Showing results for "subhasis das"
Showing 1 - 3 of 3 Results
Adult content is visible.
Artificial Intelligence in Textile Engineering
Basic Concepts and Applications
2024
EN
Accessible
Artificial Intelligence in Textile Engineering explains Artificial Intelligence techniques from first principles in the perfect way for textiles materials scientists and engineers.Advances in Artificial Intelligence technology have made a substantial impact across the textiles supply chain, making products more efficient, flexible and reliable. In this book techniques such as artificial neural network, support vector machine, fuzzy logic, rough set, evolutionary algorithm, and hybrid intel...
2023
EN
Polymeric materials play an essential and ubiquitous role in many fields including structural and packaging materials, drug development, tissue engineering, wastewater treatment, pollutant removal, separation, water purification, smart agriculture, and even road and building construction. This book contains eleven comprehensive chapters covering topics from deriving polymers from natural resources or wastes to developing novel functional polymeric materials in the form of membranes, hydrog...
Advances in Soil Microbiology: Recent Trends and Future Prospects
Volume 1: Soil-Microbe Interaction
- Series -
- Biomedical and Life Sciences (R0)
2018
EN
This book presents a comprehensive collection of articles illustrating the importance of microbial community structure and function for ecosystem sustainability and environmental reclamation. It addresses a diverse range of topics, including microbial diversity, physiology, genomics, ecosystem function, interaction, metabolism, and the fruitful use of microbial communities for crop productivity and environmental remediation.In addition, the book explores issues ranging from general...
People who read this also enjoyed
Advanced Deep Learning with Python
Design and implement advanced next-generation AI solutions using TensorFlow and PyTorch
2019
EN
Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystemKey FeaturesGet to grips with building faster and more robust deep learning architecturesInvestigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorchApply deep neural networks (DNNs) to computer vision proble...
2021
EN
The increasing environmental and health concerns owing to the use of large quantities of water and hazardous chemicals in conventional textile finishing processes has lead to the design and development of new dyeing strategies and technologies.Sustainable Practices in the Textile Industry comprises 13 chapters from various research areas dealing with the application of different sustainable technologies for enhancing the dyeing and comfort properties of textile materials w...
Fundamentals of Deep Learning
Designing Next-Generation Machine Intelligence Algorithms
2022
EN
We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception to power our push toward creating self-driving vehicles, defeating human experts at a variety of difficult games including Go, and even generating essays with shockingly coherent prose. But deciphering these breakthroughs often takes a PhD in machine learning and mathematics.The updated second edition of this book describes the intuition behind these innovations without jargon or comple...
2014
EN
Accessible
Industrial Wastewater Treatment, Recycling and Reuse is an accessible reference to assist you when handling wastewater treatment and recycling. It features an instructive compilation of methodologies, including advanced physico-chemical methods and biological methods of treatment. It focuses on recent industry practices and preferences, along with newer methodologies for energy generation through waste. The book is based on a workshop run by the Indus MAGIC program of CSIR, India. It cover...
The Art of Randomness
Randomized Algorithms in the Real World
2024
EN
Harness the power of randomness (and Python code) to solve real-world problems in fun, hands-on experiments—from simulating evolution to encrypting messages to making machine-learning algorithms!The Art of Randomness is a hands-on guide to mastering the many ways you can use randomized algorithms to solve real programming and scientific problems. You’ll learn how to use randomness to run simulations, hide information, design experiments, and even create ar...
2017
EN
The Handbook of Composites From Renewable Materials comprises a set of 8 individual volumes that brings an interdisciplinary perspective to accomplish a more detailed understanding of the interplay between the synthesis, structure, characterization, processing, applications and performance of these advanced materials. The handbook covers a multitude of natural polymers/ reinforcement/ fillers and biodegradable materials. Together, the 8 volumes total at least 5000 pages and offers...
Think Complexity
Complexity Science and Computational Modeling
2018
EN
Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you’ll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics.Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations.In this updated ...
Energy from Waste
Production and Storage
2022
EN
Accessible
Conversion of waste into value-added products such as energy transforms a potential environmental problem into a sustainable solution. Energy from Waste: Production and Storage focuses on the conversion of waste from various sources for use in energy production and storage applications. It provides the state-of-the-art in developing advanced materials and chemicals for energy applications using wastes and discusses the various treatment processes and technologies.
Advanced Deep Learning with Keras
Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more
2018
EN
Understanding and coding advanced deep learning algorithms with the most intuitive deep learning library in existenceKey FeaturesExplore the most advanced deep learning techniques that drive modern AI resultsImplement deep neural networks, autoencoders, GANs, VAEs, and deep reinforcement learningA wide study of GANs, including Improved GANs, Cross-Domain GANs, and Disentangled Representation GANsBook DescriptionRecent develop...











