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$12 USD / jam
Bendera EGYPT
giza, egypt
$12 USD / jam
Sekarang jam 3:35 PTG di sini
Menyertai Jun 13, 2022
0 Syor

Sohaila E.

@SohailaDiab

 5.0 (1 ulasan)
0.0
0.0
100%
100%
$12 USD / jam
Bendera EGYPT
giza, egypt
$12 USD / jam
100%
Pekerjaan Disiapkan
100%
Mengikut Bajet
100%
Tepat Pada Masa
N/A
Kadar Upah Semula

Data Analyst | Machine Learning | Python Developer

Hello! I am a CS student in Cairo University, passionate about working with data to get fascinating results. I'm an experienced data analyst, ML engineer and Python developer. I have been working on data analysis and machine learning projects for more than a year now, and my core expertise are: - Python - Machine learning with Sklearn, PyTorch, TensorFlow, and Keras - Data Analysis using Pandas, Matplotlib, NumPy, Plotly, and Seaborn - SQL Server and MySQL - Deep Learning with PyTorch Some of my projects: - Parkinson's Disease hand drawing image classification using CNNs and transfer learning - No Show Appointments Data Analysis - U.S. Bikeshare data analysis with an interactive Python environment - Sentiment Analysis on Movie Reviews using Logistic Regression - Real Estate Price Prediction using XGBRegression - Bank Management System using SQL Server and C# to create a web app I am also currently a Machine Learning head in Google Developer Student Clubs. I led and worked with my team of 10 to host a successful machine learning workshop with over 60 students. I am looking forward to working with you!
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Portfolio

10236874
- Built a Logistic Regression model to predict what is the sentiment of each movie review phrase on a scale of 1-5. - Achieved a Kaggle score of 61% and was one of the top 50%. Notebook: https://www.kaggle.com/code/sohailadiab/movie-reviews-data-modeling
Sentiment Analysis on Movie Reviews
10236863
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
10137352
Certificate for completion of Data Analysis Advanced Nanodegree at Udacity. During the Nanodegree program, I completed two projects: 1. No Show Appointments Data Analysis – Notebook(https://github.com/SohailaDiab/No-Show-Appointments-DataAnalysis/blob/main/MedicalAppointmentNoShows_Analysis.ipynb) • Was able to come up with several possible conclusions to why 30% of patients miss their scheduled appointments. • Went throught the data analysis process: - Understanding the business question - Data Wrangling (Gathering, Assessing, and Cleaning the data) - Exploratory Data Analysis 2. Explore U.S. Bikeshare Data – Code(https://github.com/SohailaDiab/Explore-U.S.-Bikeshare-Data/blob/master/bikeshare_2.py) Built a user-friendly interactive environment that filtered the data according to the user’s needs (input) and calculated statistics to analyze U.S. Bikeshare dataset using Python and Pandas.
Udacity Advanced Data Analysis Nanodegree
Certificate for completion of Data Analysis Advanced Nanodegree at Udacity. During the Nanodegree program, I completed two projects: 1. No Show Appointments Data Analysis – Notebook(https://github.com/SohailaDiab/No-Show-Appointments-DataAnalysis/blob/main/MedicalAppointmentNoShows_Analysis.ipynb) • Was able to come up with several possible conclusions to why 30% of patients miss their scheduled appointments. • Went throught the data analysis process: - Understanding the business question - Data Wrangling (Gathering, Assessing, and Cleaning the data) - Exploratory Data Analysis 2. Explore U.S. Bikeshare Data – Code(https://github.com/SohailaDiab/Explore-U.S.-Bikeshare-Data/blob/master/bikeshare_2.py) Built a user-friendly interactive environment that filtered the data according to the user’s needs (input) and calculated statistics to analyze U.S. Bikeshare dataset using Python and Pandas.
Udacity Advanced Data Analysis Nanodegree
Certificate for completion of Data Analysis Advanced Nanodegree at Udacity. During the Nanodegree program, I completed two projects: 1. No Show Appointments Data Analysis – Notebook(https://github.com/SohailaDiab/No-Show-Appointments-DataAnalysis/blob/main/MedicalAppointmentNoShows_Analysis.ipynb) • Was able to come up with several possible conclusions to why 30% of patients miss their scheduled appointments. • Went throught the data analysis process: - Understanding the business question - Data Wrangling (Gathering, Assessing, and Cleaning the data) - Exploratory Data Analysis 2. Explore U.S. Bikeshare Data – Code(https://github.com/SohailaDiab/Explore-U.S.-Bikeshare-Data/blob/master/bikeshare_2.py) Built a user-friendly interactive environment that filtered the data according to the user’s needs (input) and calculated statistics to analyze U.S. Bikeshare dataset using Python and Pandas.
Udacity Advanced Data Analysis Nanodegree
10236827
- Database Design Project (SQL). Developed a bank management system to store, manipulate and display bank information for customers and employees. - Designed an ER model and translated the model to a relational schema. - Created and implemented a desktop application using C# and SQL Server.
Bank Management System
- Database Design Project (SQL). Developed a bank management system to store, manipulate and display bank information for customers and employees. - Designed an ER model and translated the model to a relational schema. - Created and implemented a desktop application using C# and SQL Server.
Bank Management System
Bank Management System
Bank Management System
10236008
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning
10236874
- Built a Logistic Regression model to predict what is the sentiment of each movie review phrase on a scale of 1-5. - Achieved a Kaggle score of 61% and was one of the top 50%. Notebook: https://www.kaggle.com/code/sohailadiab/movie-reviews-data-modeling
Sentiment Analysis on Movie Reviews
10236863
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
- Earned a bronze medal for this project on Kaggle. - Built an XGBRegression model to predict the price of a unit area of a house given its features. - Achieved a score of 78% Notebook: https://www.kaggle.com/code/sohailadiab/real-estate-price-prediction
Real Estate Price Prediction
10137352
Certificate for completion of Data Analysis Advanced Nanodegree at Udacity. During the Nanodegree program, I completed two projects: 1. No Show Appointments Data Analysis – Notebook(https://github.com/SohailaDiab/No-Show-Appointments-DataAnalysis/blob/main/MedicalAppointmentNoShows_Analysis.ipynb) • Was able to come up with several possible conclusions to why 30% of patients miss their scheduled appointments. • Went throught the data analysis process: - Understanding the business question - Data Wrangling (Gathering, Assessing, and Cleaning the data) - Exploratory Data Analysis 2. Explore U.S. Bikeshare Data – Code(https://github.com/SohailaDiab/Explore-U.S.-Bikeshare-Data/blob/master/bikeshare_2.py) Built a user-friendly interactive environment that filtered the data according to the user’s needs (input) and calculated statistics to analyze U.S. Bikeshare dataset using Python and Pandas.
Udacity Advanced Data Analysis Nanodegree
Certificate for completion of Data Analysis Advanced Nanodegree at Udacity. During the Nanodegree program, I completed two projects: 1. No Show Appointments Data Analysis – Notebook(https://github.com/SohailaDiab/No-Show-Appointments-DataAnalysis/blob/main/MedicalAppointmentNoShows_Analysis.ipynb) • Was able to come up with several possible conclusions to why 30% of patients miss their scheduled appointments. • Went throught the data analysis process: - Understanding the business question - Data Wrangling (Gathering, Assessing, and Cleaning the data) - Exploratory Data Analysis 2. Explore U.S. Bikeshare Data – Code(https://github.com/SohailaDiab/Explore-U.S.-Bikeshare-Data/blob/master/bikeshare_2.py) Built a user-friendly interactive environment that filtered the data according to the user’s needs (input) and calculated statistics to analyze U.S. Bikeshare dataset using Python and Pandas.
Udacity Advanced Data Analysis Nanodegree
Certificate for completion of Data Analysis Advanced Nanodegree at Udacity. During the Nanodegree program, I completed two projects: 1. No Show Appointments Data Analysis – Notebook(https://github.com/SohailaDiab/No-Show-Appointments-DataAnalysis/blob/main/MedicalAppointmentNoShows_Analysis.ipynb) • Was able to come up with several possible conclusions to why 30% of patients miss their scheduled appointments. • Went throught the data analysis process: - Understanding the business question - Data Wrangling (Gathering, Assessing, and Cleaning the data) - Exploratory Data Analysis 2. Explore U.S. Bikeshare Data – Code(https://github.com/SohailaDiab/Explore-U.S.-Bikeshare-Data/blob/master/bikeshare_2.py) Built a user-friendly interactive environment that filtered the data according to the user’s needs (input) and calculated statistics to analyze U.S. Bikeshare dataset using Python and Pandas.
Udacity Advanced Data Analysis Nanodegree
10236827
- Database Design Project (SQL). Developed a bank management system to store, manipulate and display bank information for customers and employees. - Designed an ER model and translated the model to a relational schema. - Created and implemented a desktop application using C# and SQL Server.
Bank Management System
- Database Design Project (SQL). Developed a bank management system to store, manipulate and display bank information for customers and employees. - Designed an ER model and translated the model to a relational schema. - Created and implemented a desktop application using C# and SQL Server.
Bank Management System
Bank Management System
Bank Management System
10236008
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: - Pytorch - Multi-Layer Perceptrons - Fine-tuning - Convolutional Neural Networks - Natural Language Processing - Reinforcement Learning - Computer Vision - Completed a computer vision project titled "Parkinson's Disease Detection", which evaluates the research question: “Can we predict if a person is healthy or has Parkinson’s Disease based on their drawing of a spiral?” - Implemented a CNN model using transfer learning (used ResNet18 model). - Applied image augmentation, such as random horizontal flip, to increase accuracy. - Achieved a score of 68.5%
Neuromatch Academy Deep Learning

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Sohaila delivered on time and within budget. Thanks for the quick and helpful input.
Machine Learning (ML)
Artificial Intelligence
Scikit Learn
Tensorflow
Deep Learning
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Bendera Samuel I.
@samuelid
•
2 tahun yang lalu

Pengalaman

Machine Learning Head

Google Developer Student Clubs
Sep 2021 - Hari ini
- Led a team of 10 to host a successful machine learning workshop with 60+ students. - Worked with the team to organize tech talks for students given by field experts.

Kelayakan

Deep Learning Academy

Neuromatch Academy
2022
- An intensive 3-week deep learning academy. - Learned important DL fundamentals with hands-on exercises: Pytorch, Multi-Layer Perceptrons, Fine-tuning, Convolutional Neural Networks, Natural Language Processing, Reinforcement Learning. - Completed a computer vision project titled "Parkinson's Disease Detection".

Data Analysis Professional Nanodegree Program

Udacity
2022
- Learned how to efficiently use Python, NumPy and Pandas for data analysis. - Learned how to perform the entire data analysis process: - Understanding the business question - Data Wrangling (Gathering, Assessing, and Cleaning the data) - Exploratory Data Analysis - Worked on multiple datasets, and made 2 data analysis final projects.

Artificial Intelligence Training

ITIDA and NTI
2021
- Successfully completed the summer training course for the duration of 4 weeks (120 hours) Consisted of: - Math and Statistics - Machine Learning - Deep Learning with Tensorflow and Keras - General Skills: Communication Skills, Interview Skills, Presentation Skills - Leadership Skills, Teamwork Skills, Decision Making and Problem Solving Skills, Time Management Skills - Freelancing Skills, Introduction To Information Security and Privacy

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Machine Learning (ML) 1
Deep Learning 1
Python
Data Processing
SQL

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