Welcome to my GitHub repository! Here you will find a collection of my machine learning projects ranging from regression models to neural networks. Each project explores different aspects of machine learning algorithms, along with practical examples and visualization techniques.
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Logistic Regression Activity:
Notebook
Implementing logistic regression from scratch to solve binary classification problems. -
Decision Trees:
Notebook
Exploring decision trees for classification and regression tasks. -
Gradient Descent for Linear Regression:
Notebook
A hands-on approach to understanding gradient descent and linear regression. -
Support Vector Machines (SVM):
Notebook
Implementing SVM for classification and exploring the concept of hyperplanes and support vectors. -
Fully Connected Networks (FCN):
Notebook
Understanding and building fully connected networks for supervised learning tasks. -
Linear Regression:
Notebook
Using linear regression to model and predict relationships between variables. -
CNN Tuning and Visualization:
Notebook
Implementing and tuning convolutional neural networks (CNN) for image classification tasks.
Each project contains:
- Complete Jupyter Notebooks with step-by-step explanations.
- Data analysis, preprocessing, and visualization techniques.
- Implementation of core machine learning algorithms from scratch.
- Optimization and performance evaluation using metrics like accuracy, F1-score, and others.
To get started, clone the repository and open the notebooks in your preferred environment. Ensure you have the required dependencies installed (e.g., numpy, pandas, scikit-learn, tensorflow).
git clone https://github.com/samsorrahman/Machine-Learning-Projects.git- Python
- Jupyter Notebooks
- Scikit-Learn
- TensorFlow
- NumPy & Pandas
- Matplotlib & Seaborn
If you have any questions, feel free to reach out:
- Email: samsorrahman20@gmail.com
Thank you for visiting my repository! Feel free to star the project if you found it helpful.