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| import streamlit as st | |
| import streamlit.components.v1 as components | |
| import os # Import the os module | |
| import pandas as pd | |
| from sidebar_logo import add_sidebar_logo, load_css, add_page_title_auto | |
| # Set page configuration | |
| st.set_page_config( | |
| layout="wide" | |
| ) | |
| add_sidebar_logo() | |
| load_css() | |
| st.markdown(""" | |
| <div style=" | |
| font-size: 1.9rem; | |
| font-weight: 800; | |
| background: linear-gradient(135deg, #a78bfa, #818cf8, #f472b6); | |
| -webkit-background-clip: text; | |
| -webkit-text-fill-color: transparent; | |
| font-family: 'Poppins', sans-serif; | |
| "> | |
| 📓 1. Jupyter Notebook Introduction | |
| </div> | |
| """, unsafe_allow_html=True) | |
| # Define the file path with regular spaces | |
| path_to_html = "Jupyter_Intro.html" | |
| # Check if the HTML file exists | |
| if not os.path.exists(path_to_html): | |
| st.error("HTML file not found!") | |
| else: | |
| # Read HTML content | |
| with open(path_to_html, 'r', encoding='utf-8') as f: | |
| html_data = f.read() | |
| # Show HTML content | |
| st.header(":white[Getting familar with Jupyter notebook]") | |
| st.markdown("""Hi guys, welcome to your very first session. I am very excited to walk you through all the modules starting from | |
| Preprocessing in Python to Supervised Machine Learning, Unsupervised Machine Learning, Reinforcement Machine Learning and | |
| Deep Learning. The modules are well curated for anyone who is starting Machine Learning or even programming for the first | |
| time. So rest assured it would be a fun ride. :) | |
| To begin with, the entire course is designed to work on Jupyter notebook environment. So it is important for you to first | |
| understand what Jupter notebook is and how does one code on Jupyter notebook. | |
| The coding on Jupyter notebook is done in cell wise fashion unlike VS code. Vs code is another famous interpretor whereas | |
| one can code as well. | |
| Let us understand some basic features of Jupyter notebook first.""") | |
| st.write("---") | |
| st.components.v1.html(html_data, width=1000, height=20100) | |
| def download_notebook(): | |
| with open("Jupyter_Intro.ipynb", "rb") as f: | |
| data = f.read() | |
| return data | |
| # Create a download button for the notebook | |
| st.write("----") | |
| st.write("To download 'Jupyter introduction' Jupyter notebook click on the button below.") | |
| button_label = "Download Jupyter Notebook" | |
| button_download = st.download_button(label=button_label, data=download_notebook(), file_name="Jupyter_Intro.ipynb", mime='application/x-ipynb+json') |