I'm an aspiring AI/ML Engineer focused on Python, data analysis, machine learning, and problem solving. I'm currently building my foundations through hands-on projects and consistent DSA practice, with the goal of developing practical AI/ML solutions.
- 🤖 Passionate about Artificial Intelligence & Machine Learning
- 🐍 Currently focusing on Python Basics and Data Structures & Algorithms
- 📊 Learning Data Science,MlOps
- 🌍 Interested in contributing to Open Source
- 🚀 Working towards building real-world AI/ML projects
- 🧩 Hobbies Swimming,Chess,Reading
- 💼 Goal: 🎯 Seeking opportunities to learn and contribute as an AI/ML intern
| 🧠 Skills | 📚 Topics |
|---|---|
| 🧹 Data Cleaning & Preprocessing | Handling missing values, data transformation |
| 🔍 Exploratory Data Analysis | Understanding patterns, trends & distributions |
| 🔄 Data Manipulation | Filtering, grouping, merging & transforming data |
| 📊 Data Visualization | Charts, plots & visual data analysis |
| ⚙️ Feature Engineering | Feature selection & feature transformation |
| 🤖 Machine Learning | Building & applying ML models |
| 📈 Model Training & Evaluation | Training, testing & performance evaluation |
| 🧠 Learning Types | Supervised & Unsupervised Learning |
| Library | Purpose |
|---|---|
| NumPy | Numerical computing & array operations |
| Pandas | Data manipulation & analysis |
| Matplotlib | Data visualization |
| Seaborn | Statistical data visualization |
| Project | Description | Focus |
|---|---|---|
| 🐍 Python Projects | A collection of 14 independently built Python projects created to strengthen programming fundamentals, logical thinking, and problem-solving through hands-on practice. | Python · Problem Solving · Programming Fundamentals |
| 🧪 PythonLabs | An ongoing collection of practical Python projects, including an Expense Tracker, Library Management System, and database-related applications as I progress toward more structured Python development. | Python · OOP · File Handling · SQL |
| 📊 Data Analysis Project | Hands-on work applying NumPy and Pandas to real datasets, focusing on data cleaning, manipulation, exploratory analysis, visualization, and extracting meaningful insights. | NumPy · Pandas · Data Analysis |
Building consistently, one project at a time.
I'm continuously strengthening my foundations in Machine Learning, Data Analysis, Deep Learning, and DSA while applying what I learn through practical projects.
| 🚀 Area | 📖 Currently Learning |
|---|---|
| 🤖 Machine Learning | Supervised Learning · Unsupervised Learning · Data Preprocessing · Feature Engineering · Model Evaluation · Regression · Classification · Clustering |
| 📊 Data Analysis | NumPy · Pandas · Matplotlib · Seaborn · EDA · Data Cleaning · Data Visualization |
| 🧩 Data Structures & Algorithms | Arrays · Strings · Linked Lists · Stacks & Queues · Trees · Searching · Sorting · Algorithms · Problem Solving |
| 🧠 Deep Learning | Neural Networks · Deep Learning Fundamentals · Model Training · Model Evaluation |
Building on a solid foundation in DSA and problem solving, while progressing toward more advanced concepts through consistent practice.
| 🎯 Focus Area | 📚 Current Progress |
|---|---|
| 🧱 Core Data Structures | Arrays · Strings · Linked Lists · Stacks & Queues · Trees |
| ⚙️ Algorithms | Searching · Sorting · Recursion · Basic Algorithmic Techniques |
| 🧠 Problem Solving | Pattern Recognition · Logical Thinking · Time & Space Complexity |
| 💻 Practice | LeetCode · Algorithmic Problem Solving · Consistent Practice |
| 🚀 Next Step | Progressing toward more challenging DSA problems and strengthening problem-solving skills |
Build the fundamentals → Solve consistently → Tackle harder problems → Improve
|
Keep pushing forward. Failure is part of the process. |
Learn → Build → Contribute → Improve → Repeat
🤝 Connect With Me
