Contact Information:
Email: [email protected]
Phone: +91 7378397101
LinkedIn: linkedin.com/in/manoj-rathod-072bb0284
Location: Pune, India

As an aspiring Data Scientist, I am passionate about leveraging advanced technologies such as machine learning, deep learning, and data analysis to solve real-world challenges. With a strong foundation in statistical modeling and a knack for building machine learning pipelines, I am eager to apply my skills in innovative and impactful ways. I have hands-on experience with tools like Python, TensorFlow, Scikit-learn, and Power BI and have a solid understanding of data processing, analysis, and visualization techniques.

Bachelor of Computer Applications (BCA)
Ankushrao Tope College Jalna
2021 – 2024

Higher Secondary Certificate (HSC)
Khedkar Junior College Chapadgaon
2020 – 2021

Secondary School Certificate (SSC)
Late. Dattaji Bhale High School
2018 – 2019

• Programming Languages: Python
• Machine Learning: Data Science, Machine Learning, Deep Learning, Model Optimization, ML Pipelines
• Libraries & Frameworks: NumPy, Pandas, Scikit-learn, XGBoost, TensorFlow, Keras, Matplotlib, Seaborn
• Statistical Modeling & EDA: Strong foundation in statistical modeling and exploratory data analysis
• Computer Vision: Image Processing, Object Detection using OpenCV
• SQL & Databases: MySQL for data management and mining
• AI Techniques: Ability to apply AI solutions to real-world problems

• Python Environments: Anaconda, Jupyter, Spyder, PyCharm
• Data Visualization: Matplotlib, Seaborn, Power BI, Google Colab
• Tools: NLTK, OpenCV, Flask

Domain: Banking and Finance
In this project, I developed a machine learning model to predict home loan eligibility based on factors like income, credit score, and loan amount. The project involved:

• Data Preprocessing & EDA: Cleaning and preparing the data for analysis.
• Model Building: Applied multiple algorithms including Logistic Regression, KNN, SVM, Decision Trees, Random Forest, AdaBoost, and XGBoost.
• Model Evaluation: Performed cross-validation and evaluated model accuracy.
• Tools Used: NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, TensorFlow, Flask (for deployment).

• Full Stack Data Science and AI
  Gained expertise in the full data science workflow, including data preprocessing, model building, and deployment. Completed various projects and lab exercises with mentor support.

Feel free to explore my repositories and get in touch for collaborations or opportunities in the field of data science. I am always open to learning, growing, and solving problems with innovative solutions.