MACHINE LEARNING MASTERY: ALGORITHMS, APPLICATIONS AND INSIGHTS

Dr. Pramod Kumar · Dr. K. K. Baseer · Dr. M. JAHIR PASHA · Dr. Haewon Byeon

२०२३ अगस्ट · Xoffencerpublication

इ-पुस्तक

245

पृष्ठहरू

रेटिङ र रिभ्यूहरूको पुष्टि गरिएको हुँदैन थप जान्नुहोस्

यो इ-पुस्तकका बारेमा

Machine learning is an area of artificial intelligence (AI) that focuses on the development of algorithms and models that allow computers to learn and make predictions or judgments without being explicitly programmed. This is accomplished by teaching the computer to learn from its own experiences. The creation and development of computer systems that are able to automatically analyze and understand complicated data in order to enhance their performance over time is the focus of this field. The foundation of machine learning is the construction of mathematical models that are capable of gaining knowledge from data. These models are educated using a collection of instances that have been labeled. This collection of examples is referred to as the training data, and it includes input features as well as output labels or goal values. Adjusting the model's internal parameters or weights in accordance with the patterns and relationships discovered in the data is what the training process entails. This is done with the intention of achieving a gap that is as narrow as possible between the anticipated outputs and the actual values. Reinforcement learning is a paradigm that entails an agent interacting with an environment and learning to make a series of choices or actions in order to maximize a cumulative reward. This paradigm was developed by Edward de Bono. The agent is provided with feedback in the form of incentives or penalties according to its actions, which teaches it the optimum behavior via the process of trial and error. The methodologies of machine learning are becoming more prevalent in a broad variety of fields and applications. Image and audio recognition, natural language processing, recommendation systems, fraud detection, autonomous cars, and medical diagnostics are just few of the numerous applications that may benefit from AI. Programming languages such as Python and R, in addition to libraries and frameworks such as scikit-learn, TensorFlow, and PyTorch, are often used when it comes to the implementation of machine learning algorithms. These tools offer a comprehensive array of functions and utilities for the preparation of data, as well as for the training, assessment, and deployment of models. Learning via machines is an active topic that is developing at a quick pace because to continuing research and technological breakthroughs. The potential for employing machine learning to tackle difficult issues and promote innovation is continuing to develop as more data becomes accessible and as computer power grows.

लेखकको बारेमा

Dr. Pramod Kumar is Ph. D. in Computer science and Engineering from Sunrise University. He has over 12 years of experience in Education and Industry. He has done M. Tech. in Software Engineering from P.D.M. College of Engineering affiliated to Maharshi Dayanand University, Rohtak. His Area of interest is Software Engineering, Testing and Cloud Computing, Blockchain, Artificial Intelligence, Data Analysis and Cloud Security. He has published numerous research papers in journals of repute. Besides this, he has also attended various national and international conferences. He has also attended various workshops and Faculty Development Programs on research methodology and latest Technology. He is presently working as Associate Professor in Ganga Institute of Technology and Management Kablana, affiliated to M. D. University.

Dr. K. K. Baseer obtained his B. Tech and M. Tech degrees in Computer Science and Engineering from JNTUH, Hyderabad and Ph.D. degree from JNTUA University, Ananthapuramu, India. At present working as an Professor in department of Data Science, School of Computing, Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College), Tirupati, A.P., INDIA. He has more than 15 years of experience in both teaching and industry in the area of Computer Science and Engineering. His areas of interest include Data Science, Software Engineering, Internet of Things (IoT), Block Chain Technology, Cloud Computing and other latest trends in technology. He has filed and published 13 Patents out of which 01 Indian patent got granted and 11 Indian (Under Examination) and 02 International & 01 National Patents (Granted) and published more than 45 papers in International Journals and Conferences. Under his credits published 01 Book and 05 Book chapters. He has attended more than 70 Workshops, FDPs, STTP and Seminars. He has conducted 22 Workshops, Skill Development and FDPs and acted as resource person in different Workshops / FDPs / SDPs for delivered emerging areas such IoT, Data Science, IPR, Research Methodology and in ICT based pedagogy using Moodle Cloud.

Dr. M. JAHIR PASHA obtained his Ph.D. degree in Computer Science & Engineering from JAIN University Bangalore. At present working Professor in department of Computer Science & Engineering, G. Pullaiah College of Engineering and Technology, Kurnool, A.P., India. His areas of Interest include, Software Engineering and other latest trends in technology. He has more than 12 year of experience in both teaching and industry in the area of computer Science and Engineering. Dr M Jahir pasha is a member of IEEE&CSI.

Dr. Haewon Byeon received the DrSc degree in Biomedical Science from Ajou University School of Medicine. Haewon Byeon currently works at the Department of Medical Big Data, Inje University. His recent interests focus on health promotion, AImedicine, and biostatistics. He is currently a member of international committee for a Frontiers in Psychiatry, and an editorial board for World Journal of Psychiatry. Also, He were worked on a 4 projects (Principal Investigator) from the Ministry of Education, the Korea Research Foundation, and the Ministry of Health and Welfare. Byeon has published more than 343 articles and 19 books.

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