Aman Tiwari
Enthusiastic and dedicated, having expertise in Python, data structures, algorithms, and machine learning. Proficient with scikit-learn, tensorflow, numpy, and pandas. Experienced with natural language processing. Also preparing for the GATE exam to increase my technical knowledge. I am eager to contribute to unique projects and thrive in a dynamic enviroment.
Aman Tiwari
About Me
Enthusiastic and dedicated data scientist with expertise in Python, machine learning, deep learning, and natural language processing. I am passionate about building innovative solutions and continuously enhancing my technical knowledge. Currently pursuing a B.Tech in Computer Science and Engineering.
Technical Skills
- Languages: Python, C, C++, HTML, CSS, SQL, SQLite, MongoDB
- Deep Learning Frameworks: TensorFlow, PyTorch, Keras
- Developer Tools: Jupyter, Visual Studio Code, GitHub
- Libraries & Tools: NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn, OpenCV, NLTK, PowerBI, Streamlit
- Soft Skills: Critical Thinking, Leadership, Professionalism, Growth Mindset, Communication
Education
- B.Tech in Computer Science and Engineering
Guru Gobind Singh Indraprastha University (2021 – 2025) | CGPA: 8.8
Work Experience
- AI Internship Training @ IBM SkillsBuild (Jul 2024 – Aug 2024)
- Developed a chatbot-based framework using Python, TensorFlow, PyTorch, and Keras.
- Conducted research on AI and ML algorithms.
- Data Science Training @ IIIT Allahabad & EngineerCore (Jun 2023 – Aug 2023)
- Built a predictive model using XGBoost for house price estimation.
- Enhanced skills in data pre-processing and visualization.
Projects
Conversational PDF Analysis Using LLMs
- Built an interactive system for querying PDFs using LLaMA-3.1-70b model via Groq API.
- Tools: PyPDF2, LangChain, FAISS, Streamlit.
Research Paper to Podcast Generation
- Converted research papers into audio podcasts using NLP and Transformers.
- Designed a Streamlit interface for easy file uploads and podcast generation.
PawClassifier- Reflects the functionality of classifying pets
- Used Python, NLP, Transformers, and Audio segmentation for Converts research papers in PDF format into audio podcasts for easy listening and condenses lengthy content into concise summaries for quick insights.
- Utilized XGBoost, an efficient and high-performance gradient boosting framework for developed a predictive model to estimate house prices in Boston.
Boston House Price Prediction
- Machine Learning Implementation with XGBoost: Developed a predictive model using XGBoost to estimate house prices, achieving a 92% accuracy rate and enhancing predictive performance by 25%.
- Utilized advanced data analysis techniques and Python libraries like pandas and scikit-learn, resulting in 30% faster data manipulation and 15% more efficient model evaluation
Certifications
- Python (Google)
- SQL (UC Davis)
- Machine Learning (EngineerCore)
- Python Data Structures (University of Michigan)
- IBM SkillsBuild AI Internship Program
Let’s Connect!
- Email: emperioraman@outlook.com
- LinkedIn: linkedin.com/in/aman-tiwari-96a058228
- GitHub: github.com/Aman934