https://github.com/roushankhalid/required-ds-and-ml-to-research

A comprehensive guide to mastering Data Science and Machine Learning, featuring practical learning paths, research projects, and real-world applications.
https://github.com/roushankhalid/required-ds-and-ml-to-research

anaconda-environment analysis-framework data-science deep-learning deployment documentation flask machine-learning-algorithms python research-project sql statistics

Last synced: 3 months ago
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A comprehensive guide to mastering Data Science and Machine Learning, featuring practical learning paths, research projects, and real-world applications.

• Host: GitHub
• URL: https://github.com/roushankhalid/required-ds-and-ml-to-research
• Owner: RoushanKhalid
• Created: 2024-09-30T20:25:23.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-17T04:36:51.000Z (9 months ago)
• Last Synced: 2025-01-17T05:26:51.780Z (9 months ago)
• Topics: anaconda-environment, analysis-framework, data-science, deep-learning, deployment, documentation, flask, machine-learning-algorithms, python, research-project, sql, statistics
• Language: Jupyter Notebook
• Homepage:
• Size: 43.8 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# 📊 Data Science, Machine Learning & Research Guide

Welcome to the **Data Science, Machine Learning, and Research Guide** repository! This repository is designed to help you master the core concepts and skills in Data Science (DS) and Machine Learning (ML) while diving into AI/ML-based research projects. Whether you're a beginner or looking to advance your knowledge, this resource provides a comprehensive roadmap for practical learning and contributing to cutting-edge research.

---

## ✨ Features

### 🔍 **Core Concepts**

- **Python for DS & ML**: Learn essential Python libraries like NumPy, Pandas, Matplotlib, and Seaborn.

- **SQL for Data Analysis**: Master SQL commands to manipulate and analyze datasets.

### 🧹 **Data Cleaning & Preprocessing**

- Handle missing data, outliers, and inconsistencies.

- Transform and scale features to prepare datasets for modeling.

### 📊 **Data Analysis & Visualization**

- Discover insights with data visualization tools.

- Analyze trends and patterns with real-world datasets.

### ⚙️ **Feature Engineering**

- Select, create, and transform features to improve model performance.

### 📈 **Basic Statistics for DS**

- Understand key statistical concepts such as:

  - Mean, Median, Mode

  - Standard Deviation

  - Probability Distributions

  - Hypothesis Testing

### 🤖 **Model Building**

- Implement algorithms like regression, classification, clustering, and more.

- Tune hyperparameters for optimal results.

### 🚀 **Model Deployment**

- Deploy ML models using Flask or other web frameworks.

- Create interactive web applications for real-world use.

---

## 🔬 **Research Integration**

This repository also aims to foster **AI & ML-based research**, with a focus on:

- **Exploratory Research**: Generate hypotheses and validate them using real-world datasets.

- **Advanced Techniques**: Apply deep learning models, transfer learning, and time-series analysis.

- **Practical Applications**: Develop innovative solutions in fields like robotics, healthcare, finance, and cybersecurity.

- **Literature Reviews**: Summarize and analyze academic papers to gain insights into state-of-the-art methods.

- **Collaboration**: Engage with the community by contributing to or reviewing open-source projects.

---

## 🛣️ Roadmap

Here is the roadmap I follow for structured learning and research:  

[👉 AI & ML Learning Roadmap](https://docs.google.com/document/d/19ra-1QJEQRY4giwjMDTNCmXQSaUOBqJHvPm9qrTm5kU/edit?usp=sharing)

---

## 🎯 **Contribute**

You are welcome to contribute your research ideas, code, or insights! Here’s how you can help:

1. Fork this repository and create your feature branch.

2. Submit pull requests with detailed descriptions.

3. Collaborate on open issues or suggest new ones.

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Let’s innovate together and push the boundaries of what AI and ML can achieve! 🚀