64 Machine Learning Essay Topic Ideas & Examples

🏆 Best Machine Learning Topic Ideas & Essay Examples

1. Data Analysis Package for Machine Learning
   All sides of the tale investigate and evaluate a variety of topics and concerns. The benefits of open-source software include the fact that it is free to experiment, use, alter, and redistribute.
2. How AI and Machine Learning Influence Marketing in the Fashion Industry
   As governments shut down factories, stores, and events to stop the transmission of the virus, the COVID-19 pandemic has had a tremendous impact on the worldwide fashion industry.
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3. Machine Learning and Customer Satisfaction
   To effectively use the k-Nearest Neighbour algorithm and create useful managerial insights, one must understand the strengths and drawbacks of k-NN.
4. Artificial Intelligence and Machine Learning
   There are both benefits and challenges to the use of AI and ML in the customer complaint resolution process. The ability of a company to provide a customer experience depends on that business’s power to […]
5. Diagnosis of Dementia by Machine Learning Methods in Epidemiological Studies
   Therefore, epidemiological studies directly impact the diagnosis, prognosis, and clinical treatment by presenting medical practitioners with relevant data on the course, presentation, and treatment of an illness.
6. Regularization Techniques in Machine Learning
   In another example, when predicting the payback of a business product, the system can use indicators of the area’s population and the presence of competitors in the district, ignoring the age or gender aspects of […]
7. Machine Learning: Bias and Variance
   High variance can be similarly detrimental for a prediction, as a model trained on a highly specific data cluster will be able to predict outcomes that are too complex for utilizing outside of the example […]
8. Machine Learning and Regularization Techniques
   The last regularization technique is adversarial regularization; the reason for attention is the privacy protection. In the need for additional regularization outside the learning process, dropout will be of use.
9. Aspects of Machine Learning in Clinical Research
   As computers and machines have a place in every sphere of life, it is obvious that it is the safest route for proposing further changes in clinical research and practice.
10. Machine Learning for Internet of Things Devices
    Hussain et al.justify the use of ML for IoT by pointing out the vast amount of data that IoT gathers. Other recent papers, such as the one by Diedrichs et al, focus on the more […]
11. Artificial Intelligence and Machine Learning in Clinical Trials
    At the same time, to draw contrasts on the application of AI and ML in the health sector, the limitations of the technologies will also be elucidated to highlight areas of improvement that could be […]
12. Machine Learning Algorithms in Cancer Detection
    One of the most fundamental tools for machine learning in cancer detection is the use of imaging, with the premise that prognostic data is embedded in pathology images and digital pathology can provide big data […]
13. The Concept of Machine Learning in Business
    This research is very important since it will explain how modern-day managers can increase their reliance on information technology to enhance their managerial functions.
14. Approach For Understanding Machine Learning Methods
    It can be used to set the degree of influence of independent variables on the dependent ones. Before proceeding to the analysis of data, it is vital to identify the variables.
15. Epilepsy Prediction Using Machine Learning Method
    The findings clearly match those of Wundari et al.and Deriche et al.that innovative seizure detection techniques are more accurate in detecting epilepsy.
16. Data Mining and Machine Learning Algorithms
    The shortest distance of string between two instances defines the distance of measure. However, this is also not very clear as to which transformations are summed, and thus it aims to a probability with the […]
17. Developments in the Field of Machine Learning
    The environment of learning consists of a machine input, or a piece of information that a machine can respond to. One of the best ways that we can think of in solving the problem of […]
18. Machine Learning and Bagging Predictors
    The aggregate uses the average of the single predictors, to improve the accuracy of prediction especially for unstable procedures such as neural sets, regression trees and classification trees.
19. Concept Drifts and Machine Learning
    The main theory that is used in explaining machine learning is referred to as the computational learning theory where the learning theory is focused on the probabilistic performance bounds of the learning algorithm because the […]
20. Geographical Information System and Machine Learning
    Without the need for a more detailed discussion of the advantages and disadvantages of each method, it is essential to postulate that both DT and SVM have sufficient potential to improve flood modeling in hydrological […]
21. Machine Learning for Improved Management
    The theoretical perspectives that will be used in the proposed study will discuss the question of information technologies’ impact on the management of professional activities and the world in general.
22. Machine Learning in Complex Networks
    The primary and secondary data both demonstrate the importance of machine learning and big data in enhancing the role of managers in the modern business environment.
23. Technology and Healthcare Ethics: Machine Learning
    Programmers and pioneers of machine learning must, therefore, be on the frontline to consider emerging ethical issues that can affect a patient’s autonomy throughout the medical care delivery process.
24. Advertising Technology: Machine Learning Advancements
    This paper focus on the description of advertising technology, the insights gained in its development, and the interpretation of machine learning coupled with how tech ads contributed to the development of machine learning and other […]

✅ Good Essay Topics on Machine Learning

1. Ethical Questions of Machine Learning: Racist Hiring Policies And Increasing Profits
2. Machine Learning Approaches: Supervised, Unsupervised, and Reinforcement Learning
3. How Does Artificial Intelligence Use Machine Learning
4. The Limitations of Machine Learning in an Enterprise Setting
5. Analysis of Machine Learning Algorithm for Facial Expression Recognition
6. Large Data Sets and Machine Learning: Applications to Statistical Arbitrage
7. Can Machine Learning Approaches Lead Toward Personalized Cognitive Training
8. Machine Learning for Predicting Vaccine Immunogenicity
9. Urban Data Streams and Machine Learning: A Case of Swiss Real Estate Market
10. The Most Common Risk in Machine Learning: Protect Sensitive or Confidential Data
11. Machine Learning for Solar Accessibility: Implications for Low-Income Solar Expansion and Profitability
12. Understanding the Security Implications of the Machine-Learning Supply Chain
13. Machine Learning for Detection of Safety Signals: Example of Nivolumab and Docetaxel
14. Optimal Taxation and Insurance Using Machine Learning: Learning Sufficient Statistics and Beyond
15. Machine Learning for Quantitative Finance: Fast Derivative Pricing, Hedging, and Fitting
16. Accelerating the Branch-And-Price Algorithm Using Machine Learning
17. Machine Learning Versus Econometrics: Prediction of Box Office
18. How Netflix Uses Machine Learning
19. Machine Learning-Based Algorithm for Circularity Analysis
20. The Uses of Social Theory in Machine Learning for Social Science

📑 Interesting Topics to Write about Machine Learning

1. Investigating Genetic Interactions Through Machine Learning
2. Problems of Human-Like Biases in Machine Learning
3. Malware Classification Using Machine Learning: Knime and Orange
4. Machine Learning for Dynamic Discrete Choice
5. Credit Scoring Application of Machine Learning
6. Two Main Sub-Fields of Music Machine Learning: Music Information Retrieval and Generative Music
7. Software Reliability Prediction Using Machine Learning Techniques
8. The Role of Machine Learning in Clinical Research
9. Computational Learning Theory and Statistical Learning Theory in Machine Learning
10. Fundamentals and Exchange Rate Forecastability With Simple Machine Learning Methods
11. Nowcasting New Zealand GDP Using Machine Learning Algorithms
12. Machine Learning vs. Physics-Based Modeling for Real-Time Irrigation Management
13. Exploiting the Sports-Betting Market Using Machine Learning
14. Machine Learning: History and Relationships to Other Fields
15. Supervised Machine Learning: Regression and Classification
16. Machine Learning Models for the Classification of Sleep Deprivation Induced Performance Impairment
17. Orthogonal Machine Learning: Power and Limitations
18. Financial Time Series Data Processing for Machine Learning
19. Machine Learning Approaches for Myocardial Motion and Deformation Analysis
20. Machine Learning for Set-Identified Linear Models