Taha Sherif

Valuation of sales data of a Quebec SME - Recommender system • Data exploration and visualization • Clients and products Categorization • Deep learning based recommender system • Technologies: Python, Machine Learning, Deep learning, DNN, ANN, MBA, RFM

Smart OCR for resume parsing • Collect resumes templates using web scrapping • Use object detection to extract different blocks in a resume • Use OCR and NLP to extract relevant information • Deployment using Flask • Technologies: Web scrapping, Deep Learning, CNN OpenCV, YOLOV4, OCR, NLP, Git, Bitbucket, Flask

Online Retail Case • Exploratory Data Analysis (EDA) • Market Basket Analysis • Building a recommendation system • Deployment using Google Cloud Engine • Technologies : Matplotlib, Scikit-learn, Pandas, Seaborn, Apriori Algorithm, Django

Anomalie detection in a computer network using SVM algorithm. Tasks : • Cleaning and organising data (Data Preprocessing) • Construction of classification algorithms (SVM) • Presenting informations using data visualization technologies • Running machine learning tests Technologies : Scikit-learn, Pandas, Seaborn, Statistics