Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?
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Updated
Dec 24, 2018 - Jupyter Notebook
Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?
https://pypi.org/project/kviz/ Visualization library for keras neural networks. Contributions welcome
A collection of beautiful plots, and other data visualization stuff.
Tree based algorithm in machine learning including both theory and codes. Topics including from decision tree regression and classification to random forest tree and classification. Grid Search is also included.
📈 Interactive decision boundary visualizer
Decision Boundaries Visualization of SVDD (libsvm-3.23)
Animates the SVM Decision Boundary Hyperplane on the Iris data
A simple web app that helped students visualize the SVM algorithm according to their choice of hyperparameter setting.
Machine learning
Interactive playground for ML decision boundaries & regression surfaces (Gradio + scikit-learn + Matplotlib).
Machine learning code: linear regression and logistic regression
This is a logistic regression model for binary classification. It reads a CSV file containing input data with two attributes and a target class label, and pre-processes the data by removing unwanted columns and splitting it into training and test sets.
Python demo of logistic regression for binary and multi-class classification with decision boundary plots.
Non-parametric Gaussian kernel-density classifier supporting N-dimensional data, accuracy evaluation, and 2-D decision-boundary visualization.
Plotting decision boundaries for high-dimensional data.
Open-source machine learning visualization platform for learning algorithms from first principles. Interactive decision boundaries, real scikit-learn computation, hyperparameter tuning, and training animations.
Andrew Ng Machine Learning Course Coursera
SigmaCam: exact decision-boundary extraction for DNNs with smooth activations (Sigmoid, SiLU). IEEE IJCNN 2025 paper code.
Simple Logistic Regression on a toy Dataset in Tensorflow.
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