This book is an introduction to machine learning, with a strong focus on the mathematics behind the standard algorithms and techniques in the field, aimed at senior undergraduates and early graduate students of Mathematics.
The emphasis of the book is on the question of Why - only if why an algorithm is successful is understood, can it be properly applied, and the results trusted.
Dramatically accelerate the building process of complex models using PyTorch to extract the best performance from any computing environmentKey FeaturesReduce the model-building time by applying optimization techniques and approachesHarness the computing power of multiple devices and machines to boost the training processFocus on model quality by quickly evaluating different model configurationsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThis book, written by an HPC expert with over 25 years of experience, guides you through enhancing model training performance using PyTorch.
State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks.
Get into the world of smart data security using machine learning algorithms and Python librariesKey FeaturesLearn machine learning algorithms and cybersecurity fundamentalsAutomate your daily workflow by applying use cases to many facets of securityImplement smart machine learning solutions to detect various cybersecurity problemsBook DescriptionCyber threats today are one of the costliest losses that an organization can face.
Master effective navigation of neural networks, including convolutions and transformers, to tackle computer vision and NLP tasks using PythonKey FeaturesUnderstand the theory, mathematical foundations and structure of deep neural networksBecome familiar with transformers, large language models, and convolutional networksLearn how to apply them to various computer vision and natural language processing problemsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe field of deep learning has developed rapidly recently and today covers a broad range of applications.
Discover interesting recipes to help you understand the concepts of object detection, image processing, and facial detectionKey FeaturesExplore the latest features and APIs in OpenCV 4 and build computer vision algorithmsDevelop effective, robust, and fail-safe vision for your applicationsBuild computer vision algorithms with machine learning capabilitiesBook DescriptionOpenCV is an image and video processing library used for all types of image and video analysis.
In recent years, complex-valued neural networks have widened the scope of application in optoelectronics, imaging, remote sensing, quantum neural devices and systems, spatiotemporal analysis of physiological neural systems, and artificial neural information processing.
Implement intelligent agents using PyTorch to solve classic AI problems, play console games like Atari, and perform tasks such as autonomous driving using the CARLA driving simulatorKey FeaturesExplore the OpenAI Gym toolkit and interface to use over 700 learning tasksImplement agents to solve simple to complex AI problemsStudy learning environments and discover how to create your ownBook DescriptionMany real-world problems can be broken down into tasks that require a series of decisions to be made or actions to be taken.
Discover the use of graph networks to develop a new approach to data science using theoretical and practical methods with this expert guide using Python, printed in colorKey FeaturesCreate networks using data points and informationLearn to visualize and analyze networks to better understand communitiesExplore the use of network data in both - supervised and unsupervised machine learning projectsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionNetwork analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage.
This book consists of various contributions in conjunction with the keywords "e;reasoning"e; and "e;intelligent systems"e;, which widely covers theoretical to practical aspects of intelligent systems.
Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic.
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 developments in deep learning, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Deep Reinforcement Learning (DRL) are creating impressive AI results in our news headlines - such as AlphaGo Zero beating world chess champions, and generative AI that can create art paintings that sell for over $400k because they are so human-like.
Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with easeKey FeaturesUnderstand 3D data processing with rendering, PyTorch optimization, and heterogeneous batchingImplement differentiable rendering concepts with practical examplesDiscover how you can ease your work with the latest 3D deep learning techniques using PyTorch3DBook DescriptionWith this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time.
Gain practical, recipe-based insights into the world of deep learning using Apache MXNet for flexible and efficient research prototyping, training, and deployment to production.
With so much artificial intelligence (AI) in the headlines, it is no surprise that businesses are scrambling to exploit this exciting and transformative technology.
Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures introduces AI-based Lagrange optimization techniques that can enable more rational engineering decisions for concrete structures while conforming to codes of practice.
Build, train, and deploy intelligent applications using Java librariesKey FeaturesLeverage the power of Java libraries to build smart applicationsBuild and train deep learning models for implementing artificial intelligenceLearn various algorithms to automate complex tasksBook DescriptionArtificial intelligence (AI) is increasingly in demand as well as relevant in the modern world, where everything is driven by technology and data.
A deep dive into the key aspects and challenges of machine learning interpretability using a comprehensive toolkit, including SHAP, feature importance, and causal inference, to build fairer, safer, and more reliable models.
A deep dive into the key aspects and challenges of machine learning interpretability using a comprehensive toolkit, including SHAP, feature importance, and causal inference, to build fairer, safer, and more reliable models.
Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and KerasKey FeaturesGet to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and KerasImplement advanced concepts and popular machine learning algorithms in real-world projectsBuild analytics, computer vision, and neural network projects Book DescriptionMachine learning is transforming the way we understand and interact with the world around us.
Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problemsKey FeaturesMaster supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and moreBuild, deploy, and scale end-to-end deep neural network models in a production environmentBook DescriptionThis Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms.
Metaheuristics for Resource Deployment under Uncertainty in Complex Systems analyzes how to set locations for the deployment of resources to incur the best performance at the lowest cost.
Build a strong foundation of machine learning algorithms in 7 daysKey FeaturesUse Python and its wide array of machine learning libraries to build predictive models Learn the basics of the 7 most widely used machine learning algorithms within a weekKnow when and where to apply data science algorithms using this guideBook DescriptionMachine learning applications are highly automated and self-modifying, and continue to improve over time with minimal human intervention, as they learn from the trained data.
Brain Technology in Augmented Cognition: Current and Future Trends informs engineers interested in human-computer interaction about the current state of augmented cognition.
Edge AI is transforming the way computers interact with the real world, allowing IoT devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations.
Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of natural language processing (NLP), speech, and computer vision tasks.
This volume provides students with the necessary tools to better understand the fields of neurobiological modeling, cluster analysis of proteins and genes.
