Projects On Artificial Intelligence and Machine Learning

We state that the application of artificial intelligence (AI) and machine learning (ML) evolve among several fields. Subject matter expert proposes novel and original topics on all domain of artificial intelligence (AI) and machine learning (ML) for scholars. Our work plan is in such a way that you get a proper thesis at the end you can approach us at any time if any minor changes need to be done in any area of the project. We tackle the correct solution for the proposed statement problem for any artificial intelligence (AI) and machine learning (ML) projects as we have huge resources and latest methodologies, techniques to derive the accurate result.

Contact our domain expert today and get one to ne solution for all your projects in artificial intelligence (AI) and machine learning (ML)  

Here the following discussion describes several research concepts based on various research domains:

  1. Healthcare:
  • Diagnosis Assist: To detect possible diseases or problems and to examine clinical images (such as MRIs, X-rays), we employ ML techniques.
  • Drug Discovery: To forecast the molecular activity and fasten the procedures of drug discovery, our work utilizes deep learning.
  1. E-commerce & Retail:
  • Suggestion Framework: Our project recommends products to customers by considering their previous search data or interests through the creation of a framework.
  • Customer Churn Forecasting: We detect users who intend to stop utilizing a service or purchasing goods.
  1. Entertainment & Media:
  • Music Suggestion: To suggest music or playlists by analyzing the user’s interests, we create a model.
  • Movie Script Generator: Our research creates film scripts or storylines by utilizing recurrent neural networks.
  1. Smart Cities:
  • Traffic Flow Optimization: We optimize traffic signal regularity and enhance the flow through the use of reinforcement learning.
  • Waste Management: AI techniques assist us to forecast waste production figures and optimize waste gathering paths,
  1. Computer Vision:
  • Object Identification: By analyzing videos or image data, identification and categorization of objects are very helpful for us in automatic vehicles or monitoring.
  • Facial Recognition: We execute a framework that examines digital video or image data to detect or validate people.
  1. Transportation & Logistics:
  • Route Optimization: To discover the best path for deliveries based on congestion and other factors, we make use of ML.
  • Predictive Maintenance: Our project forecasts when machines or equipment are possible to collapse and sets up an advanced maintenance.
  1. Natural Language processing:
  • Sentiment Analysis: To know about the sentiment (positive, neutral or negative) of an individual, we examine the text from tweets or product feedback.
  • Chatbots: Development of interactional model helps us to answer questions or ease online transactions.
  1. Agriculture:
  • Yield Forecasting: By considering various factors like satellite image, weather data and others, we forecast the crop production.
  • Disease Identification in Plants: To identify and cure diseases, our research examines crop images.
  1. Cybersecurity:
  • Phishing Website Identification: By considering the information and design, we categorize the websites as genuine or phishing.
  • Intrusion Detection: To identify abnormalities in network congestion that may denote a cyber-assault, our project trains the framework.
  1. Gaming:
  • Game : For video games, we build an intelligent model that can play against or collaborate with human players.
  • Procedural Content Generation: To autonomously create game-based rules such as stages, constraints or description, our approach employs AI.
  1. Environment:
  • Air Quality Forecasting: To forecast air quality indices in terms of previous and actual-time data, we utilize time series prediction.
  • Wildlife Monitoring: We monitor and categorize wildlife in secured regions by employing deep learning and camera captured images.
  1. Finance:
  • Credit Scoring: In our project, we forecast the possibility of a customer defaulting on a loan by executing ML-based frameworks.
  • Stock Market Forecasting: To forecast upcoming prices or business strategies, our work examines previous stock market data.

It is very essential to consider the following factors such as effective interpretation of ML techniques, association with field professionals like finance or healthcare, accessibility to important data for the execution of above-described research topics. Instead of being directly involved in the project, it is very appreciable to carry out a feasibility study to check we have all relevant resources.

Research Topics on Artificial Intelligence and Machine Learning

Artificial Intelligence and Machine Learning Thesis Topics

Huge domain expertise support are provided by to provide Artificial Intelligence and Machine Learning Thesis Topics. Interesting topics as per scholars’ specifications are given as topic stays as foremost key for research success.

Some of our special features in selecting right thesis support are:

  • Novel thesis ideas
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The below listed are the interesting thesis topics ideas that we have developed go through it and contact us for more support.

  1. Revolutionizing condition monitoring techniques with integration of artificial intelligence and machine learning
  2. Harnessing the potential of microalgae-bacteria interaction for eco-friendly wastewater treatment: A review on new strategies involving machine learning and artificial intelligence
  3. A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
  4. New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson’s disease
  5. Balancing machine learning and artificial intelligence in soil science with human perspective and experience
  6. FDA-cleared artificial intelligence and machine learning-based medical devices and their 510(k) predicate networks
  7. Biofuels for a sustainable future: Examining the role of nano-additives, economics, policy, internet of things, artificial intelligence and machine learning technology in biodiesel production
  8. Integrating machine learning algorithms and explainable artificial intelligence approach for predicting patient unpunctuality in psychiatric clinics
  9. Intriguing of pharmaceutical product development processes with the help of artificial intelligence and deep/machine learning or artificial neural network
  10. Applications of artificial intelligence technologies in water environments: From basic techniques to novel tiny machine learning systems
  11. Implementation of artificial intelligence and machine learning-based methods in brain–computer interaction
  12. Mature artificial intelligence– and machine learning–enabled medical tools impacting vascular surgical care: A scoping review of late-stage, US Food and Drug Administration–approved or cleared technologies relevant to vascular surgeons
  13. Artificial Intelligence/Machine Learning and Mechanistic Modeling Approaches as Translational Tools to Advance Personalized Medicine Decisions
  14. Recent advances in describing and driving crystal nucleation using machine learning and artificial intelligence
  15. Predictive Modeling Using Artificial Intelligence and Machine Learning Algorithms on Electronic Health Record Data: Advantages and Challenges
  16. Optimising pre-reforming for quality r-SOC syngas preparation using artificial intelligence (AI) based machine learning (ML)
  17. Artificial intelligence and machine learning overview in pathology & laboratory medicine: A general review of data preprocessing and basic supervised concepts
  18. A review on rhodamine probes for metal ion recognition with a future on artificial intelligence and machine learning
  19. Guiding the optimization of membraneless microfluidic fuel cells via explainable artificial intelligence: Comparative analyses of multiple machine learning models and investigation of key operating parameters
  20. Application of artificial intelligence and machine learning technology for the prediction of postmortem interval: A systematic review of preclinical and clinical studies

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