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