1. Movie Recommendation using Machine learning
Machine learning gives the computer the ability to learn from past data and recommend the list of movies and TV shows to the user. By developing this project, you will learn about various machine learning algorithms and develop a machine learning model to recommend movie titles using Python. By building this project hands-on, you will learn how to use ML to recommend movie titles based on the user's viewing history.
2. Credit Card fraud detection using Machine learning
The aim of this machine learning project is to reduce losses due to payment fraud for both merchants and issuing banks and increase revenue opportunities for merchants. Fraud in credit card transactions is unauthorized and unwanted usage of an account by someone other than the owner of that account. Fraud detection involves monitoring the activities of populations of users in order to estimate, perceive or avoid objectionable behavior, which consists of fraud, intrusion, and defaulting. By building this project, you will learn how to use ML to use past banking data to identify such fraudulent credit card transactions.
3. Handwritten digits recognition using Machine learning
Handwritten digit recognition is the ability of a computer to recognize the human handwritten digits from different sources like images, papers, touch screens, etc, and classify them into 10 predefined classes (0-9). The goal of this project is to create a model that will be able to recognize and determine the handwritten digits from its image by using the concepts of Convolution Neural Network. To create this model, we need a dataset like MNIST dataset. MNIST contains a total of 70,000 handwritten digit images (60,000 - training set and 10,000 - test set) in 28x28 pixel bounding box and anti-aliased. You will learn about Deep learning, neural networks, Keras, and TensorFlow these machine learning concepts by building this project.
4. Stock price prediction using machine learning
Aim of this machine learning project is to predict the stock price. Stock prices Dataset consists of a particular company stock price, open, close, low, and high. The dataset also consists of adj close price, date, and volume. Stock price dataset can be downloaded from the NSE website or Using the fix yahoo finance python package, this package will help to download the updated stock market data. The goal of this machine learning project is to analyze a stock from previous data for future prediction. By building you will learn various machine learning algorithms like auto ARIMA, LSTM etc.
5. Boston house price prediction Machine learning
Boston House Prices Dataset consists of prices of houses across different places in Boston city. The dataset also consists of information on areas of non-retail business (INDUS), crime rate (CRIM), age of people who own a house (AGE), and several other attributes (the dataset has a total of 14 attributes). Boston Housing dataset can be downloaded from the UCI Machine Learning Repository. The goal of this machine learning project is to predict the selling price of a new home by applying basic machine learning concepts to the housing prices data. This dataset is too small with 506 observations and is considered a good start for machine learning beginners to kick-start their hands-on practice on regression concepts.
6. Weather forecasting using machine learning
Machine learning gives the computer the ability to learn from past data and make predictions. By developing this project, you will put ML to action by building a project that predicts weather forecasting. This system will predict the weather based on parameters such as temperature, humidity, and wind.
7. Heart disease prediction using machine learning
The main objective of this machine learning project is to develop a heart prediction system. This system discovers and extracts the hidden knowledge associated with disease from historical data sets. This predictions system aims to exploit data mining techniques on the medical datasets to assist in the prediction of heart disease. By building this project, you will learn how to use Machine Learning to use data to predict heart disease.
8. Student performance analysis using machine learning
Machine learning gives the computer the ability to learn from past data and predict student performance. The dataset includes the actual academic details of the students. By developing this project, you will put ML to action by building a project that predicts student performance by taking the previous data.
9. Book recommendations using machine learning
Machine learning gives the computer the ability to learn from past data and make predictions. This system recommends books that are of the user's interest. By developing this project, you will learn about various machine learning algorithms and develop a machine learning model to recommend books using Python. By building this project hands-on, you will learn how to use ML to recommend books based on the user's interest.
10. Email spam detection using machine learning
The aim of this project is to identify the spam message using machine learning. Spam can be detected through natural language processing and machine learning methodologies. Machine learning methods are commonly used in spam filtering. These methods are used to render spam classifying emails to either ham (valid message) or spam (unwanted messages) with the help of a machine learning classifier. By developing this project you will learn natural language processing on machine learning algorithms.