about_me:
role: Data Science & AI Enthusiast
summary: >
Passionate about working with data to extract insights and build
practical, real-world AI solutions. Strong interest in machine learning,
deep learning, and analytical problem solving.
interests:
- Machine Learning
- Deep Learning
- Neural Networks
- Data Analytics
- AI-driven Applications
current_focus:
- Building end-to-end machine learning projects
- Improving model performance and interpretability
- Writing clean, reproducible, and well-documented code
career_goal: >
To work as a Data Scientist or AI Engineer and contribute to
impactful, data-driven products.
learning_mindset: >
Continuous learner focused on strengthening fundamentals through
hands-on projects and experimentation.
{
"programming_languages": [
"Python","Java","C","SQL"
],
"data_science_and_ml": [
"Pandas","NumPy","Matplotlib","Plotly",
"Scikit-learn","TensorFlow","PyTorch",
"Keras","SciPy"
],
"databases": [
"PostgreSQL","MySQL","MongoDB",
],
"data_visualization_tools": [
"Power BI","Tableau","Looker Studio"
],
"cloud_and_devops": [
"AWS","Microsoft Azure",
"Docker",
],
"tools_and_others": [
"Git",
"GitHub",
"Jupyter Notebook",
"Visual Studio Code",
"Anaconda"
]
}-
pip-tools (Jazzband)
Improved CI workflow naming for better clarity
🔗 jazzband/pip-tools#2300 -
scikit-learn
Clarified the behaviour of the 'verbose' parameter in GridSearchCV and RandomizedSearchCV to improve documentation clarity.
🔗 scikit-learn/scikit-learn#32968