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$10 USD / hora
Bandera de PALESTINIAN TERRITORY
gaza, palestinian territory
$10 USD / hora
Aquí son las 2:24 p. m.
Se unió el noviembre 6, 2016
0 Recomendaciones

Nader S.

@Engneernader

 4,8 (1 comentario)
0,8
0,8
100%
100%
$10 USD / hora
Bandera de PALESTINIAN TERRITORY
gaza, palestinian territory
$10 USD / hora
100 %
Trabajos finalizados
100 %
Dentro del presupuesto
100 %
A tiempo
N/A
Tasa de recontratación

Python Developer

I am Data Scientist, I have 2 years of experience in Machine learning and data analysis. My target is to exceed client expectations and ensure they are 100% satisfied. I look forward to working with my clients to help reach their business goals. I am always focused on what I provide to clients and always recheck my code quality and also focused about good results. I am extremely passionate about solving problems in the following domains: • Libraries: (Numpy,Pandas,matplotlib) • And Machine learning algorithms: (KNN,PCA,LDA,Random forest,k-means) I did various projects in this field: • Prediction • Classification • Data Analysis • Data exploration/visualization • Object Detection/Recognition • Tkinter GUI • Supervised and Unsupervised Learning I'm very Fast Response and ability to learn new field . I am working as individual and I can be team player, I also have full stack development experience working with customers worldwide.
Freelancer Data Analysts Palestinian Territory
Ver todo Data Analysts en Palestinian Territory

Contacta Nader S. sobre tu trabajo

Inicia sesión para comentar cualquier detalle por chat.

Portafolio

6913154
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
6908161
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
6913154
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
In this project, I trained the machine on two types of plates(clean and dirty), made the machine recognize new dishes and classify them into two types.
Clean and Dirty classification plate recognition.
6908161
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.
COVID-19 has infected more than 10,000 people in South Korea. KCDC (Korea Centers for Disease Control & Prevention) Announced the information of COVID-19 quickly and transparently. I analyzed and visualized the data using various data mining or visualization techniques. I maked a structured dataset that can be used in the report materials of KCDC and local governments.
Analyse visualized dataset of Covid-19 in South Korea.

Comentarios

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4,8
$25,00 USD
Data Classification -- 2
thank you nader looking to work with you again
Security Systems
Data Analysis
A
Bandera de Lena A.
@aljehanilena
•
hace 4 años

Experiencia

Data Analysis

Islamic university
ene 2020 - nov 2020 (10 meses, 1 día)
I have obtained training at the Islamic University in the field of data analysis and data science and then worked through the university projects in this field.

Educación

BA

Palestinian Territory 2016 - 2019
(3 años)

Calificaciones

Data science , Data Analysis

Islamic university
2020
I have received training at the Islamic University in the field of data analysis and data science.

Contacta Nader S. sobre tu trabajo

Inicia sesión para comentar cualquier detalle por chat.

Verificaciones

Freelancer preferente
Identidad verificada
Pago verificado
Teléfono verificado
Email verificado
Facebook conectado

Principales habilidades

Data Analysis 1
PHP
JavaScript
Python
SQL

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