Machine_Learning / Home.py
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import streamlit as st
from streamlit_lottie import st_lottie
import requests
# Function to load Lottie animations
def load_lottieurl(url: str):
try:
r = requests.get(url)
r.raise_for_status() # Will raise an exception for 4xx/5xx errors
return r.json()
except requests.exceptions.RequestException as e:
# Log the error if the URL is not accessible or if there is any issue
st.error(f"Error loading Lottie animation from {url}: {e}")
return None
# Load animations
robot_animation = load_lottieurl("https://lottie.host/45619748-3867-4f57-8f50-cac297eca2da/1q98CFxp2I.json")
hero_animation = load_lottieurl("https://assets9.lottiefiles.com/packages/lf20_touohxv0.json")
data_science_animation = load_lottieurl("https://assets9.lottiefiles.com/packages/lf20_jcikwtux.json")
ml_animation = load_lottieurl("https://lottie.host/e4bb50e7-3033-4642-b51b-05b703d86236/yje0T0dWeq.json") # New URL for ML animation
dl_animation = load_lottieurl("https://assets10.lottiefiles.com/packages/lf20_kuhijlvx.json")
gen_ai_animation = load_lottieurl("https://assets4.lottiefiles.com/packages/lf20_x62chJ.json")
# Home Page
st.title("Zero to Hero in Machine Learning 🌟")
if hero_animation: # Only show if the animation was successfully loaded
st_lottie(hero_animation, height=300, key="hero")
st.header("About the Author πŸ“–")
if robot_animation:
st_lottie(robot_animation, height=300, key="robot")
st.write("""
Hi, I'm Phaneendra Bharadwaj, an aspiring data scientist and machine learning enthusiast.
Here's a bit about me:
- **Skills:** Python, Exploratory Data Analysis, Machine Learning, Deep Learning, Generative AI.
- **Experience:** I'm a Fresher, working on various ML related projects.
""")
st.markdown(
"""
<div style="position: fixed; top: 20px; right: 20px; display: flex; align-items: center;">
<div style="font-size:30px; color:#f39c12; font-weight:bold; animation: textAnimation 2s ease-in-out infinite; margin-right: 20px;">
Hey User! Are you Ready??
</div>
<div>
<!-- Lottie animation -->
<div style="width: 100px; height: 100px;">
<script src="https://cdnjs.cloudflare.com/ajax/libs/bodymovin/5.7.10/lottie.min.js"></script>
<div id="lottie"></div>
<script>
var animation = bodymovin.loadAnimation({
container: document.getElementById('lottie'),
renderer: 'svg',
loop: true,
autoplay: true,
path: 'https://lottie.host/45619748-3867-4f57-8f50-cac297eca2da/1q98CFxp2I.json'
});
</script>
</div>
</div>
</div>
<style>
@keyframes textAnimation {
0% { color: #f39c12; transform: scale(1.1); }
50% { color: #e74c3c; transform: scale(1.2); }
100% { color: #f39c12; transform: scale(1.1); }
}
</style>
""",
unsafe_allow_html=True
)
# Sections
st.subheader("πŸ“Š Data Science")
if data_science_animation:
st_lottie(data_science_animation, height=200, key="data_science")
st.write("""
Data Science involves extracting insights from data using statistical techniques.
**Example:** Predicting sales based on historical data.
""")
st.subheader("πŸ€– Machine Learning")
if ml_animation:
st_lottie(ml_animation, height=200, key="machine_learning")
st.write("""
Machine Learning is a tool used to learn the data from Natural Intelligence,it is a tool used to mimic/copy Natural Intelligence.This uses statistical concepts to mimic /copy learning ability.
**Example:** Spam email detection.
""")
st.subheader("🧠 Deep Learning")
if dl_animation:
st_lottie(dl_animation, height=200, key="deep_learning")
st.write("""
Deep Learning is a subset of Machine Learning that uses neural networks.It is also a tool used to learn the data from Natural Intelligence.
**Example:** Image recognition, like identifying cats in pictures.
""")
st.subheader("✨ Generative AI")
if gen_ai_animation:
st_lottie(gen_ai_animation, height=200, key="gen_ai")
st.write("""
Generative AI creates new content by learning from existing data which we've learn't by using ML,DL from Natural Intelligence.
**Example:** ChatGPT for generating human-like text responses.
""")
# Footer with animation
st.write("---")
st.markdown("**Let's embark and dive deep on this journey from Zero to Hero! πŸš€**")