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This repository contains a collection of fundamental topics and techniques in machine learning. It aims to provide a comprehensive understanding of various aspects of machine learning through simplified notebooks. Each topic is covered in a separate notebook, allowing for easy exploration and learning.
This notebook consists of the notebook file that consists of a supervised learning model built to classify the nature of the breast cancer cells based on the features.
This repository contains a Jupyter Notebook exploring the adult income dataset. The notebook performs Exploratory Data Analysis (EDA), including visualizations with charts and graphs. Additionally, it implements various classification models to predict income and analyzes their accuracy.
👩💻This repository contains implementations of various machine learning algorithms, along with example datasets and Jupyter Notebook files for demonstration.
This is my Hamoye Stage C tag-along project. The notebook focuses on applying Machine Learning Classification models and Measuring Classification Performance.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow