Machine Learning Projects Repository

👋 Welcome to my Machine Learning Projects repository! This repository contains a collection of machine learning projects and practice notebooks that I've coded during my learning journey. The projects are implemented using popular libraries such as Scikit-learn and TensorFlow, along with fundamental libraries like Pandas, NumPy, and Matplotlib.

📂 Repository Structure

The repository is organized as follows:

📦 machine-learning-projects-repo
 ┣ 📂 scikit-learn
 ┃ ┣ 📂 classification
 ┃ ┗ 📂 regression
 ┗ 📂 tensorflow
   ┣ 📂 classification
   ┗ 📂 regression
   ┗ 📂 tarnsfer_learning

Within each section, the projects are further divided based on their type: classification and regression and also on the basis of the concepts like Feature Extraction etc. This structure helps you easily navigate through the repository and find the projects of interest to you.

🚀 Scikit-learn Projects

Classification

This section is empty for now.

Regression

🌟 Project 1: Bulldozer price prediction

📝 Description: The common regression project where bulldozer prices are predicted using scikit-learn.

🚀 TensorFlow Projects

Introduction:

📝 Description: This contains an introductory notebook to deep learning and tensorflow and a small project at the end of notebook.

Classification

🌟 Project 1: Computer Vision

📝 Description: This contains a notebook on computer vision. First introduction and then a project.

🌟 Project 2: Dog Vision

📝 Description: A very common classification of dogs into their breeds.

🌟 Project 3: Fashion Mnist

📝 Description: I have worked onfashion_mnist dataset and created a deep learning model for it.

🌟 Project 4: Excercise

📝 Description: Contains a practice notebook where I have practiced on a classification dataset.

Regression

🌟 Project 1: Insurance

📝 Description: Contains a notebook where I have worked on the kaggles's insurance dataset and developed a model for it.

🌟 Project 2: Exercise

📝 Description: Contains a practice notebook where I have developed a model for california_housing dataset

📃 License

This repository is licensed under the MIT License. See the LICENSE file for more information.

Transfer Learning

📝 Description: Contains my practice notebooks in parts.

🌟 Part 1: Feature Extraction:

📝 Description: Contains a notebook on transfer_learning's concept Feature Extraction. Exercise where i have tried a model on food and have tried ResNet_152 on my custom dataset.

Certificates🥇:

Tensorflow 🚀

Scikit-Learn 💻:

📧 Contact

If you have any questions, suggestions, or feedback, feel free to reach out to me at [email protected]. I would be happy to connect with you!

Happy learning and coding! 🚀✨