Tushar Thokdar's Projects
🥭🥭Mango Disease Prediction CNN Deep Learning Project using Streamlit🥭🥭 Description: This project tackles the challenge of accurately identifying and classifying mango diseases using a Convolutional Neural Network (CNN)
💻Want to boost your bank's term deposit sales? This clever system predicts which customers are most likely to say "yes" to a term deposit, letting you target them with personalized calls. ️ No more cold calls! Just happy customers locking in great rates.
Predict Bike🚲 Rentals with Weather! This project uses regression to predict hourly bike rentals by combining historical usage data with weather information. It helps bike-sharing companies optimize resources and improve user experience.
BlackFriday EDA And Feature Engineering.
Unveil Restaurant Trends & Customer Insights with Zomato EDA This project delves into the fascinating world of Zomato through Exploratory Data Analysis (EDA). By analyzing restaurant data, we uncover hidden patterns, trends, and customer preferences in the food and dining landscape.
👁️ Vision AI: Leverage GEMINI's powerful image recognition and understanding to create intelligent visual experiences. Chatbots: Develop engaging and informative chatbots powered by GEMINI's natural language processing and generation. Question Answering: Design effective Q&A systems that provide accurate and insightful responses
This project explores the connection between family background, writing/speaking skills, and math ability. It focuses on educational equity, aiming to identify challenges and create targeted resources
🎞IMDB Sentimental Analysis with Simple RNN This repository contains a Streamlit application for predicting the sentiment of movie reviews using a pre-trained Simple RNN model. The model has been trained on the IMDB dataset, and the application allows users to input their own reviews to get sentiment predictions. Feel free to explore the code.
"Titanic: Machine Learning from Disaster" is a classic Kaggle competition for beginners https://www.kaggle.com/competitions/titanic. The goal is to use machine learning to predict which passengers survived the sinking of the Titanic based on historical data. This teaches data analysis and model building skills in a real-world context.
👨💼👩💼Crew AI is a popular open-source framework that enables AI agents work together to complete tasks. It's built on Langchain and encourages collaborative intelligence to help agents work together efficiently to solve complex problems.