Data has a story
Data Analyst – Data Scientist
I have been solving business problems oriented in data-driven solutions since 1999 and I can handle a large variety of them. I can analyze and transform data and discover patterns to use them as features for different kind of analyses or predictive models.
Ι create updateable, maintainable and reusable Machine Learning and Data Analysis systems in Python using the OOP paradigm. The systems read and preprocess data and can perform automated analyses. The systems may have the ability to train and optimize predictive models and retrain models when updated with new data.
The final user will not need coding skills to use the system’s tools and may access them easily from Jupyter Notebook as well as from other environments or encompass them in their server. Full support to use these tools will be provided.
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Feature Learning
- Anomaly Detection.
- University of Piraeus: Bachelor, “Bachelor in Economics”
- University of Michigan: Specialization, “Python for Everybody”.
- University of Michigan: Specialization, “Applied Data Science with Python”
- Wesleyan University: Specialization, “Data Analysis and Interpretation”.
- MIT: Specialization, “Computational Thinking Using Python”.
- Duke University: Specialization, “Java Programming and Software Engineering Fundamentals”.
- Duke University: Course, “Data Science Math Skills”.
- Harvard: Course, “Using Python for Research”.
- Imperial College London: Course, “Mathematics for Machine Learning: Linear Algebra”.
- Mathesis: Course, “Introduction to Python”.
- Mathesis: Course, “Advanced Python”.
- Mathesis: Course, “Mathematics – Probabilities”
- deeplearning-ai: Course, Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning”.
- deeplearning-ai: Course, “Convolutional Neural Networks in TensorFlow”.
- National Research University Higher School of Economics: Course, “Introduction to Deep Learning”.
- National Research University Higher School of Economics: Course, “How to Win a Data Science Competition”.
- Greek: Native
- English: Proficiency of Cambridge in the English Language (C2)
- Academia-edu: “Using Machine Learning for Text Classification to identify useful information in texts: A comparison of Naïve Bayes and Support Vector Machines to identify decisions in business meeting transcripts”
- Mathesis: Linguistic Course, “What is language”.
- Mathesis: Philosophy Course, “From Thales to Aristotle”.
- Mathesis: Philosophy Course, “Aristotelian Ethics”.
- Mathesis: Philosophy Course, “Plato”
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