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$20 USD / hour
Flag of EGYPT
ashmoun, egypt
$20 USD / hour
It's currently 11:40 AM here
Joined December 22, 2018
1 Recommendation

Omar Ahmad-Magdy E.

@omarelnahas500

annual-level-two.svgpreferred-freelancer-v2.svgverified.svg
5.0 (29 reviews)
5.9
5.9
$20 USD / hour
Flag of EGYPT
ashmoun, egypt
$20 USD / hour
100%
Jobs Completed
100%
On Budget
100%
On Time
24%
Repeat Hire Rate

Data Analyst & ML engineer

I am Data Analyst experienced in: • Data Assessing and cleaning • Data Visualization • Statistical Analysis • Python Development • Back-end Development. • Data Engineering. I am currently a computer science undergraduate student in my senior year, I am willing to learn more and eager to cope up with the latest technologies.
Freelancer Python Developers Egypt

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Portfolio Items

Teams/cup organizer which is regarded as the central agent that has all details about current and future matches including:

Match Time.
Match Score.
Match Teams.
Match Referee. There will be 16 teams participating in the cup. Before playing a match between any two teams, the central agent will tell these two agents with details required to begin the match including:
Opponent Team.
Match Playground.
Match Time. The two agents playing the match together will receive these details and start the match on time. There is a GUI for the central agent giving details about current and future matches to be played including:
Teams names.
Results of matches.
A number of goals were scored and received. There is another GUI created for every match between two agents playing together that shows the time remaining and the current result. For every goal of any team scores, the central agent should be informed to update its data.
Football Matches with Ai Agents
Teams/cup organizer which is regarded as the central agent that has all details about current and future matches including:

Match Time.
Match Score.
Match Teams.
Match Referee. There will be 16 teams participating in the cup. Before playing a match between any two teams, the central agent will tell these two agents with details required to begin the match including:
Opponent Team.
Match Playground.
Match Time. The two agents playing the match together will receive these details and start the match on time. There is a GUI for the central agent giving details about current and future matches to be played including:
Teams names.
Results of matches.
A number of goals were scored and received. There is another GUI created for every match between two agents playing together that shows the time remaining and the current result. For every goal of any team scores, the central agent should be informed to update its data.
Football Matches with Ai Agents
Teams/cup organizer which is regarded as the central agent that has all details about current and future matches including:

Match Time.
Match Score.
Match Teams.
Match Referee. There will be 16 teams participating in the cup. Before playing a match between any two teams, the central agent will tell these two agents with details required to begin the match including:
Opponent Team.
Match Playground.
Match Time. The two agents playing the match together will receive these details and start the match on time. There is a GUI for the central agent giving details about current and future matches to be played including:
Teams names.
Results of matches.
A number of goals were scored and received. There is another GUI created for every match between two agents playing together that shows the time remaining and the current result. For every goal of any team scores, the central agent should be informed to update its data.
Football Matches with Ai Agents
Teams/cup organizer which is regarded as the central agent that has all details about current and future matches including:

Match Time.
Match Score.
Match Teams.
Match Referee. There will be 16 teams participating in the cup. Before playing a match between any two teams, the central agent will tell these two agents with details required to begin the match including:
Opponent Team.
Match Playground.
Match Time. The two agents playing the match together will receive these details and start the match on time. There is a GUI for the central agent giving details about current and future matches to be played including:
Teams names.
Results of matches.
A number of goals were scored and received. There is another GUI created for every match between two agents playing together that shows the time remaining and the current result. For every goal of any team scores, the central agent should be informed to update its data.
Football Matches with Ai Agents
Teams/cup organizer which is regarded as the central agent that has all details about current and future matches including:

Match Time.
Match Score.
Match Teams.
Match Referee. There will be 16 teams participating in the cup. Before playing a match between any two teams, the central agent will tell these two agents with details required to begin the match including:
Opponent Team.
Match Playground.
Match Time. The two agents playing the match together will receive these details and start the match on time. There is a GUI for the central agent giving details about current and future matches to be played including:
Teams names.
Results of matches.
A number of goals were scored and received. There is another GUI created for every match between two agents playing together that shows the time remaining and the current result. For every goal of any team scores, the central agent should be informed to update its data.
Football Matches with Ai Agents
Novel Script Writer using python Tkinter
Novel Script Writer using python
Novel Script Writer using python Tkinter
Novel Script Writer using python
Novel Script Writer using python Tkinter
Novel Script Writer using python
Novel Script Writer using python Tkinter
Novel Script Writer using python
Novel Script Writer using python Tkinter
Novel Script Writer using python
Novel Script Writer using python Tkinter
Novel Script Writer using python
Novel Script Writer using python Tkinter
Novel Script Writer using python
A python program to transcribe audio to excel file of each audio in a folder using IBM Speech to text service
From Speech to Text
A python program to transcribe audio to excel file of each audio in a folder using IBM Speech to text service
From Speech to Text
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
The data used in this notebook is based on Data.gov Climate Change Topic and its US Climate Resilience Toolkit https://toolkit.climate.gov/#explore data with its explorer https://crt-climate-explorer.nemac.org/
Describing How Temperature and Precipitation have changed across years using matplotlib visualizations.
Woodmere,NY Climate Change
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
More About it on https://github.com/omarelnahas23/WeRateDogs
WeRateDogs
more about it on: https://github.com/omarelnahas23/BikeShare-Project
Bike Share
more about it on: https://github.com/omarelnahas23/BikeShare-Project
Bike Share
more about it on: https://github.com/omarelnahas23/BikeShare-Project
Bike Share

Reviews

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Showing 1 - 5 out of 29 reviews
Filter reviews by: 5.0
Price undisclosed
Thank you Omar! Great job. It works exactly as it should work. Parsing is accurate.
Python Machine Learning (ML) OCR Artificial Intelligence Deep Learning
E
Flag of Erig E. @erigevgin
4 months ago
5.0
Price undisclosed
will be happy to work with him in future
Machine Learning (ML) Artificial Intelligence Computer Vision Deep Learning
User Avatar
Flag of Khan F. @rafi0919
5 months ago
5.0
Price undisclosed
Good job delivered in time and very talented. will hire Omar again.
Python Software Architecture Raspberry Pi Data Analysis
+1 more
D
Flag of Doudou A. @doudousl
9 months ago
5.0
Price undisclosed
Omar is great programer he knows what you need and he do it in creative way. he is highly recommended. thank you Omar.
Python OCR
User Avatar
Flag of Esmat S. @esmatsamman
10 months ago
5.0
Price undisclosed
Great Communication
Java Python Software Architecture MySQL C++ Programming
J
Flag of Jarrad G. @jmgholston
11 months ago

Experience

Machine Learning Intern

Si Ware Systems
Oct 2022 - Present
LinkedIn helped me get this job I have been working on Computer vision projects: 1-Object Detection and Tracking 2-Instance and Semantic Segmentation 3- Classification that uses the latest technologies and State of Art Models to achieve highly reliable performance for Quality Control in the Optics Division

Competitor

Huawei
Oct 2019 - Nov 2020 (1 year, 1 month)
I was honored to be selected to participate in The Global Finals of Huawei ICT Practice Competition 2019-2020-cloud track and win the biggest prize of the competition with the Egypt Cloud Team. • I was asked to perform Big Data-related tasks using Huawei Cloud MapReduce Service with: o Apache HIVE o HBase o Spark o Flink o Loader as a lab exam . • I was asked to solve problems using python in national stage. as a lab exam

Education

BSc in Computer Science and Information Technology

Minufiya University, Egypt 2018 - 2022
(4 years)

Qualifications

AI Programming with Python Nanodegree

Udacity
2022
Ai Programming With Python Nano Degree from Udacity and Amazon Web Services (AWS) I was selected to receive The scholarship for the program from AWS alongside 1000 other students globally in the summer cohort as I participated in the DeepRacer student league and managed to secure a place among them. The Program is part of the AI & ML Scholarship powered by AWS in collaboration with Intel Corporation and Udacity you can find more information about it here: https://lnkd.in/dTneVuCm

Data Analysis Professional Nano Degree

Udacity
2021
in this Nanodegree I have learned: 1- Python Basics and Data Structures. 2- Python Numpy and Pandas. 3- Matplotlib functions. 4- Data Gathering and Scarping using python. 5- Data Assessing and cleaning. 6- Data Visualization. 7- Freelancing basics. certificate: https://confirm.udacity.com/GZTEEXVW

Natural Language Processing with Classification and Vector Spaces

Coursera
2020
a) Perform sentiment analysis of tweets using logistic regression and then naïve Bayes, b) Use vector space models to discover relationships between words and use PCA to reduce the dimensionality of the vector space and visualize those relationships, and c) Write a simple English to French translation algorithm using pre-computed word embeddings and locality sensitive hashing to relate words via approximate k-nearest neighbor search.

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Top Skills

Python 25 Software Architecture 11 Data Analysis 9 Linux 8 Apache Hadoop 6

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