This is a machine learning model to predict the survival in titanic disaster.
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Updated
Nov 7, 2022 - Jupyter Notebook
Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
This is a machine learning model to predict the survival in titanic disaster.
Machine learning models for discrimination of psychrophilic proteins
This is Machine Learning Beginner level Project. In this Project We can Predict fire in forest based on some features.
Projects on Machine learning using classification and regression techniques
🤓📙Compilation of works of the master's degree in artificial intelligence
Machine Learning Using Python & Sci-Kit Learn
In this repository are covered some of the starters cases about Machine Learning.
Machine Learning for Economics (Sogang University, 2022-2)
Projects of practical machine learning and statistical learning that I did when studying in McGill University
Best practices for solving Machine Learning Multilabel Classification problems
This project aims to train a machine learning model to predict the price of a Peugeot 206 Type 2 car
Diabetes prediction using machine learning algorithms
Using patient data as a csv file, I have built machine learning models to predict heart disease. Predictions involve:
predict The percentage of cancer by using classification: Support vector machines (SVM)
DIY implementations of machine/deep learning models used on a variety of datasets.
論文『Machine Learning Phases Of Matter』の理解を目標にしたコード.
Comparison of ML algo Regression, Random Forests and Neural Netwok, on different data
Este repositorio almacena algunos algoritmos de Machine Learning con implementación usando librerías y sin librerías, mayormente usando Python. Se agregan algunos algoritmos adicionales, usando Python, Rust y otros lenguajes.
An initiative to predict heart disease earlier using various parameters input to a machine learning model trained on a dataset.