Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| # Page Configuration | |
| st.set_page_config( | |
| page_title="Zero to Hero in Machine Learning", | |
| page_icon="π€", | |
| layout="wide", | |
| ) | |
| # Title Section | |
| st.title("π― **Zero to Hero in Machine Learning**") | |
| st.markdown("#### *Empowering your journey into the fascinating world of Machine Learning!*") | |
| # About the App Section | |
| st.header("π‘ **About the App**") | |
| st.write(""" | |
| Welcome to **Zero to Hero in Machine Learning**, your ultimate guide to mastering the essentials of machine learning! | |
| π Whether you're a **complete beginner** or looking to **sharpen your skills**, this app has got you covered: | |
| - β Basics to advanced ML concepts | |
| - π Interactive examples and visualizations | |
| - π Hands-on datasets to practice | |
| - π§ Engaging exercises to test your understanding | |
| This app makes learning **fun and accessible** for everyone. Let's dive in! π | |
| """) | |
| # About the Author Section | |
| st.header("π¨βπ» **About the Author**") | |
| st.write(""" | |
| Hi! I'm **Kaustubh Yewale** π, an **AI Developer** passionate about making complex topics simple and easy to understand. | |
| I specialize in: | |
| - π€ **Building intelligent systems**: Spam detection, virtual assistants, and stock price predictors | |
| - π» **Programming**: Python, SQL, and data analytics tools | |
| - π **Data Science**: From EDA to model deployment | |
| With a strong foundation in Python and machine learning, I aim to make data science learning **fun and accessible for everyone**! π | |
| """) | |
| # Skills Section | |
| st.header("β¨ **Skills at a Glance**") | |
| skills = { | |
| "Programming Languages": "Python π, SQL π", | |
| "Machine Learning Frameworks": "Scikit-learn π€, TensorFlow π₯, Keras π§ ", | |
| "Data Analytics": "Pandas π, NumPy π, Power BI π", | |
| "Visualization Tools": "Matplotlib π¨, Seaborn π", | |
| "Projects": "Spam Detection π‘οΈ, Virtual Assistants ποΈ, Stock Prediction π", | |
| } | |
| for skill, details in skills.items(): | |
| st.markdown(f"**{skill}:** {details}") | |
| # LinkedIn and GitHub Section | |
| st.header("π **Connect with Me**") | |
| st.markdown( | |
| """ | |
| - [](https://www.linkedin.com/in/kaustubh-yewale-3902551b9) | |
| - [](https://github.com/Kaustubh102) | |
| """ | |
| ) | |
| # Footer Section | |
| st.markdown( | |
| """ | |
| --- | |
| π *Let's turn your Machine Learning aspirations into reality! | |
| Together, we'll go from Zero to Hero!* π | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |