Machine Learning Repository

Welcome to the Machine Learning Repository! This repository is a collection of code and projects related to machine learning. Whether you're a student learning about machine learning in a class, working on machine-learning projects, or pursuing self-learning, you'll find a variety of resources here to help you understand and implement machine learning concepts.

Table of Contents

1. Class Code 1.1 Codes 1.2 CSV Files
2. Machine Learning Projects
3. Self-Learning Codes for Machine Learning
4. Getting Started

Class Code

This section contains code snippets, notebooks, and projects related to machine learning that are specifically designed for a classroom setting. If you are currently taking a machine learning course, you may find materials here that complement your class lectures and assignments.

Codes

• ML_Class_Code_1: Linear Regression

  • Description: Implementation of linear regression for predicting a target variable based on one or more independent variables.
  • Files: linear_regression_code.py

• ML_Class_Code_2: Decision Trees

  • Description: Introduction to decision trees and their implementation for classification tasks.
  • Files: decision_trees_code.py

CSV Files

• ML_Class_Data_1: Linear Regression Dataset

  • Description: Dataset used in ML_Class_Code_1 for linear regression.
  • Files: linear_regression_data.csv

• ML_Class_Data_2: Decision Trees Dataset

  • Description: Dataset used in ML_Class_Code_2 for decision trees.
  • Files: decision_trees_data.csv

...

Machine Learning Projects

This section contains full-fledged machine learning projects that you can explore and learn from.

• ML_Project_1: Image Classification with CNN

  • Description: Building a convolutional neural network (CNN) for image classification using a popular deep learning framework.
  • Files: image_classification_cnn.ipynb, images/

• ML_Project_2: Natural Language Processing (NLP) Application

  • Description: Developing an NLP application for sentiment analysis.
  • Files: nlp_application_code.py, dataset.txt

...

Self-Learning Codes for Machine Learning

This section is dedicated to individual code snippets and projects suitable for self-learners interested in exploring machine learning concepts on their own.

• SelfLearn_Code_1: Feature Scaling Techniques

  • Description: Implementation of various feature scaling techniques in machine learning.
  • Files: feature_scaling_code.py

• SelfLearn_Code_2: Principal Component Analysis (PCA)

  • Description: Introduction to PCA and its implementation for dimensionality reduction.
  • Files: pca_code.py

...

Getting Started

To get started with the code and projects in this repository, follow these steps:

1. Clone the repository to your local machine: git clone https://github.com/Mahesh7741/machine-learning-repo.git

2. Navigate to the desired section or project folder:

3. Open the notebook or code file using your preferred development environment.

4. Run the code and explore the project!

Happy learning and coding! 🚀