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.
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
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
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.
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Rock Paper Scissors ✊✋✌️
- 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.
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Cat and Dog Image Classifier 🐱🐶
- 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.
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Book Recommendation Engine using KNN 📚
- Description: Develop a K-Nearest Neighbors algorithm to recommend books based on user preferences and ratings from the Book-Crossings dataset.
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Linear Regression Health Costs Calculator 💰
- 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.
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Neural Network SMS Text Classifier 📱
- 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.
For any inquiries or feedback, please feel free to reach out:
- Name: Mayank Yadav
- Email: mayanky075@gmail.com
- LinkedIn: LinkedIn Profile
To get started with this repository, follow these steps:
- Clone the Repository:
git clone https://github.com/mayankyadav23/Machine-Learning-with-Python.git cd Machine-Learning-with-Python