Machine_learning / pages /1. Intro to Data Science.py
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import streamlit as st
# Title
st.title("Introduction to Data Science πŸ“Š")
# What is Data Science
st.subheader(":rainbow[What is Data Science?] πŸ”")
multi = """Data Science is a field that helps us understand and use data to solve problems.
It combines things like math, coding, and expert knowledge to look at data and find useful patterns or trends.
The process involves gathering data, cleaning it up, analyzing it, and turning it into easy-to-understand visuals.
With data science, we can predict future events, solve tough problems, and make decisions based on facts, all in a fast-changing world. """
st.markdown(multi)
# Natural Intelligence
st.subheader(":rainbow[Natural Intelligence] 🧠")
st.write("Natural Intelligence is how humans think, learn, and solve problems using their brains and senses. "
"It's what helps humans adapt, make decisions, and figure out things in real life. πŸ€”")
st.write(":blue[Example:] 🌳")
st.write("* Humans are good at identifying animals and plants, recognizing faces, and making decisions based on experience.")
# Artificial Intelligence
st.subheader(":rainbow[Artificial Intelligence] πŸ€–")
st.image("https://media.gettyimages.com/id/1501388344/vector/artificial-intelligence-concept.jpg?s=612x612&w=0&k=20&c=jD5Y3dTf9CihE1KiLrBZAwyjx-E44xyrpH64I5lAMDo=")
multi = """Artificial Intelligence refers to the simulation of human intelligence in machines designed
to think, learn, and make decisions like humans. We are guiding machines to mimic natural intelligence to create AI systems that can perform tasks without human intervention."""
st.markdown(multi)
st.write(":blue[Example:] πŸš—")
st.write("* Tesla's self-driving cars: AI is used in self-driving cars to process data from cameras, sensors, and maps to navigate and make decisions, such as stopping at traffic lights or avoiding obstacles.")
# Machine Learning (ML)
st.subheader(":rainbow[Machine Learning (ML)] πŸ€–πŸ“ˆ")
st.write("Machine Learning (ML) is a branch of AI where machines learn from data and get smarter over time, "
"without the need for explicit programming. ML mimics human learning ability using statistical methods to make predictions or decisions.")
st.write(":blue[Example:] 🧠")
multi = """
* Face unlock on your phone.
* Virtual assistants like Alexa understanding your voice commands.
* Text-to-image generation tools.
"""
st.write(multi)
# Generative AI
st.subheader(":rainbow[Generative AI] πŸŽ¨πŸ€–")
st.write("Generative AI lets machines create! From writing essays to generating art, it’s AI at its creative best.")
st.write(":blue[Example:] ✍️")
st.write("* OpenAI's GPT-3: A powerful generative model that can generate coherent and contextually appropriate text, from answering questions to writing essays, stories, or even poetry.")
# Closing Remarks
st.subheader(":rainbow[Conclusion] πŸ“")
st.write("""
- **Data Science** is the field where data is used to solve real-world problems using techniques from statistics, coding, and expert knowledge.
- **Natural Intelligence** is the human ability to solve problems and learn from experiences.
- **Artificial Intelligence** is a simulation of human intelligence in machines, designed to make decisions like humans.
- **Machine Learning** allows machines to learn from data without being explicitly programmed, and it mimics human learning.
- **Generative AI** is a creative branch of AI, where machines generate new content, like text, images, or even music!
""")