• Lalit Malviya
• Yash Mahajan
• Yash Desai
• Aayush Patil
• Prof. Santosh Kale

The proliferation of textual data across digital platforms has given rise to the need for automated sentiment analysis and emotion detection. This project addresses this demand by proposing a comprehensive solution that leverages both traditional machine learning (ML) techniques and state-of-the-art deep learning (DL) architectures, while also mitigating class imbalance through random under sampling. In today's data-driven world, understanding the sentiments and emotions expressed in textual data is of paramount importance. This project presents a comprehensive solution to the challenges of sentiment analysis and emotion detection by harnessing the power of machine learning (ML), deep learning (DL), and strategic random under sampling. The explosion of textual data on digital platforms necessitates automated methods for sentiment analysis, involving the classification of text into positive, negative, or neutral sentiments. Furthermore, emotion detection requires the identification of specific emotions, such as happiness, anger, and sadness, within this text. These tasks are compounded by imbalanced datasets where some classes are significantly underrepresented. Accurate sentiment analysis and emotion detection have profound implications across various domains, including brand management, customer satisfaction analysis, and mental health monitoring. The models developed in this project will empower decision-makers with insights derived from textual data, enhancing the quality of user experiences and informed decision-making.

Machine Learning , Deep Learning , Sentiment Analysis , Data Preprocessing , Convolutional Neural Networks , Haar Cascade , Emotion Detection.

"Sentimental Analysis And Emotion Detection Using ML, DL And Random Under Sampling", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.c311-c318, March-2024, Available :http://www.jetir.org/papers/JETIR2403239.pdf

"Sentimental Analysis And Emotion Detection Using ML, DL And Random Under Sampling", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppc311-c318, March-2024, Available at : http://www.jetir.org/papers/JETIR2403239.pdf