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Data science projects🚀

My personal (public) project to share tools and tips about Data Science and Python

What do you need to be a great data scientist?

  1. Critical Thinking (like every scientist)
  2. Python, R, Julia (at least intermediate level), some C or C++
  3. Statistics
  4. Linear Algebra
  5. Differential Equations
  6. Creativity
  7. Good Learning Techniques
  8. Machine Learning
  9. Deep Learning
  10. Big Data Analysis (Spark, Map-Reduce principle, Ray)
  11. ETL Pipeline + DataSet generation
  12. ...one or two topic to specialize your skills (i.e. Autonomous Driving, Reinforcement Learning, Computer Vision, Finance)

Goals

  • Simple Reinforcement Learning (or other online learning system)
    • Q-Table
    • Deep Q-Learning (Experience Replay)
  • GUI basics (QT, ImGUI, ...)
  • Physical Simulations
  • BioInformatics
  • Effective Data Visualizations (Seaborn, DataViz, ...)
  • One simple and effective tool to improve Computer Vision accuracy (No Flatten Information etc...) like this
  • Explainable AI
  • Edge AI (TinyML, Raspberry, ...)
  • Transformers (NLP and Text-to-Image)
    • Visual
    • Stable Diffusion
    • Mistral
  • Business Process Automation (PowerBI, Zapier, etc...)
  • RAG (Retrieval-Augmented Generation)

Projects

  • Finance
    • Stock Prediction
    • Risk Analysis
    • Portfolio Management
  • Physics
    • New Materials
    • Simulations