Projects

Machine Learning

Python
Machine Learning
Data Analysis
Neural Networks

Implementation of machine learning algorithms for data analysis and prediction, including neural networks and traditional ML approaches

Visual representation of machine learning models and data analysis results GitHub Project

This project focuses on implementing and comparing various machine learning algorithms for real-world applications. The work includes both traditional machine learning approaches and neural networks, with an emphasis on practical implementation and performance analysis.

Key aspects of the project:

  • Implementation of multiple ML algorithms from scratch
  • Data preprocessing and feature engineering
  • Model training and validation
  • Performance comparison between different approaches
  • Visualization of results and insights

The project is implemented in Python, utilizing popular libraries such as NumPy, Pandas, and scikit-learn for data processing and analysis. The code is available on GitHub, along with detailed documentation and example use cases.