Breast Cancer Prediction using Neural Network | Deep Learning Project - Python & TensorFlow / Keras

Build a neural network that classifies breast tumors as malignant or benign using TensorFlow and Keras. This is a complete, end-to-end deep learning project — we load the data, explore it, split it, scale the features, build the network, train it, and then properly evaluate it with a confusion matrix, precision, recall, and ROC-AUC. We finish at around 97% accuracy on unseen data. This is a full lesson from my Deep Learning Bootcamp, shared free. No GPU required — everything runs in Google Colab. 🔗 LINKS Deep Learning Bootcamp (Udemy) → https://www.udemy.com/course/deep-lea... Notebook (Colab) → https://drive.google.com/file/d/1Qxs7... Dataset → https://drive.google.com/file/d/1GyXx... 📌 WHAT YOU'LL LEARN How to structure a binary classification project end to end Why you need three splits — train, validation and test — and not just two How to scale features correctly without leaking test data into training Sigmoid activation and binary cross-entropy, and why this pairing works Early stopping and how to read learning curves for overfitting How to evaluate a classifier beyond accuracy — confusion matrix, precision, recall, F1, ROC and AUC Saving both your model AND your scaler for deployment 🧰 TOOLS USED Python · TensorFlow · Keras · scikit-learn · pandas · NumPy · Matplotlib · Google Colab 📚 ABOUT THE COURSE The Deep Learning Bootcamp covers the math foundations, neural networks from scratch, PyTorch and TensorFlow, CNNs and transfer learning, RNNs, Transformers and NLP, model deployment with FastAPI, Streamlit and AWS EC2, and two full capstone projects. Course link → https://www.udemy.com/course/deep-lea... 🔔 Subscribe for more deep learning projects. #DeepLearning #TensorFlow #Keras #MachineLearning #Python #DataScience