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$22 USD / tunti
Maan EGYPT lippu
bani sweif, egypt
$22 USD / tunti
Aika on tällä hetkellä 11:48 ap. täällä
Liittynyt maaliskuuta 5, 2021
0 Suosittelee

Mohamed S.

@mohamedsamir3

 4,8 (20 arvostelua)
3,1
3,1
91%
91%
$22 USD / tunti
Maan EGYPT lippu
bani sweif, egypt
$22 USD / tunti
75 %
Suoritetut työt
75 %
Budjetin mukaisesti
75 %
Aikataulussa
4 %
Uudelleenpalkkausaste

Data Science, AI/ ML, Real Estate, Healthcare

Because I believe in the untapped potential in each and every one of us, I develop AI products to automate intelligent processes, offering people more space to unfold their greatest potential. With every AI solution I deploy, someone is given the opportunity to step up to their true potential. Data science is not only my dream job, but the lens in which I learn about the world, people and perspectives. Creating computer programs that can autonomously think and decide fascinates me. Every day I have the privilege of experiencing a priceless combination of art and science, envisioning and implementing, learning and impacting I thrive in machine learning and data science environments through team collaboration and take any opportunity to learn from others and prove my own expertise. I am a self motivated problem solver and hope to find meaningful work in a field that constantly challenges me. I have a lot of challenges developing my skills
Freelancer Python Developers Egypt
Katso kaikki Python Developers paikassa Egypt

Ota yhteyttä käyttäjään Mohamed S. työhösi liittyen

Kirjaudu sisään keskustellaksesi yksityiskohdista chatissa.

Portfolio

10591070
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
10591065
There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development
Titanic Data Science
There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development
Titanic Data Science
There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development
Titanic Data Science
There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development
Titanic Data Science
10591055
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction
10591070
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
Black Friday marks the beginning of the Christmas shopping festival across the US. On Black Friday big shopping giants like Amazon, Flipkart, etc. lure customers by offering discounts and deals on different product categories. The product categories range from electronic items, Clothing, kitchen appliances, Décor. Research has been carried out to predict sales by various researchers. The analysis of this data serves as a basis to provide discounts on various product items. With the purpose of analyzing and predicting the sales, we have used three models. The dataset Black Friday Sales Dataset available on Kaggle has been used for analysis and prediction purposes. The models used for prediction are linear regression, lasso regression, ridge regression, Decision Tree Regressor, and Random Forest Regressor. Mean Squared Error (MSE) is used as a performance evaluation measure. Random Forest Regressor outperforms the other models with the least MSE scor
Black Friday
10591065
There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development
Titanic Data Science
There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development
Titanic Data Science
There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development
Titanic Data Science
There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development The notebook walks us through a typical workflow for solving data science competitions at sites like Kaggle. There are several excellent notebooks to study data science competition entries. However many will skip some of the explanation on how the solution is developed as these notebooks are developed by experts for experts. The objective of this notebook is to follow a step-by-step workflow, explaining each step and rationale for every decision we take during solution development
Titanic Data Science
10591055
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction
Car Price Prediction is a really an interesting machine learning problem as there are many factors that influence the price of a car in the second-hand market. In this competition, we will be looking at a dataset based on sale/purchase of cars where our end goal will be to predict the price of the car given its features to maximize the profit
Car Price Prediction

Arvostelut

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Näytetään 1 - 5 / 20 arvostelua
Suodata arvosteluja:
5,0
€40,00 EUR
need an expert in machine learning to use federated learning model and get people's interest from their device data -- 3
He is really expert and delivered on time and. Would recommend him highly
Python
Data Processing
Machine Learning (ML)
Data Mining
Data Science
Käyttäjän avatar
Maan lippu Arpita S.
@sarkerofc
•
vuosi sitten
5,0
₹100,00 INR
Project for Mohamed S.
This is amazing. It is a very wonderful work. I hope to work with you again. Very excellent work
Java
Python
Algorithm
Statistics
Machine Learning (ML)
+1 enemmän
M
Closed User
@mahmudsamir03
•
vuosi sitten
1,0
$12,50 USD
Project for Mohamed S.
do not trust - he said you could create a python script that creates a cartoon effect - and he did not at all. Then argued about accpeting my cancelation request. Will never use again
Java
Python
Algorithm
Statistics
Machine Learning (ML)
+1 enemmän
D
Maan lippu Daniel S.
@dstiefe
•
vuosi sitten
5,0
$110,00 CAD
OpenGL and Python task
Fantastic job! I will definitely work with him again
Python
OpenGL
N
Maan lippu Daniel B.
@night6320
•
vuosi sitten
0,0
$20,00 USD
Project 34306363 has been deleted
The project is not completed according to the dispute
Käyttäjän avatar
Maan lippu Joao R.
@jhonysbh
•
2 vuotta sitten

Kokemus

Associate Researcher

EnGaz for Translation and Research services
maalisk. 2023 - Voimassa
I have developed a deep understanding of the translation industry and the challenges that organizations face when communicating across languages and cultures. My work involves conducting research on best practices for translation and localization, as well as identifying trends and developments in the industry. With a strong background in research methodologies and data analysis, I am skilled in designing and implementing research studies that provide valuable insights to organizations.

Data Scientist

Freelancer
syysk. 2022 - Voimassa
- Work on various data science projects for clients across industries, including healthcare, finance, and e-commerce. - Collect and analyze data, build predictive models, and perform statistical analysis to extract insights and provide actionable recommendations. - Develop and deploy machine learning models using various technologies, such as scikit-learn, TensorFlow, and Keras. - Create custom data visualizations to communicate insights and findings to clients.

Software Engineer

EgSA-Egyptian Space Agency
kesäk. 2021 - lokak. 2021 (4 kuukautta, 2 päivää)
Developed and maintained software for satellite control systems, including telemetry data processing and command and control interfaces. - Designed and implemented software for satellite mission planning and scheduling, including orbit determination and trajectory analysis. - Contributed to the development of the agency's ground station network, including the design and implementation of network protocols and interfaces.

Koulutus

Bachelor's of Computer Science

Nahda University in Beni Suef, Egypt 2018 - 2022
(4 vuotta)

Pätevyydet

Ask Questions to Make Data-Driven Decisions

Google
2021
- Ask Questions to Make Data-Driven Decisions - An online non-credit course authorized by Google and offered through Coursera

Certified Data Science Professional

Epsilon Ai
2020
- Completed all 10 required courses in DS(120 hours). - Mastered 10 crucial data science skills.

Ota yhteyttä käyttäjään Mohamed S. työhösi liittyen

Kirjaudu sisään keskustellaksesi yksityiskohdista chatissa.

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Statistics 5
Algorithm 4
Data Mining 3

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