Machine Learning & AI Project List with Abstract and Source Code - 21/22
The term artificial intelligence itself says “acquiring intelligence artificially”. Artificial Intelligence is prorogating human intelligence into machines and is the branch of computer science directly related to developing intelligent machines that can simulate human intelligence. A unique characteristic of an artificially intelligent system is that it takes the decisions rationally based on previous experiences and the training given to the model. AI has many applications like voice assistance, image recognition, face unlock in mobiles, etc.
We have selected quite interesting projects in Machine Learning & Artificial Intelligence and tried to explain each project in detail with step by step execution where every individual irrespective of their educational background can learn and execute this projects by themselves.
Project List with Step by Step execution
| S.No | Project Code | ML Projects | Action |
|---|---|---|---|
| 1 | TYTML1001 | Chronic Kidney Disease Prediction using M.L Algorithms | DETAILS |
| 2 | TYTML1002 | Making a Machine to predict whether a person is affected which Heart Disease or Not. | DETAILS |
| 3 | TYTML1003 | Predicting the trend of the house prices with United States housing data and Regression models | DETAILS |
| 4 | TYTML1004 | Identifying weight category of person using Random Forest | DETAILS |
| 5 | TYTML1005 | Credit card fraudulent detection using Machine Learning through financial data. | DETAILS |
| 6 | TYTML1006 | Helping patients know whether they are diabetic or not using Machine Learning | DETAILS |
| 7 | TYTML1007 | Heart Disease Prediction using Machine Learning | DETAILS |
| 8 | TYTML1008 | Identifying male or female based on voice using XGBoost and ML | DETAILS |
| 9 | TYTML1009 | Tic Tac Toe Game with AI Integrated and Front End Framework | DETAILS |
| 10 | TYTML1010 | Making the Data Balanced without any Bias to avoid Overfitting and making wrong predictions. | DETAILS |
| 11 | TYTML1011 | Making Machine identify a covid affected person using supervised learning approach | DETAILS |
| 12 | TYTML1012 | Score prediction of IPL team with flask app | DETAILS |
| 13 | TYTML1013 | How does the Market Behave in future? | DETAILS |
| 14 | TYTML1014 | Contact tracing of covid affected person using DBSCAN Clustering methodology | DETAILS |
| 15 | TYTML1015 | Tic Tac Toe Game with AI Integrated and Front End Framework | DETAILS |
| 16 | TYTML1016 | Road Transportation Analysis and Statistical modelling. | DETAILS |
| 17 | TYTML1017 | Network Severity detection at a specific location based on log data available | DETAILS |
Latest Machine Learning IEEE Project List
- Natural language processing (NLP): Developing AI systems that can understand and generate human-like language, including tasks such as translation, summarization, and dialogue generation.
- Computer vision: Building AI systems that can analyse and understand images and videos, including tasks such as object recognition, facial recognition, and image classification.
- Robotics: Developing AI systems that can perform physical tasks, such as navigating a space, grasping and manipulating objects, and interacting with the environment.
- Machine learning: Building AI systems that can learn from data and improve their performance over time, including tasks such as regression, classification, clustering, and dimensionality reduction.
- Deep learning: A subset of machine learning that involves training artificial neural networks to recognize patterns and make decisions based on data.
- Healthcare: Using AI to improve patient care, including tasks such as analysing medical images, identifying potential diagnoses, and predicting patient outcomes.
- Finance: Developing AI systems that can analyse financial data and make predictions or decisions, such as identifying fraudulent activity or predicting stock prices.
- Agriculture: Using AI to improve farming practices, including tasks such as analysing soil and crop data, predicting crop yields, and optimising irrigation systems.
- Education: Developing AI systems that can assist with education and training, including tasks such as personalised learning and tutoring.
- Environment: Using AI to monitor and protect the environment, including tasks such as analysing satellite images and predicting weather patterns.
- Natural resource management: Using AI to optimise the use of natural resources, such as water and energy.
- Transportation: Developing AI systems that can assist with transportation, including tasks such as traffic prediction, autonomous vehicles, and optimising delivery routes.
- Social media: Building AI systems that can analyse and understand social media data, including tasks such as sentiment analysis, trend prediction, and spam detection.
- Cybersecurity: Using AI to improve cybersecurity, including tasks such as detecting and preventing cyber attacks and identifying vulnerabilities.
- Customer service: Developing AI systems that can assist with customer service, including tasks such as answering customer queries and resolving issues.
- Manufacturing: Using AI to improve manufacturing processes, including tasks such as optimising production schedules and predicting maintenance needs.
- Supply chain management: Building AI systems that can assist with managing supply chain operations, including tasks such as demand forecasting and optimising inventory levels.
- Retail: Developing AI systems that can assist with retail operations, including tasks such as personalising product recommendations and optimising pricing.
- Music: Using AI to analyse and understand music, including tasks such as music recommendation, music generation, and music classification.
- Sports: Building AI systems that can assist with sports, including tasks such as player analysis, performance prediction, and game analysis.
- Personal assistants: Developing AI systems that can assist with tasks such as scheduling, task management, and answering questions.
- Search engines: Building AI systems that can understand and analyse search queries and return relevant results.
- e-Commerce: Using AI to improve e-commerce operations, including tasks such as personalising product recommendations and optimising pricing.
- Marketing: Developing AI systems that can assist with marketing tasks, including customer segmentation, campaign optimization, and lead generation.
- Fraud detection: Building AI systems that can analyse data to identify fraudulent activity, such as fraudulent credit card transactions or fraudulent insurance claims.
- Legal: Using AI to assist with legal tasks, including tasks such as contract analysis and legal research.
- HR: Developing AI systems that can assist with human resources tasks, such as resume screening and employee performance evaluation.
- Security: Building AI systems that can assist with security tasks, such as identifying threats and anomalies in surveillance footage.
- Weather forecasting: Using AI to improve weather forecasting, including tasks such as predicting severe weather events and analysing satellite data.
- Energy: Developing AI systems that can assist with energy management, including tasks such as optimising energy consumption and predicting energy demand.
- Real estate: Using AI to improve real estate operations, including tasks such as predicting property values and identifying potential buyers.
- Environmental science: Building AI systems that can assist with environmental tasks, such as analysing satellite data and predicting weather patterns.
- Agriculture: Developing AI systems that can improve farming practices, such as analysing soil data and predicting crop yields.
- Genetics: Using AI to analyse and understand genetic data, including tasks such as identifying genetic mutations and predicting disease risk.
- Drug discovery: Building AI systems that can assist with drug discovery, including tasks such as identifying potential drug targets and optimising drug design.
- Healthcare: Developing AI systems that can assist with healthcare tasks, such as analysing medical images and predicting patient outcomes.
- Telecommunications: Using AI to improve telecommunications, including tasks such as optimising network performance and predicting network demand.
- Gaming: Building AI systems that can assist with gaming, including tasks such as game design and player analysis.
- Social services: Developing AI systems that can assist with social services tasks, such as identifying potential cases of abuse and predicting social trends.
- Government: Using AI to improve government operations, including tasks such as analysing data to identify trends and patterns.
- Natural disasters: Building AI systems that can assist with natural disaster response and prevention, including tasks such as predicting severe weather events and analysing satellite data.
- Space exploration: Using AI to improve space exploration, including tasks such as analysing data from space missions and optimising spacecraft design.
- Education: Developing AI systems that can assist with education and training, including tasks such as personalised learning and tutoring.
- Defence: Building AI systems that can assist with defence tasks, such as analysing surveillance data and identifying potential threats.
- Transportation: Using AI to improve transportation, including tasks such as optimising delivery routes and predicting traffic patterns.
- Law enforcement: Developing AI systems that can assist with law enforcement tasks, such as analysing surveillance footage and identifying potential suspects.
- Disaster relief: Building AI systems that can assist with disaster relief efforts, including tasks such as identifying affected areas and predicting resource needs.
- Social impact: Using AI to improve social impact, including tasks such as predicting and preventing social issues, such as poverty and homelessness.
- Renewable energy: Developing AI systems that can assist with renewable energy tasks, such as optimising energy production and predicting energy demand.
- Agriculture: Building AI systems that can assist with agriculture tasks, such as optimising irrigation systems and predicting crop yields.
- Environmental science: Using AI to improve environmental science, including tasks such as analysing satellite data and predicting weather patterns.
- Medicine: Building AI systems that can assist with medical tasks, such as analysing medical images and predicting patient outcomes.
- Personal assistants: Developing AI systems that can assist with tasks such as scheduling, task management, and answering questions.
- Fraud detection: Using AI to analyse data to identify fraudulent activity, such as fraudulent credit card transactions or fraudulent insurance claims.
- Legal: Building AI systems that can assist with legal tasks, such as contract analysis and legal research.
- HR: Developing AI systems that can assist with human resources tasks, such as resume screening and employee performance evaluation.
- Security: Using AI to assist with security tasks, such as identifying threats and anomalies in surveillance footage.
- Weather forecasting: Building AI systems that can improve weather forecasting, including tasks such as predicting severe weather events and analysing satellite data.
- Energy: Developing AI systems that can assist with energy management, including tasks such as optimising energy consumption and predicting energy demand.
- Real estate: Using AI to improve real estate operations, including tasks such as predicting property values and identifying potential buyers.
- Environmental science: Building AI systems that can assist with environmental tasks, such as analysing satellite data and predicting weather patterns.
- Agriculture: Using AI to improve farming practices, such as analysing soil data and predicting crop yields.
- Genetics: Developing AI systems that can analyse and understand genetic data, including tasks such as identifying genetic mutations and predicting disease risk.
- Drug discovery: Building AI systems that can assist with drug discovery, including tasks such as identifying potential drug targets and optimising drug design.
- Healthcare: Using AI to assist with healthcare tasks, such as analysing medical images and predicting patient outcomes.
- Telecommunications: Building AI systems that can improve telecommunications, including tasks such as optimising network performance and predicting network demand.
- Gaming: Using AI to assist with gaming, including tasks such as game design and player analysis.
- Social services: Developing AI systems that can assist with social services tasks, such as identifying potential cases of abuse and predicting social trends.
- Government: Building AI systems that can improve government operations, including tasks such as analysing data to identify trends and patterns.
- Natural disasters: Using AI to assist with natural disaster response and prevention, including tasks such as predicting severe weather events and analysing satellite data.
- Space exploration: Developing AI systems that can improve space exploration, including tasks such as analysing data from space missions and optimising spacecraft design.
- Education: Building AI systems that can assist with education and training, including tasks such as personalised learning and tutoring.
- Defence: Using AI to assist with defence tasks, such as analysing surveillance data and identifying potential threats.
- Transportation: Developing AI systems that can improve transportation, including tasks such as optimising delivery routes and predicting traffic patterns.
- Law enforcement: Building AI systems that can assist with law enforcement tasks, such as analysing surveillance footage and identifying potential suspects.
- Disaster relief: Using AI to assist with disaster relief efforts, including tasks such as identifying affected areas and predicting resource needs.
- Social impact: Developing AI systems that can improve social impact, including tasks such as predicting and preventing social issues, such as poverty and homelessness.
- Renewable energy: Building AI systems that can assist with renewable energy tasks, such as optimising energy production and predicting energy demand.
- Agriculture: Using AI to assist with agriculture tasks, such as optimising irrigation systems and predicting crop yields.
- Environmental science: Developing AI systems that can assist with environmental tasks, such as analysing satellite data and predicting weather patterns.
- Medicine: Building AI systems that can assist with medical tasks, such as analysing medical images and predicting patient outcomes.
- Personal assistants: Developing AI systems that can assist with tasks such as scheduling, task management, and answering questions.
- Fraud detection: Using AI to analyse data to identify fraudulent activity, such as fraudulent credit card transactions or fraudulent insurance claims.
- Legal: Building AI systems that can assist with legal tasks, such as contract analysis and legal research.
- HR: Using AI to assist with human resources tasks, such as resume screening and employee performance evaluation.
- Security: Developing AI systems that can assist with security tasks, such as identifying threats and anomalies in surveillance footage.
- Weather forecasting: Building AI systems that can improve weather forecasting, including tasks such as predicting severe weather events and analysing satellite data.
- Energy: Using AI to assist with energy management, including tasks such as optimising energy consumption and predicting energy demand.
- Real estate: Building AI systems that can improve real estate operations, including tasks such as predicting property values and identifying potential buyers.
- Environmental science: Developing AI systems that can assist with environmental tasks, such as analysing satellite data and predicting weather patterns.
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