Bøker av Pooja Sharma

Explore the world of Artificial Intelligence with a deep understanding of Machine Learning concepts and algorithmsKEY FEATURES ¿ A detailed study of mathematical concepts, Machine Learning concepts, and techniques.¿ Discusses methods for evaluating model performances and interpreting results.¿ Explores all types of Machine Learning (supervised, unsupervised, reinforcement, association rule mining, artificial neural network) in detail.DESCRIPTION "Simplified Machine Learning" is a comprehensive guide that navigates readers through the intricate landscape of Machine Learning, offering a balanced blend of theory, algorithms, and practical applications. The first section introduces foundational concepts such as supervised and unsupervised learning, regression, classification, clustering, and feature engineering, providing a solid base in Machine Learning theory. The second section explores algorithms like decision trees, support vector machines, and neural networks, explaining their functions, strengths, and limitations, with a special focus on deep learning, reinforcement learning, and ensemble methods. The book also covers essential topics like model evaluation, hyperparameter tuning, and model interpretability. The final section transitions from theory to practice, equipping readers with hands-on experience in deploying models, building scalable systems, and understanding ethical considerations.WHAT YOU WILL LEARN¿ Solid foundation in Machine Learning principles, algorithms, and methodologies.¿ Implementation of Machine Learning models using popular libraries like NumPy, Pandas, PyTorch, or scikit-learn.¿ Knowledge about selecting appropriate models, evaluating their performance, and tuning hyperparameters.¿ Techniques to pre-process and engineer features for Machine Learning models.¿ To frame real-world problems as Machine Learning tasks and apply appropriate techniques to solve them.WHO THIS BOOK IS FORThis book is designed for a diverse audience interested in Machine Learning, a core branch of Artificial Intelligence. Its intellectual coverage will benefit students, programmers, researchers, educators, AI enthusiasts, software engineers, and data scientists.

Waste-to-Energy: Sustainable Approaches for Emerging Economies presents the latest developments and applications for the conversion of waste into biofuels and other energy products. Divided into two parts, Section I reviews the major sources of solid waste and their management strategies in developing countries, and includes the collection, composition, segregation, and dispersal of various waste streams, as well as the generation of biogas and other value-added products. Section II examines the transformation of waste into biofuels and the management strategies required to efficiently implement waste-to-energy processes. Methods for the production of hydrogen, biomethane, biofuels, and bioenergy, as well as resource recovery are discussed in depth, and mathematical models are provided for anaerobic digestion techniques. The benefits and challenges of waste-to-energy as a waste management strategy are explored through dedicated chapters on the techno-economics, environmental and social regulation, and the operation of WtE plants. The final chapter of the book presents a lifecycle assessment and environmental impact analysis of the technologies and strategies discussed.

Stardust explores what it's like to be young and putting everyone else first. Turning 18 and experiencing everything all at once is scary, to say the least. 'Stardust' knows and understands how youth is the most difficult and magnificent time of your life. Through this book, Pooja hopes you find your safe space and maybe yourself. She believes if her work can help and heal even one person, her purpose would be fulfilled. She looks forward to all of her readers sharing their story as well.