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π Hi, Iβm Ekene!
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π οΈ Python Developer with a strong interest in Machine/Deep learning, data visualization, and creative problem-solving. Expert in Django & Flask framworks for robust and scalable web apps. I excel in both Front and Back-End design. Extremely passionate about programming and community development.
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π Certified mechanical engineer with 4+ years of experience using 3D modeling, data processing, data mining and machine learning algorithms to help solve challenging business problems.
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π± I am curently completing an OpenClassrooms training program as Artificial Intelligence Engineer (July 2020 - Date), developed in partnership with Microsoft and Centrale Supelec. Details can be found here.
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π Iβm interested in Data Science, Machine & Deep Learning
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ποΈ I'm really interested in problem solving and decision making with data ; my focus is to develop, optimize and reformulate repeatable models to solve challenging and high-value business problems, and provide actionable insights.
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π§ I love working in a cross-functional environment, to collaborate with different teams on all data-related topics (data management, data engineering, data science, etc.).
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π Iβm looking to collaborate on as many projects as possible! I'm also looking for a permanent role within data team where I could develop my functional skills further.
- π©βπ» Programming language(s): Python, R, HTML CSS
- π οΈ Development tools : Jupyter Notebook (Anaconda), Google Colaboratory, Visual Studio Code, Github, PyCharm, Sublime, Atom, Kaggle
- π©βπ¬ Data Science: pandas, numpy, scikit-learn, tensorflow, keras
- π Data Viz: matplotlib, seaborn, plotly
- π¬ ποΈβπ¨οΈ Artificial intelligence : NLP (with Sklearn, NTLK, Spacy, Gensim) and Computer Vision (Classification, Semantic Segmentation)
- βοΈ Cloud Computing: Microsoft Azure
- π Flask / Django Developement
- ποΈ Database : PostgreSQL, MySQL, MongoDB
- World University Rankings: Multivariate Data Analysis using PCA
- World University Rankings: Multivariate Data Analysis using K-Means
- World University Rankings: Multivariate Data Analysis using Hierarchical Clustering
- Open Food Facts: Multivariate Data Analysis
- Credit Scoring Model: Classification Models With Imbalanced Data
- Customer Segmentation: K-Means Clustering