import streamlit as st import pandas as pd st.markdown(""" """, unsafe_allow_html=True) # Main Heading st.markdown('

Introduction to Data Science and Artificial Intelligence

', unsafe_allow_html=True) st.markdown("
", unsafe_allow_html=True) # Section: AI st.markdown('

What is Artificial Intelligence (AI)?

', unsafe_allow_html=True) st.write(""" Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn, and make decisions like humans. In simple terms, when machines mimic/copy natural intelligence i.e.(performing day-to-day tasks). It includes two main capabilities: - **Learning Ability** (achieved using Machine Learning (ML) and Deep Learning (DL)) - **Generating Ability** (achieved using Generative AI) """) # Section: Generative AI st.markdown('

What is Generative AI?

', unsafe_allow_html=True) st.write(""" Generative AI is a tool which is used to mimic/copy the generating ability and provide this ability to machines. It is a type of artificial intelligence that creates new contents like text, images, music, or videos, by learning patterns from existing data. """) # Section: Data Science st.markdown('

What is Data Science?

', unsafe_allow_html=True) st.write(""" Data Science is a field that combines statistics, mathematics, and computer science to extract insights from data. It involves techniques and algorithms, including Machine Learning and Deep Learning, to work with structured, unstructured, and semi-structured data. """) # Section: Machine Learning st.markdown('

Machine Learning

', unsafe_allow_html=True) st.write(""" Machine Learning uses statistical concepts to give machines the ability to learn from data.It is a tool used to mimic/copy the learning ability The relationship between input and output can be expressed as a function: """) st.latex(r"f(x_i) = y_i") st.markdown(""" For machines to learn this function, they need two things: - **Data** (data contains x and y where x are feature variables and y is class variable) - **Algorithms** (used to capture the relationships between x and y) NOTE: The data given to the machine learning model should be **structured**; if not, then it needs to be converted to a structured format. Machine Learning can be categorized into: 1. Supervised Learning 2. Unsupervised Learning 3. Semi-Supervised Learning """, unsafe_allow_html=True) # Section: Deep Learning st.markdown('

Deep Learning

', unsafe_allow_html=True) st.markdown(""" Deep Learning is a tool which is used to mimic/copy the learning ability and provide this ability to machines, similar to ML. But DL uses complex logical structure of **neurons** connected to each other form **neural networks** to learn. It is used for working with **unstructured data** (such as images, videos, audio, and text), which becomes complex to handle using machine learning algorithms. """) # About the Author st.markdown( """

About the Author

Shubham Mohanty

I'm a Data Science Enthusiast with a strong passion for turning raw data into meaningful insights. With a love for statistics, machine learning, and real-world problem solving, I enjoy working on end-to-end data science projects that make a difference.

LinkedIn GitHub
""", unsafe_allow_html=True ) # Space before button st.markdown("

", unsafe_allow_html=True) # Navigation button (optional if you have multi-page setup) if st.button("Next Page"): st.switch_page("pages/player stats.py")