Machine Learning Project Proposal

Our machine learning project proposal comes with research report where we try to fill, up the prevailing gaps and along with survey status. Over all a detailed explanation will be provided so that you can move ahead of the selected topic.

We create a machine learning project proposal that includes framework the issue that you aim to solve, how you plan to solve it, the resources that you need and the possible influence of the project. We have given a template you can utilize it to generate a proposal.

Title: Machine Learning for Real-Time Mask Detection in Video Surveillance

Abstract: Our project suggests the improvement of a machine learning method that is able of detecting the presence or absence of face masks on every one in real-time video feeds. We aim to improve the public health measures that offer a tool that can be utilized in an area where mask-wearing is mandated and thus helps the implementation of health rules.

Introduction:

  • Background: We have to wear a face mask as it is important for public health practice because of the world-wide spread of communicable diseases like COVID-19.
  • Problem Statement: manual watching of mask observation is labor-intensive and is not possible on a large scale.
  • Objective: We have to automate the process of mask detection, that can decreases the necessity for human watching and to make sure compliance with the health rules.

Literature Review:

  • Our study reviews the key result from current researches on mask detection.
  • Existing methods strengths and weakness can be debated by us.
  • To find the gaps that our project will discourse.

Methodology:

  • Data Collection: Framework the sources of our data and how it will be gathered and labeled.
  • Data Preprocessing: We have to define the steps to make the data for model training (e.g., resizing, normalization, augmentation).
  • Model selection: In our work we have to explain the selection of machine learning models and techniques.
  • Training: Explain the training procedure, with any frameworks and tools you will have to utilize.
  • Evaluation: Explain how we can estimate the models achievement with the appropriate metrics.

Tools and Technologies:

  • Our project needs that list the software, hardware, and any other methods.
  • How we will utilize the tools and explain the selection process for this.

Timeline: We have to offer a detailed timeline of the project from starting to ending, decomposing the phases of the project and to evaluate time for individual.

Budget: Enumerate the estimated cost that linked with the project that involves the software, hardware and personnel.

Expected Outcomes:

  • The possible influence and advantages of our project are debated by us.
  • Our work defines the expected outcomes and the calculated procedure.

Challenges and Limitations:

  • In our work we have to recognize the possible tasks and restrictions in data, technology and implementation.
  • We have to suggest approaches to lessen the problems.

Conclusion: Review our proposal and reiterate the significance of our project and contribution to that     area.

References: To list out the academic references that can helpful to our proposal.

            When making our proposal first we make sure that to offer sufficient details to assure readers of the feasibility and essential of our project. Tailor the proposal of our audience, if it is for academic, commercial, or social influence commitments and we make sure that the advantages and possible applications of the project are perfect and convincing.

Machine Learning Project Proposal Ideas

Machine Learning Thesis Proposal Ideas

Tell us about your areas of interest we sought out the topics while you can select any one or custom topics can be developed. Get a complete research support from leading professionals for your research proposal and so on. We also understand the challenges in this field, experts at phdprime.com, not only have related educational qualification but also have huge experience working in the relevant domain to seek by drawing the attention by your research work for an impressive outcome.

  1. Efficiency Enhancement of Machine Learning Approaches through the Impact of Preprocessing Techniques
  2. A machine-learning based tool for bioimages managing and annotation
  3. A Machine Learning Approach to Carotid Wall Localization in A-mode Ultrasound
  4. Speech Emotion Recognition Using Multi-Layer Sparse Auto-Encoder Extreme Learning Machine and Spectral/Spectro-Temporal Features with New Weighting Method for Data Imbalance
  5. Model-Based Machine Learning for Energy-Efficient UAV Placement
  6. Using Machine Learning to Predict Frailty from Cognitive Assessments
  7. Big Data Analysis Using Hadoop Framework and Machine Learning as Decision Support System (DSS) (Case Study: Knowledge of Islam Mindset)
  8. Learning from Privacy Preserved Encrypted Data on Cloud Through Supervised and Unsupervised Machine Learning
  9. An experimental study for software quality prediction with machine learning methods
  10. Supervised Machine Learning: A Survey
  11. A Study of DDOS Attack Classification Using Machine Learning Classifiers
  12. Malscanner – File Behavior Analysis using Machine Learning
  13. MapReduce Tuning to Improve Distributed Machine Learning Performance
  14. A Dynamic Integrated Model in Machine Learning and Its Application
  15. Machine Learning-Based Security Test Model and Evaluation for SIP-Based DoS Attacks
  16. Exploring The Learning Analytics Of Skill-Based Course Using Machine Learning Classification Models
  17. Personalized Adaptive Learning Technologies Based on Machine Learning Techniques to Identify Learning Styles: A Systematic Literature Review
  18. Fraud identification architecture using data mining and machine learning in a private transport company that operates by applications\
  19. APMWMM: Approach to Probe Malware on Windows Machine using Machine Learning
  20. Opportunistic use of GNSS Signals to Characterize the Environment by Means of Machine Learning Based Processing
Opening Time

9:00am

Lunch Time

12:30pm

Break Time

4:00pm

Closing Time

6:30pm

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