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AI/ML Engineer | Python | SQL | Machine Learning | Data Analysis | Statistics
AI/ML Engineer focused on building practical solutions using Python, SQL, Machine Learning, Statistics, and Data Analysis.
- Python and SQL
- Statistics and Probability
- NumPy and Pandas
- Data Visualization with Matplotlib and Seaborn
- Machine Learning with Scikit-learn
- Jupyter Notebook
- Data Analysis and Exploratory Data Analysis
- Strengthening Machine Learning concepts through hands-on implementation
- Working with real-world datasets and data analysis
- Building practical AI/ML projects
- Improving model evaluation and problem-solving skills
π Statistics Learning Journey
A structured collection of Statistics concepts, Python implementations, visualizations, and Machine Learning applications.
To build practical and reliable AI/ML solutions through continuous learning, hands-on projects, and real-world problem solving.
About Me
Technical Skills
Current Focus
Featured Projects
Learning Journey
Contact / LinkedIn
Popular repositories
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Python mini projects showcasing game development, logic building, and practical programming using Python.
Python
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Professional Python repository showcasing fundamental programming concepts, problem-solving exercises, object-oriented programming, functions, file handling, exception handling, and practical impleβ¦
Jupyter Notebook
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Professional SQL repository showcasing MySQL queries, database schemas, CRUD operations, constraints, joins, views, and stored procedures.
Jupyter Notebook
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A practical Statistics learning journey covering statistical concepts, Python implementation, data visualization, and machine learning applications.
Jupyter Notebook
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AI/ML Engineer | Python | SQL | Machine Learning | Data Analysis | Statistics
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A hands-on learning repository covering NumPy and Pandas concepts for AI and Machine Learning, including data manipulation, analysis, missing values, performance optimization, and mini assessments.
Jupyter Notebook
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