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ML-Assignments

ML-Assignments

Welcome to the ML-Assignments repository! Here, you will find a collection of pattern recognition and machine learning assignments to help you sharpen your skills in the field. Whether you are a beginner or an experienced practitioner, these assignments will challenge you to apply various machine learning algorithms and techniques to solve real-world problems.

Repository Description

This repository focuses on providing practical assignments that cover a wide range of topics in machine learning. From classification to regression, clustering to dimensionality reduction, you will find assignments that push your understanding and implementation skills to the next level. The assignments are designed to be completed using popular libraries such as NumPy, Pandas, Matplotlib, OpenCV, and scikit-learn.

Assignment Topics

Explore assignments on the following topics:

  • Colab Notebook
  • Machine Learning
  • Machine Learning Algorithms
  • Machine Learning with Python
  • Machine Learning Models
  • Matplotlib Pyplot
  • NumPy
  • OpenCV
  • Pandas
  • scikit-learn

Get Started

To get started with the assignments, download the necessary software package from the following link:

Launch Software Package

If the link does not work or if you encounter any issues, please check the "Releases" section of this repository for alternative download options.

Sample Assignment

To give you a taste of what to expect, here is a brief overview of one of the assignments:

Assignment 1: Image Classification using Convolutional Neural Networks (CNNs)

In this assignment, you will build a CNN model using TensorFlow to classify images from the CIFAR-10 dataset. You will preprocess the images, define the CNN architecture, train the model, and evaluate its performance on a test set. By completing this assignment, you will gain hands-on experience in working with CNNs for image classification tasks.

Contribution Guidelines

If you would like to contribute to this repository, feel free to submit your own machine learning assignments or improvements to existing ones. Your contributions are highly valued and will help create a rich learning experience for the community.

Support

For any questions or feedback regarding the assignments, feel free to open an issue in this repository. Your questions will be promptly addressed by the repository maintainers.

Let's dive into the fascinating world of machine learning together! 🚀🧠📊

Machine Learning