich

40 %

Wiedereinstellungsrate

Data Scientist and Mechatronics Engineer

I have studied, practiced and worked with Machine learning models, control system, embedded system and mechatronics and robotics system. I have done projects in : -Machine Learning, data analysis. -Robotics, control system. -PLC industrial control system. -PIC and arduino micrecontroller system. -Raspberry bi embedded system. -Python programming. -C and C++ programming projects. -Close loop motor power driver. -Discrete simulation and modeling. -Matlab control system. -Labview image processing system. Programming Languages: C, C++, Python,R, java, C#. Software: Matlab, Labview, Rstudio, Arduino, Pycharm, Processing, Solidworks, Visual studio, Arena, Multisim, Proteus ISIS and PCB Designer ISIS.

Alle Machine Learning Experts in Yemen ansehen

Kontaktieren Sie Mohamed D. bezüglich Ihres Jobs

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Portfolio

Unsupervised machine learning using Partitioning algorithms are clustering approaches that split the data sets, containing n observations, into a set of k groups (i.e. clusters). The algorithms require the analyst to specify the number of clusters to be generated.
This chapter describes the most commonly used partitioning algorithms including:

Cluster Analysis in R Programming Language

Roc curve shown the true positive rate versus false positive rate for different classifiers, namely:
1- "SVM-Linear",
2- "SVM-RBF",
3- "Boosting",
4- "Bagging",
5- "Random Forest",
6- "Neural network",
7- "Logit",
8- "MDA"

ROC curve for different Binary classifiers

The project was about to show the correlation between multivariate data-set.

Data Analysis and Data Visualization using Python

PCB for EMG signal acquisition

PCB

PCB for EMG signal acquisition

PCB

PCB for EMG signal acquisition

PCB

PCB for EMG signal acquisition

PCB

Web scraping

Web scraping

Supermarket Cashiers Simulation Using ARENA

In a certain supermarket, they don’t know the maximum arrival rate of
customer the supermarket cashiers can serve without long waiting time
that would enforce the customer to leave.
The supermarket have six cashier but they don’t know if it enough or
not, they want to know the maximum arrival rate to compare it to their
actual data and decide to buy now cashier or not.

1.2- The goals and objectives:
Determine the maximum arrival rate of the customers if the super market
have six cashier.

1.3- Given information:
1- Number of cashier = 6 unit.
2- Maximum waiting time = 15 minutes.
3- Maximum queue length = 9 customers.

Discrete modeling and simulation using Arena

Unsupervised machine learning using Partitioning algorithms are clustering approaches that split the data sets, containing n observations, into a set of k groups (i.e. clusters). The algorithms require the analyst to specify the number of clusters to be generated.
This chapter describes the most commonly used partitioning algorithms including:

Cluster Analysis in R Programming Language

Roc curve shown the true positive rate versus false positive rate for different classifiers, namely:
1- "SVM-Linear",
2- "SVM-RBF",
3- "Boosting",
4- "Bagging",
5- "Random Forest",
6- "Neural network",
7- "Logit",
8- "MDA"

ROC curve for different Binary classifiers

The project was about to show the correlation between multivariate data-set.

Data Analysis and Data Visualization using Python

PCB for EMG signal acquisition

PCB

PCB for EMG signal acquisition

PCB

PCB for EMG signal acquisition

PCB

PCB for EMG signal acquisition

PCB

Web scraping

Web scraping

Supermarket Cashiers Simulation Using ARENA

In a certain supermarket, they don’t know the maximum arrival rate of
customer the supermarket cashiers can serve without long waiting time
that would enforce the customer to leave.
The supermarket have six cashier but they don’t know if it enough or
not, they want to know the maximum arrival rate to compare it to their
actual data and decide to buy now cashier or not.

1.2- The goals and objectives:
Determine the maximum arrival rate of the customers if the super market
have six cashier.

1.3- Given information:
1- Number of cashier = 6 unit.
2- Maximum waiting time = 15 minutes.
3- Maximum queue length = 9 customers.

Discrete modeling and simulation using Arena

Bewertungen

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5,0

£54,00 GBP

MATLAB, SIMULINK, Closed loop controller, Mechanical Engineering

It was great to work with Mohamed. He delivered the project on time and had a good understanding of the project. Highly recommended!

Matlab and Mathematica

Mechanical Engineering

Electrical Engineering

Sohaib K.

@sohaibkm

•

vor 5 Jahren

5,0

$180,00 USD

Reproduce the results of a paper

he did a great work always ready to respond and help i would like to work with him every time 100% recommended

Machine Learning (ML)

R Programming Language

Neural Networks

Sumbal S.

@sumbali

•

vor 6 Jahren

4,8

$60,00 USD

Do some data manipulation in Python

Good communication, very responsive to any requests.

Machine Learning (ML)

F

Ye C.

@freerider000

•

vor 6 Jahren

5,0

$120,00 USD

Predictive modeling

Fast turnaround, good work, very responsive to questions.

Data Processing

Machine Learning (ML)

F

Ye C.

@freerider000

•

vor 6 Jahren

5,0

$105,00 AUD

Analyses using simulink model

Good work done..will hire him again

Matlab and Mathematica

Mechanical Engineering

Electrical Engineering

Olaide Grace E.

@olaideejiwole

•

vor 6 Jahren

Ausbildung

Bachelor's Degree in Mechatronics Engineering

Sana'a University,

Yemen

2012 - 2017

(5 Jahre)

Kontaktieren Sie Mohamed D. bezüglich Ihres Jobs

Melden Sie sich an, um Details im Chat zu besprechen.

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Electrical Engineering

5

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