gizachew29 / data-science-portofolio

Data Science Portfolio

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Masters thesis: Respiratory modulation of cardiovascular brain pulsations in Alzheimer’s disease

• Utilized statistical methods to find the significant differences in the modulation of brain cardiovascular pulse with respiration between controls and Alzheimer’s cases to help the neurological researchers to have a better understanding of Alzheimer’s diseases. The differences found were strongly significant (P<0.01) and novel.
• Preprocessed and extracted features using a 3D multiresolution optical flow of 0.25 TB complex brain imaging data using python.
• Publication: Youssef Hosni, Ahmed Elabasy et.al., Respiration modulates cardiovascular brain impulse pathology in Alzheimer’s disease. Submitted to Journal of Cerebral Blood Flow and Metabolism.
• Publication: Ahmed Elabasy, Youssef Hosni et.al., Optical Flow Analysis of Propagating Respiratory Brain Pulsations. Submitted to IEEE Transactions on Medical Imaging.

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Machine Learning:

Regression

• Automobile price prediction: Utlitize python to implement end to end data science pipeline to predict the price of old Automobile based on the given features.

Classification

• Sensor Activity Recogniation: Classifying the output of eight sensors into five activities and studied the effect of changing window sizes and axel combination.
• Alzhimers CV-BOLD Classification: Utilized Python to develop supervised machine learning techniques to classify imbalanced Alzheimer’s CVBOLD data, which enhanced the classification performance by 10%.

Clustering

• Find the best location to open a new Gym: Utilized python to implement unsupervised techniques to helping the business owner to increase his revenue by finding the best neighborhood to open a new gym.
• Customer identification for mail order products: Utilized python to implement unsupervised techniques to helping the business owner to increase his revenue by finding the best neighborhood to open a new gym.

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Deep Learning

• Melenoma Classification: Classifying malignant Melanoma using skin lesion images using CNN-based classifiers.

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Computer Vision

• Pose Estimation and Squat counter: Utilize python to develop a real-time pose estimation and squat counter using MovingNet lightning.

• Real Time Sign Language interpretation App: Developed a real-time sign language interpretation application using React.js and tensorflow.js.

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Natural Language Processing

• Sentiment Analysis web app: Web application for classification of reviews, using deep learning model implemented in PyTorch and deployed on Amazon SageMaker.
• Plagirasm Detector web app: Creating plagiarism detector trained on LSC and containments features and deployed on AWS SageMaker.
• Data Science Resume Selector: Selecting the resume that are eligbile to data scientist postions, the dataset used contains 125 resumes, in the resumetext column. Resumes were queried from Indeed.

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Time series Analysis

• Power consumption prediction: Classifying malignant Melanoma using skin lesion images using CNN-based classifiers.

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Data Analysis

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Data Visulization:

• Immigrants to Canada data visulization: Visualizing the data of the immigrants to Canada using different visualizing libraries in Python.
• Geospatial visualization of San Francisco Police Department Incidents: Visualizaing the geospatial data of the San Francisco police department incidents for the year 2016.

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Spark

• San Diego Rainforest Fire Predicition: Predicting the occurance of rainforest fire in san Diego using weather data collected by san Diego weather center.
• Cluster Analysis of the San Diego Weather Data: Ultilizing pyspark to implement unsupervised learning model to cluster the san Diego weather data so as to better understand the occurance of the rainforest fire.

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Data Modeling

• Songs App User Activity Data Modeling : Modeling user activity data for a music streaming app called Sparkify to optimize queries for understanding what songs users are listening to by creating a Postgres relational database and ETL pipeline to build up Fact and Dimension tables and insert data into new tables.
• Songs App data modeling using Apache Casandra: Create an Apache Cassandra database which can create queries on song play data to answer analysis questions.

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Certificates

• Machine Learning Specialization
• Big Data Specialization
• Intro to Machine Learning with Tensorflow Nanodegree
• Machine Learning Engineer Nanodegree
• AWS Fundemntals Specialization
• Data Science Professional Certificate
• AI for Medicine
• Data Visualization with Seborn
• Time Series Forecasting
• Data-Visualization-with-Plotly-in-Python
• Machine Learning Explanality-Kaggle

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Course Work

• Deep Learning
• Data Science
• Machine learning engineering
• Intro to machine learning with tesnorflow
• Data Engineering
• Time Series Kaggle Course
• Data Visualization Kaggle Course
• Data-Visualization-with-Plotly-in-Python
• Machine Learning Explanality-Kaggle