# Health-Prediction-Device Developing and deploying ML model on esp32 which takes heart rate, body temperature and blood cell count as SpO2 and predicts the health condition as Normal, Sirius and dischargeable. # **Introduction to Machine Learning with Jupyter Notebooks** Welcome to the world of Machine Learning. This instructional materials will guide you to learn machine learning using Jupyter Notebook. ## **Getting Started** ### **1. Setting Up Your Environment** Before we go deep into machine learning, you'll need to set up your environment. follow these steps to set up your environment. **Install Jupyter Notebook**: Install the classic Jupyter Notebook by writting the below command in your terminal: `pip install notebook` ### **2. Launching Jupyter Notebook** To run the notebook: `jupyter notebook` or if this doesnt work, write this insteade. `python -m notebook` ## **Basics of Machain Learning (ML)** ### **What is Machine Learning?** It is a subset of Artificial Inteligence (AI). It focuses on making a model capable of learning from data to make predictions or decisions. ### **Types of Machaine Learning:** 1. *Supervised Learning*: Learning from labeled data (e.g., classification, regression). 2. *Unsupervised Learning*: Finding patterns in unlabeled data (e.g., clustering, dimensionality reduction). 3. *Reinforcement Learning*: Learning through rewards and punishments. ## **Building your first ML Model** **Task**: Predicting Patient Health using TensorFlow and Jupyter Notebook. **Objective**: Develop instructional materials for students to learn machine learning using Jupyter Notebook and other ML tools.The aim is to accurately predict patient health conditions(normal,serious,dischargeable) based on temperature, pulse, and blood cell counts. **Tools and Technologies**: **1**. Jupyter Notebook: For data preprocessing, model development, and training. **2**. Programming Language: Python - Widely used for its simplicity, extensive libraries, and ecosystem support. ## Developed by Harsh Raj Contacts : - [Email](mailto:developerharshraj@gmail.com) - [LinkedIn](https://in.linkedin.com/in/harsh-raj-416a0b27b) - [GitHub](https://github.com/HarshRajTiwary) ## Happy Learning