Sahil Ichake's Projects
Activities to perform for Data Analysis
Document Summarization App using large language model (LLM) and Langchain framework. Used a pre-trained T5 model and its tokenizer from Hugging Face Transformers library. Created a summarization pipeline to generate summary using model.
Determining a person’s gender using Logistic Regression, Random Forest, K-Nearest Neighbors, Support Vector Machine and Decision Tree. Finally concluding that Random Forest is the best algorithm with 99% accuracy.
Conducted data analysis, statistical analysis, and data visualization on an Indian crime dataset. Applied various machine learning algorithms to gain insights from the data. Utilized Time-Series models for prediction and forecasting based on the crime data analysis.
Q & A with multiple pdf App is a Python application that allows you to ask questions about the PDFs you upload using natural language model to generate accurate answers to your queries.
Build a model that detect toxic comments and different types of toxicity. Using Natural Language Processing and LSTM model. Deploying the model using Gradio app.
Convolution Neural Network model to recognize traffic signs by processing the images that containing traffic signs.