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Informative review notes on Machine Learning / Deep Learning concepts. Each folder represents a distinct branch, including some theoretical explanation + coding and useful examples as well as projects.

Jupyter Notebook 99.90% Python 0.10%
machine-learning linear-regression data-science numpy pandas matplotlib scipy logestic-regression deep-learning tensorflow2

machine_learning_note's Introduction

Hi this is Parisima ๐Ÿ˜Š

  • ๐ŸŽ“ I recently graduated with a Master's degree in Electrical and Computer Engineering from New York University!
  • ๐Ÿง  I'm deeply passionate about learning various Machine Learning and Deep Learning techniques. My work has predominantly focused on Image Processing, Computer Vision, and Deep Learning, particularly within the Inverse Problems and Generative domains.
  • ๐Ÿš€ My hobbies include camping ๐Ÿ•๏ธ, working out ๐Ÿ’ช, hiking ๐ŸŒ„, painting ๐ŸŽจ, dancing ๐Ÿ’ƒ, among others!
  • ๐Ÿค I am always open to collaboration within teams, so please feel free to reach out! [email protected]
  • ๐Ÿ” I will be regularly updating this space! (Note: Some repositories are still private.) Check back often for more updates!

Tools:

Python MATLAB C C++ SQL VHDL Tableau LaTeX Shell Jekyll VSCode TensorFlow PyTorch NumPy SciPy Seaborn Pandas OpenCV Scikit-learn Matplotlib CUDA HPC Azure

Illustration:

Adobe Photoshop Adobe After Effects Adobe Premiere Pro

machine_learning_note's People

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