import streamlit as st

# Set the title and header for the application
st.title('Welcome to the NLP Application!')

# NLP Introduction with Emojis
st.header('🌍 Introduction to Natural Language Processing (NLP)')

st.markdown("""
**Natural Language Processing (NLP)** is a field at the intersection of **Artificial Intelligence** and **Linguistics**. It enables machines to understand, interpret, and generate human language. From **speech recognition** to **text summarization** and **machine translation**, NLP is a game changer in technology. 🤖

### Key NLP Tasks 🔑:
- **Text Classification**: Assigning predefined labels to text (e.g., spam detection).
- **Named Entity Recognition (NER)**: Identifying entities like names, dates, locations, etc.
- **Sentiment Analysis**: Determining the sentiment (positive, negative, neutral) of text.
- **Part-of-Speech (POS) Tagging**: Identifying the grammatical components (e.g., noun, verb).
- **Machine Translation**: Translating text from one language to another.
- **Text Generation**: Creating meaningful text based on input (like this application!).

### Why is NLP Important? 💡
With a massive amount of unstructured textual data available online, **NLP** helps in extracting insights, automating tasks, and providing more personalized services. From chatbots to recommendation systems and search engines, NLP is reshaping how we interact with machines. 🌐

### Our Application 🌟
In this interactive application, we leverage state-of-the-art models from **Hugging Face** to perform various NLP tasks. Whether you're new to NLP or looking to explore advanced techniques, you're in the right place! Let's dive in! 🚀
""")

# Separator
st.markdown("---")

# About the Creator Section
st.write("## 👤 About the Creator")
st.markdown("""
**Hi there! 👋 I'm Mende Jagadeesh**, a passionate **AI enthusiast** and **Data Science professional**.  
With a background in **Machine Learning** and **Big Data Technologies**, I specialize in:  
""")

# Skills Section in Columns
skills_col1, skills_col2 = st.columns(2)

with skills_col1:
    st.write("### 🛠️ Skills")
    st.write("""
    - **Programming**: Python, R, SQL  
    - **Data Visualization**: Tableau, Power BI, Matplotlib  
    - **Machine Learning**: Scikit-Learn  
    """)

with skills_col2:
    st.write("### 📚 Experience & Interests")
    st.write("""
    - **Data Science & Analytics**: Building predictive models and analyzing complex datasets.  
    - **Deep Learning**: Exploring cutting-edge models like transformers and neural networks.  
    - **AI Applications**: Solving real-world problems using Artificial Intelligence and Machine Learning.
    """)

# Social Links with Buttons
st.write("### 🌐 Connect with Me")
col1, col2, col3, col4 = st.columns(4)

with col1:
    st.button("LinkedIn", on_click=lambda: st.write("You can check out my LinkedIn [here](https://www.linkedin.com/in/mende-jagadeesh-02922323a/)"))
with col2:
    st.button("GitHub", on_click=lambda: st.write("You can explore my GitHub [here](https://github.com/Jagadeesh2411)"))
with col3:
    st.button("Email Me", on_click=lambda: st.write("You can reach me at [jagadeesh.mende2401@gmail.com](mailto:jagadeesh.mende2401@gmail.com)"))
with col4:
    st.write("📞 **Contact Number**: 7032440692")

# Footer Section
st.markdown("---")
st.markdown("""
<center>
    <p style='font-size:14px; color:#888;'> © 2024 AI & Data Science Hub. All Rights Reserved. </p>
</center>
""", unsafe_allow_html=True)