Upload Introduction.py

pages/Introduction.py

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+
+import streamlit as st
+
+
+st.title(" Let's Explore Data Science Together🚀")
+
+
+# What is Data Science?
+st.subheader("What is Data Science? 📊")
+st.markdown(
+    """
+    Data Science is about understanding and analyzing information (called data) to make better decisions.  
+    Data can be anything – numbers, words, pictures, or even videos. For example, data could be the number of people who visit a store or the temperature recorded on different days.
+
+    Scientists use data to find patterns, make predictions, and solve problems. They gather, study, and understand data to help make decisions or discoveries.
+    
+    In simple terms, Data Science combines gathering and analyzing data to understand what's happening and help us make better choices in life or business.  
+    """
+)
+
+st.subheader("**What is Natural Intelligence and Artificial Intelligence?**")
+# Natural Intelligence (NI)
+st.subheader("What is Natural Intelligence? 🧠")
+st.markdown(
+    """
+    Natural Intelligence is how humans and animals think and learn. It’s our ability to understand things, solve problems, and make decisions using our brain.  
+
+    For example:  
+    - Humans can easily recognize objects, faces, and even emotions in people.  
+    - We can learn from our experiences and adapt to new situations.
+    """
+)
+
+# Artificial Intelligence (AI)
+st.subheader("What is Artificial Intelligence (AI)? 🤖")
+st.markdown(
+    """
+    Artificial Intelligence (AI) is when machines are designed to think and act like humans. It's a way of teaching computers to learn from data and make decisions, just like we do.
+    From Siri answering your questions to chatbots helping you shop, AI is everywhere.
+    
+    We use tools like Python to teach machines how to copy the way we think and learn. AI can do many things, like recognize images, understand speech, and even recommend things to you online. 
+    For example:  
+    - Self-driving cars 🚘
+    - Movie Recommendations suggesting your next watch show. 👀
+    """
+)
+
+# Machine Learning (ML)
+st.subheader("What is Machine Learning? 🧠")
+st.markdown(
+    """
+    Machine Learning is a part of AI. It’s a way for computers to learn from data without being programmed step-by-step. The more data the machine gets, the smarter it gets over time.  
+
+    For example: 
+    - Predicting house prices 🏡
+    - Sorting emails into spam or not 📧 
+    - A recommendation system learns from your preferences to suggest movies or products you might like.
+    """
+)
+
+# Deep Learning (DL)
+st.subheader("What is Deep Learning?")
+st.markdown(
+    """
+    Deep Learning is a type of Machine Learning that works with complex data, like images and sound. It uses something called "neural networks," which are layers of information, similar to how our brain works.
+    Lik it helps computers recognize faces in photos by looking at many different features like eyes, noses, and mouths.
+    
+    Example: 
+    - Virtual assistants like Alexa understanding your voice commands. 🎙️
+    - Image Classification💬🏚️ 
+    
+    """
+)
+
+# Generative AI (GenAI)
+st.subheader("What is Generative AI? 🎨")
+st.markdown(
+    """
+    Generative AI is a special kind of AI that can create new things. It looks at existing data, learns from it, and then creates something new. 
+
+    For example:  
+    - GPT-3 can write articles, stories, or even poems by learning from large amounts of text.
+    - AI can create realistic images, like generating faces or designing art from scratch.
+    """
+)