https://github.com/mayankyadav23/machine-learning-with-python

🚀 A collection of machine learning projects using TensorFlow and Python, showcasing practical applications in prediction 🤖 and classification 📊. Dive in to explore! 🐍✨
https://github.com/mayankyadav23/machine-learning-with-python

freecodecamp machine-learning predictive-modeling python tensorflow

Last synced: 2 months ago
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🚀 A collection of machine learning projects using TensorFlow and Python, showcasing practical applications in prediction 🤖 and classification 📊. Dive in to explore! 🐍✨

• Host: GitHub
• URL: https://github.com/mayankyadav23/machine-learning-with-python
• Owner: mayankyadav23
• License: mit
• Created: 2024-11-03T05:06:10.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-11-05T11:57:37.000Z (over 1 year ago)
• Last Synced: 2025-02-27T17:11:45.617Z (over 1 year ago)
• Topics: freecodecamp, machine-learning, predictive-modeling, python, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 89.3 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Machine Learning with Python 🤖📊

## Overview

Machine learning has numerous practical applications that can enhance your projects or career. This repository contains materials and projects from the **Machine Learning with Python Certification** ***by Free Code Camp***, which you have successfully completed. In this course, you'll learn to build neural networks using the TensorFlow framework and explore advanced techniques like natural language processing and reinforcement learning.

## Certification

![Screenshot 2024-11-05 172113](https://github.com/user-attachments/assets/578ccf98-fbf5-4c87-9715-a251b774562e)

## Course Content

### TensorFlow

TensorFlow is an open-source framework that simplifies the process of machine learning and neural networking. The course created by **Tim Ruscica** (also known as “Tech With Tim”) covers the powerful capabilities of TensorFlow. 

- Comprehensive introduction to TensorFlow

- Hands-on experience building neural networks

### How Neural Networks Work

Neural networks are at the core of modern artificial intelligence. This course, led by **Brandon Rohrer**, demystifies neural networks, making them accessible to beginners. 

- Deep dive into:

  - How Deep Neural Networks Work

  - Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM)

  - Deep Learning fundamentals

  - How Convolutional Neural Networks work

## Machine Learning Projects

The certification includes several hands-on projects designed to solidify your understanding of machine learning concepts. By completing these projects, you demonstrate foundational knowledge in machine learning, qualifying for the **Machine Learning with Python certification**.

### Projects List

1. **[Rock Paper Scissors](https://github.com/mayankyadav23/Machine-Learning-with-Python/tree/main/Rock%20Paper%20Scissors)** ✊✋✌️

   - **Description**: Build a model to play the game Rock Paper Scissors against users. Implement a strategy that allows the model to learn from previous moves.

2. **[Cat and Dog Image Classifier](https://github.com/mayankyadav23/Machine-Learning-with-Python/tree/main/Cat%20and%20Dog%20Image%20Classifier)** 🐱🐶

   - **Description**: Create a classifier that distinguishes between images of cats and dogs using convolutional neural networks. Train the model on a dataset of labeled images.

3. **[Book Recommendation Engine using KNN](https://github.com/mayankyadav23/Machine-Learning-with-Python/tree/main/Book%20Recommendation%20Engine%20using%20KNN)** 📚

   - **Description**: Develop a K-Nearest Neighbors algorithm to recommend books based on user preferences and ratings from the Book-Crossings dataset.

4. **[Linear Regression Health Costs Calculator](https://github.com/mayankyadav23/Machine-Learning-with-Python/tree/main/Linear%20Regression%20Health%20Costs%20Calculator)** 💰

   - **Description**: Predict healthcare costs using linear regression on provided datasets. Analyze factors affecting health costs and implement a model to forecast expenses based on user data.

5. **[Neural Network SMS Text Classifier](https://github.com/mayankyadav23/Machine-Learning-with-Python/tree/main/Neural%20Network%20SMS%20Text%20Classifier)** 📱

   - **Description**: Classify SMS messages as either "ham" or "spam" using a neural network. Train the model on the SMS Spam Collection dataset to accurately predict message classifications.

## Contact Information

For any inquiries or feedback, please feel free to reach out:

- **Name**: Mayank Yadav

- **Email**: [mayanky075@gmail.com](mailto:mayanky075@gmail.com)

- **LinkedIn**: [LinkedIn Profile](https://www.linkedin.com/in/mayankyadv/)

## Getting Started

To get started with this repository, follow these steps:

1. **Clone the Repository**:

   ```bash

   git clone https://github.com/mayankyadav23/Machine-Learning-with-Python.git

   cd Machine-Learning-with-Python