from pathlib import Path import streamlit as st from PIL import Image st.set_page_config( page_title="NLP WEB APP" ) # --- PATH SETTINGS --- current_dir = Path(__file__).parent if "__file__" in locals() else Path.cwd() css_file = current_dir / "styles" / "main.css" resume_file = current_dir / "assets" / "my_resume.pdf" profile_pic = current_dir / "assets" / "profile-pic.png" # --- GENERAL SETTINGS --- PAGE_TITLE = "Digital CV | John Doe" PAGE_ICON = ":wave:" NAME = "SUDHANSHU" DESCRIPTION = """ Aspiring Data Scientist | 18-Year-Old Data Enthusiast | 1 Year of Hands-On Experience | Passionate about Solving Real-World Problems" """ EMAIL = "gusainsudhanshu43@gmail.com" SOCIAL_MEDIA = { "YouTube": "https://youtube.com/", "LinkedIn": "https://www.linkedin.com/in/sudhanshu-gusain-34271028a/", "GitHub": "https://github.com/sudhanshu976", "Twitter": "https://twitter.com", } PROJECTS = { "🏆 POWER-BI Dashboards - Making interactive and dynamic dashboards": "https://github.com/sudhanshu976/POWER-BI-PROJECTS", "🏆 Potato Disease Classifier using CNN - Checks whether a given potato leaf is healthy , early-blight or late-blight": "https://github.com/sudhanshu976/POTATO-DISEASE-CLASSIFIER-WITH-DEPLOYMENT", "🏆 Combined NLP WEB APP - This web app contains all NLP Projects I have made till date ": "https://github.com/sudhanshu976/NLP_FULL", } # --- LOAD CSS, PDF & PROFIL PIC --- with open(css_file) as f: st.markdown("".format(f.read()), unsafe_allow_html=True) with open(resume_file, "rb") as pdf_file: PDFbyte = pdf_file.read() profile_pic = Image.open(profile_pic) # --- HERO SECTION --- col1, col2 = st.columns(2, gap="small") with col1: st.image(profile_pic, width=230) with col2: st.title(NAME) st.write(DESCRIPTION) st.download_button( label=" 📄 Download Resume", data=PDFbyte, file_name=resume_file.name, mime="application/octet-stream", ) st.write("📫", EMAIL) # --- SOCIAL LINKS --- st.write('\n') cols = st.columns(len(SOCIAL_MEDIA)) for index, (platform, link) in enumerate(SOCIAL_MEDIA.items()): cols[index].write(f"[{platform}]({link})") # --- EXPERIENCE & QUALIFICATIONS --- st.write('\n') st.subheader("Experience & Qulifications") st.write( """ - ✔️ 1 Year expereince of performing various Data Science and NLP tasks - ✔️ Strong hands on experience and knowledge in Python , ML , DL and NLP - ✔️ Good understanding of statistical principles and their respective applications - ✔️ Excellent team-player and displaying strong sense of initiative on tasks """ ) # --- SKILLS --- st.write('\n') st.subheader("Hard Skills") st.write( """ - 👩‍💻 Programming: Python (Scikit-learn, Pandas , Numpy , Pytorch , Tensorflow) - 📊 Data Visulization: PowerBi, Matplotlib , Seaborn - 📚 Modeling: Supervised and Unsupervised ML algorithms , ANN , RNN , CNN - 🗄️ Databases: MySQL - 🗄️ WEB DEPLOYMENT: FLASK , Streamlit , Heroku """ ) # --- WORK HISTORY --- st.write('\n') st.subheader("Work History") st.write("---") # --- JOB 1 st.write("🚧", "**Freelancer Data Scientist and NLP Engineer**") st.write("05/2023 - Present") st.write( """ - ► Used PowerBI for creating interactive dashboards - ► Solved many ML , DL and NLP problems in various fields like medical , agriculture , etc - ► Well versed in solving real life problems especially using NLP """ ) # --- Projects & Accomplishments --- st.write('\n') st.subheader("Projects & Accomplishments") st.write("---") for project, link in PROJECTS.items(): st.write(f"[{project}]({link})")