pages/1Introduction to Machine Learning.py

import streamlit as st

st.set_page_config(
    page_title="HomePage",
    page_icon="🚀",
    layout="wide"
)

# Container for "What is Data Science?"
st.markdown("""
        <div style="text-align: left; margin-top: 20px;">
            <h2 style="color: #BB3385;">What is Data Science? 📊✨</h2></div>""", unsafe_allow_html=True)

st.write("""
**Data Science** is a field that unlocks the power of data to drive insights and predictions. By leveraging tools like **Artificial Intelligence**, **Machine Learning**, and **Data Visualization**, Data Science transforms raw data into meaningful knowledge.

Whether it’s uncovering hidden trends in business, predicting future outcomes, or solving real-world problems, Data Science bridges the gap between data and actionable insights.

In a world fueled by data, Data Science empowers us to make smarter decisions, automate processes, and innovate like never before. 🌟
""")

st.markdown("""
        <div style="text-align: left; margin-top: 20px;">
            <h4 style="color: #2a52be;">For Example:How Netflix Knows What You’ll Love🎬</h4></div>""", unsafe_allow_html=True)
    

st.write("""
    Netflix is a master of **Data Science**, using it to make your viewing experience uniquely personal. 
    By analyzing what you watch, how long you watch it, and your favorite genres, Netflix applies 
    **Machine Learning algorithms** to uncover your preferences.

    This is how it creates tailored recommendations like:
    - *"Because you watched XYZ…"*
    - *"Top picks for you."*

    Through **Data Science**, Netflix turns massive amounts of raw data into meaningful insights, 
    ensuring you spend less time searching and more time enjoying. It’s seamless, smart, and keeps you coming back for more! 🌟
    """)


st.markdown("""
        <div style="text-align: left; margin-top: 20px;">
            <h2 style="color: #BB3385;">What is Artificial Intelligence? 🤖✨</h2></div>""", unsafe_allow_html=True)

st.write("""**Artificial Intelligence(AI)** is a broad field where machines simulate natural intelligence, enabling them to demonstrate intelligent behaviors like analyzing data, recognizing patterns, solving problems, and making decisions. This also includes the capability to learn, reason, and perform tasks typically associated with human cognition, often without direct human involvement.""")


# Image
st.image(
        "https://huggingface.co/spaces/LakshmiHarika/MachineLearning/resolve/main/Images/AI_venn_diagram",
        use_container_width=True)


st.markdown("""
        <div style="text-align: left; margin-top: 20px;">
            <h4 style="color: #2a52be;">For Example:</h4></div>""", unsafe_allow_html=True)


st.write("""There was a father and his young daughter. She was so small that she couldn't even identify the difference between a dog and a cat. Her father decided to teach her by showing her pictures of dogs and cats every day. After many days, he showed her new pictures of dogs and cats, and to his joy, she successfully identified them. This was possible because of the natural intelligence given by God.""")

st.write("""Similarly, in Artificial Intelligence (AI), we human beings guide machines by feeding them data and teaching them patterns, much like the father did with his daughter. Over time, the machine learns to mimic natural intelligence to create artificial intelligence,inspired by the way we develop our own understanding.""")

st.write("""To mimic or copy natural intelligence, AI systems rely on two abilities:
- **Learning Ability**
- **Generating Ability**""")

st.markdown("""
        <div style="text-align: left; margin-top: 20px;">
            <h3 style="color: #843f5b;">Learning Ability</h3></div>""", unsafe_allow_html=True)

st.write("""
Just as the daughter learned to identify dogs and cats by observing many examples, AI systems are trained on datasets to recognize patterns and gain knowledge.

For this, we use two major tools:
1. **Machine Learning (ML)**
2. **Deep Learning (DL)**
""")

st.markdown("""
        <div style="text-align: left; margin-top: 20px;">
            <h3 style="color: #843f5b;">Generating Ability</h3></div>""", unsafe_allow_html=True)

st.write("""Once the AI has learned, it can use this knowledge to create new outputs, generate insights, or make predictions, similar to how the daughter identified new images of dogs and cats after her learning phase.

This ability is powered by tools like:
- **Generative AI**""")

st.markdown("""
        <div style="text-align: left; margin-top: 20px;">
            <h3 style="color: #e25822;">What is Machine Learning(ML)</h3></div>""", unsafe_allow_html=True)


st.write("""
**Machine Learning (ML)** is a tool that enables machines to mimic natural intelligence by providing them with the ability to learn, ultimately creating artificial intelligence.

To learn from data, **ML** relies on two key components: **data** and **algorithms**. It uses a relationship function between the data and the algorithm to identify patterns, make predictions, or derive insights.
""")

st.markdown("""
        <div style="text-align: left; margin-top: 20px;">
            <h3 style="color: #e25822;">What is Deep Learning(DL)</h3></div>""", unsafe_allow_html=True)

import streamlit as st

st.write("""
**Deep Learning (DL)** is a specialized subset of Machine Learning that uses artificial neural networks to mimic natural intelligence by providing them with the ability to learn, ultimately creating artificial intelligence.

To learn from data, **DL** relies on layers of interconnected nodes (neurons) in neural networks. It uses these layers to extract patterns, understand relationships, and make advanced predictions or decisions based on the data.
""")

st.markdown("""
        <div style="text-align: left; margin-top: 20px;">
            <h3 style="color: #e25822;">What is Generative AI(Gen AI)</h3></div>""", unsafe_allow_html=True)
            
st.write("""
**Generative AI** is a tool that enables machines to generate their own outputs based on the intelligence acquired through learning. It empowers machines to create new outputs by leveraging patterns and insights gained from data.

Using **Generative AI**, machines can produce various forms of creative outputs, including conversations, images, music, stories, videos, designs, synthetic data, and more.
""")