LFM Brain Tumor Classification 🧠🔬

• A brain tumor occurs when abnormal cells form within the brain.
• There are two main types of tumors: cancerous (malignant) tumors and benign tumors.
• All types of brain tumors may produce symptoms that vary depending on the part of the brain involved.
• These symptoms may include headaches, seizures, problems with vision, vomiting and mental changes.

Main Objective 🎯

The dataset that we will be using comes from the Brain Tumor Classification, where our primary objective is to build a deep learning model that can successfully recognize and categorize images into either a tumorous or non tumorous.

Definition 📚

The dataset that we will be using comes from the Brain Tumor Classification, where our primary objective is to build a deep learning model that can successfully recognize and categorize images into either a tumorous or non tumorous.

Methodology 📝

Transfer Learning:Transfer learning is a machine learning method where a model developed for a task is reused as the starting point for a model on a second task.

Data Augmentation 📸🔄

Modeling 🧠💻

Model Performance 📊

Conclusion 📝

• The purpose of this project was to build a CNN model that would classify if the subject has a tumor or not.
• Dataset can play vital role in getting good results.
• Techniques like data augmentation and data hallucination can be helpful.
• Different architectures can improve model accuracy. 🧠💪🔬