This was my first time using machine learning on real-world data, I applied PCA and PLS regression to analyze chemical data and predict wine quality, applying dimensionality reduction techniques effectively
Used Pandas and Scikit-learn throughout the process
This was my first machine learning project, I explored regression and neural network models to predict GPL, learning the basics of ML models and neural networks along the way
sed Scikit-learn for ML models and PyTorch for neural networks
I implemented federated learning to train object detection models across multiple edge devices, focusing on efficient client-server communication and data privacy
Implemented federated learning using FLWR
I learned about PySpark and its application to large datasets, focusing on efficient data processing and implementing regression, classification, and clustering models
Used PySpark and scikit-learn for data processing and model training
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