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Abhishek Jha

Data Scientist

+91 8287706259 [email protected]

Resume

Hello, I am

Abhishek Jha.

1

Deep Learning Project

About Me

Passionate about Machine Learning and Deep Learning (ANN, CNN, RNN) with strong skills in building AI-driven applications. Pursuing B.S.
in Data Science and Applications at IIT Madras, with a keen interest in data analysis, model development, and real-world AI solutions

Key Skills

Python, SQL, Java Script, HTML5, CSS3

Scikit-learn, XGBoost, Hugging Face, Pandas, NumPy, Matplotlib, Seaborn, Plotly

TensorFlow, Keras, PyTorch, LangChain, LangGraph, CrewAI, VectorDB

NLP, Text-Processing, Hugging Face, LangChain

React.js, Vue.js, Streamlit, Flask

OpenAI API, Jupyter Notebook, Google Colab, VS Code, Git, Github, Docker, FastAPI,AWS, Postman, PostgreSQL

My Projects

My Experience

AtliQ Technology Virtual

Data Scientist (Internship) Aug 2025 - Present

Gained hands-on experience with data cleaning, visualization, and predictive modeling as part of the virtual internship projects.

Skills: Data Analysis, Machine Learning, Deep Learning, GenAI, NLP, Agentic AI

Awards & Certificate

Python: Beginner to Advanced For Data Professionals

SQL for Data Science

Math and Statistics For AI, Data Science

Master Machine Learning for Data Science & AI: Beginner to Advanced

Deep Learning: Beginner to Advanced

Natural Language Processing

Gen AI to Agentic AI with Business Projects

Let's Connect

Feel free to get in touch with me. I am always open to discussing new projects, creative ideas or opportunities to be part of your visions.

[email protected]

https://www.linkedin.com/in/abhishekjha15/

+ 91 8287706259

https://github.com/abhijha8287

Deep Learning Project

Dogs vs Cats Image Classification

Domain/Function: CNN

Built and trained a deep Convolutional Neural Network (CNN) to classify dog and cat images using the Kaggle dataset.Performed data preprocessing steps such as image resizing, normalization, and augmentation (rotation, flipping, zooming) to improve model generalization.

View Project
on GitHUB

Dogs vs Cats Image Classification

This is how the dataset look, on this dataset only I worked

Dogs vs Cats Image Classification

Comparing XGBoost and ANN accuracy

Project Details

I built and trained a Deep Convolutional Neural Network (CNN) to classify dog and cat images using the Kaggle Dogs vs. Cats dataset. The project involved preprocessing the images through resizing, normalization, and augmentation techniques like flipping and rotation to improve generalization. I designed a CNN architecture with convolutional, pooling, dropout, and dense layers for efficient feature extraction and robust learning. The model was trained using TensorFlow/Keras with regularization, early stopping, and hyperparameter tuning to prevent overfitting and boost accuracy. Model performance was evaluated with accuracy, confusion matrix, and classification reports, achieving reliable results for real-world image classification tasks.