Dog Breed Classification: This project involves using image recognition techniques to classify different dog breeds. It's a great way to learn about image processing, feature engineering, and machine learning algorithms like convolutional neural networks (CNNs). You can find a popular dataset for this task on Kaggle called "Stanford Dogs Dataset."
Titanic Passenger Survival Prediction: This classic project aims to predict whether a passenger survived the Titanic disaster based on various factors like age, gender, and class. It's a good starting point to learn about data exploration, cleaning, and building basic machine learning models like logistic regression and decision trees.
Iris Flower Classification: This project involves classifying different species of iris flowers based on their petal and sepal measurements. It's a simple yet effective way to understand supervised learning algorithms like k-nearest neighbors and support vector machines.
House Price Prediction: This project involves predicting the price of a house based on various features like location, size, and number of bedrooms. It's a good opportunity to learn about linear regression, feature engineering, and model evaluation techniques.
Quora Question Pairs: This project involves identifying whether two Quora questions are semantically similar. It's a great way to learn about natural language processing (NLP) techniques like text cleaning, tokenization, and word embedding.
Movie Recommendation System: This project involves recommending movies to users based on their past viewing history and ratings. It's a good opportunity to learn about collaborative filtering techniques and recommender systems.
Toxic Comment Classification: This project involves identifying comments that contain toxic language, such as hate speech or bullying. It's a challenging task that requires advanced NLP techniques like sentiment analysis and deep learning models.
Customer Churn Prediction: This project involves predicting whether a customer is likely to churn, meaning they will stop doing business with a company. It's a valuable task for businesses to understand and retain their customers.
Time Series Forecasting: This project involves predicting future values of a time series, such as stock prices or energy consumption. It's a complex task that requires advanced statistical techniques and deep learning models like recurrent neural networks (RNNs).
Image Segmentation: This project involves segmenting an image into different parts, such as identifying objects or regions in a picture. It's a powerful technique with various applications, including medical image analysis and autonomous driving.