The migration from the analog to the digital world was viewed as a major milestone in the management of data. The use of machine learning and data analytics can be applied to cyber security.
It can lead to severe harm and can be recovered by applying extra cost, time, and effort to remove the viruses from the computers. The change in leadership led to a restructuring of the entity, […]
Therefore, the clarification of the basic processes of the different topics of medical imaging, including X-rays, MRIs, and CT scans, will provide context for our investigation of machine learning in the next section.
The body of the article is presented in the form of a literature review study, which estimates the progress of ML implementation in the sphere of cardiology.
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.
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.
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 […]
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.
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 […]
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 […]
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.
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.
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 […]
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 […]
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 […]
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.
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.
The findings clearly match those of Wundari et al.and Deriche et al.that innovative seizure detection techniques are more accurate in detecting epilepsy.
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 […]
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 […]
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.
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 […]
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 […]
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.
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.
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
Ethical Questions of Machine Learning: Racist Hiring Policies And Increasing Profits
Machine Learning Approaches: Supervised, Unsupervised, and Reinforcement Learning
How Does Artificial Intelligence Use Machine Learning
The Limitations of Machine Learning in an Enterprise Setting
Analysis of Machine Learning Algorithm for Facial Expression Recognition
Large Data Sets and Machine Learning: Applications to Statistical Arbitrage
Can Machine Learning Approaches Lead Toward Personalized Cognitive Training
Machine Learning for Predicting Vaccine Immunogenicity
Urban Data Streams and Machine Learning: A Case of Swiss Real Estate Market
The Most Common Risk in Machine Learning: Protect Sensitive or Confidential Data
Machine Learning for Solar Accessibility: Implications for Low-Income Solar Expansion and Profitability
Understanding the Security Implications of the Machine-Learning Supply Chain
Machine Learning for Detection of Safety Signals: Example of Nivolumab and Docetaxel
Optimal Taxation and Insurance Using Machine Learning: Learning Sufficient Statistics and Beyond
Machine Learning for Quantitative Finance: Fast Derivative Pricing, Hedging, and Fitting
Accelerating the Branch-And-Price Algorithm Using Machine Learning
Machine Learning Versus Econometrics: Prediction of Box Office
How Netflix Uses Machine Learning
Machine Learning-Based Algorithm for Circularity Analysis
The Uses of Social Theory in Machine Learning for Social Science
📑 Interesting Topics to Write about Machine Learning
Investigating Genetic Interactions Through Machine Learning
Problems of Human-Like Biases in Machine Learning
Malware Classification Using Machine Learning: Knime and Orange
Machine Learning for Dynamic Discrete Choice
Credit Scoring Application of Machine Learning
Two Main Sub-Fields of Music Machine Learning: Music Information Retrieval and Generative Music
Software Reliability Prediction Using Machine Learning Techniques
The Role of Machine Learning in Clinical Research
Computational Learning Theory and Statistical Learning Theory in Machine Learning
Fundamentals and Exchange Rate Forecastability With Simple Machine Learning Methods
Nowcasting New Zealand GDP Using Machine Learning Algorithms
Machine Learning vs. Physics-Based Modeling for Real-Time Irrigation Management
Exploiting the Sports-Betting Market Using Machine Learning
Machine Learning: History and Relationships to Other Fields
Supervised Machine Learning: Regression and Classification
Machine Learning Models for the Classification of Sleep Deprivation-Induced Performance Impairment
Orthogonal Machine Learning: Power and Limitations
Financial Time Series Data Processing for Machine Learning
Machine Learning Approaches for Myocardial Motion and Deformation Analysis