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Articles by Premansh Sharma
Page 6 of 7
How Machine Learning used in Genomics?
The study of genomics has seen an explosion of data in recent years due to breakthroughs in sequencing technology. The study of an organism's whole set of genetic material, including genes and their actions, is known as genomics. The massive volumes of genetic data generated by these technologies present a once-in-a-lifetime chance for researchers to acquire insights into disease causes and design more effective therapies. Unfortunately, evaluating and understanding such massive volumes of data is a difficult process. Machine learning, an artificial intelligence area, has emerged as a potent tool for genomics research. Explanation Machine learning algorithms use statistical models ...
Read MoreUniversities that offer MS/MS+PhD programs in Data Science, Machine Learning
As every company is using data collected by them during their business the amount of data is increasing rapidly and it is crucial to extract information from it to increase the business or find a better solution with the help of data. As a result, there is a growing demand for qualified workers in these industries. A Master of Science (MS), Master of Science+PhD, or Ph.D. in Data Science, Machine Learning, or Big Data can provide students with the theoretical and practical abilities needed to evaluate big data sets and make sound judgments. In this article, we'll take a look ...
Read MoreUnderstanding Machine Learning impact on economic research
Machine learning is a strong tool that has the potential to transform how economists analyze and comprehend economic events. By offering more precise and sophisticated assessments of economic data, machine learning may provide more effective plans and ways for dealing with economic challenges. To fully realize the promise of machine learning in economic research, researchers must address bias and interpretability difficulties, as well as strive to develop more rigorous and transparent machine learning approaches. Impact on Economic Research The capacity of machine learning in economics to handle huge, complicated information is one of its key advantages. Conventional statistical approaches are ...
Read MoreRoadmap to study AI, Machine Learning, and Deep Machine Learning
AI also known as Artificial Intelligence, Machine learning in short written as ML, and deep learning (DL) are a few of the top three fast-emerging, great, and intriguing technological disciplines containing a wide range of implementations i.e. applications like self-driving automobiles and face recognition systems. Because of their complexities, understanding these topics may appear difficult. Yet, success in these domains requires a solid foundation in computer science, mathematics, and statistics. Moreover, familiarity with common libraries and modeling tools is required. This article outlines a learning route for AI, ML, and DL, outlining key ideas, tools, and methodologies. This roadmap ...
Read MoreWhat is corporate fraud detection in machine learning?
Introduction Business fraud is a severe problem that may result in considerable financial loss and reputational harm to an organization. Traditional approaches for detecting fraudulent actions are sometimes time-consuming and manual, rendering them useless in detecting fraudulent activity in real-time. Yet, with increased data availability and developments in machine learning technology, firms now have access to more efficient fraud detection approaches. This article will define corporate fraud detection in machine learning, explain how it works, and discuss the benefits and obstacles of using it. Corporate Frauds Corporate fraud refers to the purposeful and intentional deceit or misrepresentation of financial ...
Read MoreMobile development vs Machine Learning: Best Career Options
Introduction Two of the most promising careers in technology today are mobile development and machine learning. Professionals who are interested in developing novel solutions and pushing the limits of what is conceivable in the technological world will find intriguing prospects in both of these disciplines. Yet, choosing a professional route can be challenging for many people because each choice has its own distinct benefits and drawbacks. In order to assist you to choose which job path is ideal for you, we will examine the advantages and disadvantages of pursuing careers in mobile development and machine learning in this post. Mobile ...
Read MoreWhy should you learn machine learning and artificial intelligence
Introduction Due to the rising need for qualified individuals, interesting job prospects, commercial applications, customization, and innovation, studying machine learning (ML) and artificial intelligence (AI) is becoming more and more crucial. Professionals who can design, construct, and maintain these systems are required as more businesses use AI and ML technology. In addition to providing interesting job prospects across a range of industries, ML and AI may assist organizations in streamlining operations, making data-driven choices, and increasing productivity and profitability. Moreover, ML and AI are at the forefront of technological advancement and may be utilized to tailor client experiences. People can ...
Read MoreWhat is Overfitting and how to avoid it?
Introduction In statistics, the phrase "overfitting" is used to describe a modeling error that happens when a function correlates too tightly to a certain set of data. As a result, overfitting could not be able to fit new data, which could reduce the precision of forecasting future observations. Examining validation measures like accuracy and loss might show overfitting. The validation measures frequently increase until a point at which they level out or start to drop when the model is affected by overfitting. During an upward trend, the model looks for a good match, and once it finds one, the movement ...
Read MoreRelationship between AI and Data
Introduction Artificial intelligence (AI) successfully imitates human cognition and reasoning processes for use in everyday applications. This is frequently observed in cybersecurity with work automation and threat variant prediction. But the fuel that is being provided to any AI system, like a car, is what powers it. However, there is a lot more data than fuel. Therefore, the goal of this article is to clarify the crucial role that data plays in AI. Relationship Between AI and Data Below are a few Relationships Between AI and Data It’s Garbage in and Garbages out An AI system's "output, " the ...
Read MorePandas series Vs. single-column DataFrame
Introduction This article compares and contrasts Python's Pandas library's single-column DataFrames and Pandas Series data structures. The goal of the paper is to clearly explain the two data structures, their similarities and differences. To assist readers in selecting the best alternative for their particular use case, it contains comparisons between the two structures and practical examples on aspects like data type, indexing, slicing, and performance. The essay is appropriate for Python programmers at the basic and intermediate levels who are already familiar with Pandas and wish to get a deeper grasp of these two key data structures. What is Pandas? ...
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