mohamed elbeih

تقييم البيانات تحليل البيانات المحترف تنقيب البيانات تنسيق إدارة قاعدة البيانات بايثون (لغة برمجة) قاعدة بيانات SQL Strong mathematical and statistical background Solid knowledge of Data Structure and Algorithms Solid Knowledge of Object Oriented Programming (OOP) Data gathering ( Web scraping with Beautifulsoup ) Proficiency in SQL queries for structured data Familiarity with MongoDB for unstructured data ( NoSQL databases ) Exploratory Data Analysis (EDA) Proficiency in Plotly and Plotly dash for visualization and building interactive dashboard Proficiency in Tableau ( visualization dashboards and storytelling ) Deep understanding and Proficiency in implementing A/B Tests Proficiency in coding with Python programming language with a high command of the data science related libraries and modules as: Pandas Numpy Matplotlib seaborn OpenCV and NLTK Data sampling techniques feature selection methods and dimensionality reduction techniques Proficiency in machine learning algorithms including Regression classification unsupervised learning algorithms association rules learning and ensemble learning techniques Hands on ML/DL frameworks as: Sci-Kit learn Keras and Tensorflow Proficiency in time series analysis and forecasting ( LSTM and statsmodels library familiarity with Prophet library and kats toolkit from Facebook and also Transformers Models ) Hands on unsupervised deep learning techniques such as self organized map for features extraction Boltzmann machines and autoencoders algorithms for recommendation systems Proficiency in implementing deep learning models in various computer vision applications as : Image Classification Object Detection and Image Segmentation using SOTA algorithms Hands on traditional Statistical Language Models such as Bow TF-IDF N-gram and Neural Language Models such as word2vec Glove Seq2seq model with LSTM Attention mechanism For dealing with multiple NLP tasks such as sentiment analysis named entity recognition topic modeling text summarization and generation chatbots and machine translation Deep understanding in Transformers for language models and hands on models build on top of it ( Bert GPT2 … etc ) Productionization with Flask and Plotly Dash Proficient in using ( Microsoft Office Package ) Specially Excel : ( Data visualization and pivot tables Creating advanced formulas and Crafting advanced charts and tables ) Ability to learn new technologies and evaluate multiple technologies to solve a problem Pytorch framework Deployment variations and integrations Generative Adversarial Networks ( GANs ) Mathematics Statistics Data Structures Algorithms Object-Oriented Programming (OOP) Data gathering Web scraping BeautifulSoup Data wrangling SQL MongoDB NoSQL Plotly Dash (Plotly Dash) Tableau A/B testing Pandas NumPy Matplotlib Seaborn OpenCV NLTK Data sampling Feature selection Dimensionality reduction Machine learning Regression Classification Unsupervised learning Association rule learning Ensemble learning scikit-learn Keras TensorFlow Time series analysis Forecasting LSTM statsmodels Prophet Kats Transformers Self-organizing map Boltzmann machines Autoencoders Recommendation systems Deep learning Computer vision Image classification