https://github.com/kumartusha/machine_learning_fundamentals

🤖 Machine Learning Journey 🚀 A repository showcasing my learning journey in Machine Learning with hands-on projects, algorithms, and practice notebooks.
https://github.com/kumartusha/machine_learning_fundamentals

matplotlib numpy pandas python3 scikit-learn seaborn sql sqlite

Last synced: 9 days ago
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🤖 Machine Learning Journey 🚀 A repository showcasing my learning journey in Machine Learning with hands-on projects, algorithms, and practice notebooks.

• Host: GitHub
• URL: https://github.com/kumartusha/machine_learning_fundamentals
• Owner: kumartusha
• Created: 2024-12-07T05:10:54.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2025-01-25T07:13:52.000Z (17 days ago)
• Last Synced: 2025-01-25T08:18:37.036Z (17 days ago)
• Topics: matplotlib, numpy, pandas, python3, scikit-learn, seaborn, sql, sqlite
• Language: Jupyter Notebook
• Homepage:
• Size: 60.6 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# 🌟 **Machine Learning Algorithms Repository **🚀

Welcome to the **Machine Learning Algorithms** repository! This repository contains several projects, data processing workflows, and fundamental machine learning techniques. 

## 📁 **Repository Structure**

Here’s an overview of the structure of this repository:

- `001_Data_Cleaning/` : Data cleaning techniques

- `002_Encoding/` : Data encoding methods

- `003_Outliers/` : Handling and removing outliers

- `004_Feature_Scaling_Standardization/` : Feature scaling and standardization

- `005_Handling_Duplicate_Data/` : Methods for handling duplicate data

- `006_Replace_And_Data_Type_Change/` : Replacing and changing data types

- `007_Function_Transformation/` : Mathematical transformations

- `008_Feature_Scaling_Technique/` : Advanced feature scaling techniques

- `009_Train_and_Test_Split_Dataset/` : Splitting datasets for training and testing

- `010_Supervised_machine_learning/` : Supervised learning algorithms

- `01_Datasets/` : Datasets used in the projects

- `ML_Projects/` : Machine learning project implementations

- `1_Activities/Oodles_Technology/` : Activities related to Oodles Technology

- `Machine_Learning_Workshop.pdf` : A workshop document on Machine Learning

- `Machine_Learning_Interview_Questions.txt` : Common interview questions for ML

- `Matplotlib_charts.pdf` : Visualization using Matplotlib

---

## 📝** Table of Contents**

- [Project Overview](#-project-overview)

- [Setup & Installation](#-setup--installation)

- [Contributing](#-contributing)

- [Resources](#-resources)

- [Related Projects](#-related-projects)

- [License](#-license)

- [Contact](#-contact)

---

## 📊 Project Overview

This repository provides implementations of various **Machine Learning** algorithms and data preprocessing techniques. The goal is to help developers and students understand the basics of ML and enhance their problem-solving skills.

### 🧑‍💻 **Features**

- Data Cleaning and Preprocessing techniques

- Feature Scaling and Transformation

- Machine Learning Algorithm Implementations (Supervised Learning)

- Project Datasets and Hands-on Activities

- Interview Preparation for Machine Learning Roles

---

## ⚙️ **Setup & Installation**

To get started with this repository, follow the instructions below:

### **Prerequisites**

1. **Python 3.6+**: Ensure Python is installed on your system.

2. **Pip**: You will need to install Python dependencies.

### Installation

Clone this repository:



git clone https://github.com/kumartusha/machine-learning-algorithms.git


cd machine-learning-algorithms

pip install -r requirements.txt



### 💡 **Contributing**

Contributions are always welcome! Here’s how you can contribute:

Fork the repository

Create a new branch (git checkout -b feature-xyz)

Commit your changes (git commit -am 'Add new feature')

Push to the branch (git push origin feature-xyz)

Open a pull request

### 🛠️ **Resources**

Here are some helpful links and resources for further learning:

📖 Machine Learning Course - Coursera

🎥 Python for Data Science - YouTube

💬 Machine Learning Community - StackOverflow

📚 Scikit-learn Documentation

📄 Data Science Resources - Kaggle

### 📧 **Contact**

If you have any questions or would like to collaborate, feel free to reach out to me:

✉️ Email: [email protected]

🌐 LinkedIn: https://www.linkedin.com/in/tushar-kumar-670986226/

🐦 Twitter: @kumartusha