Increase the performance of various neural network architectures using NEAT, HyperNEAT, ES-HyperNEAT, Novelty Search, SAFE, and deep neuroevolutionKey FeaturesImplement neuroevolution algorithms to improve the performance of neural network architecturesUnderstand evolutionary algorithms and neuroevolution methods with real-world examplesLearn essential neuroevolution concepts and how they are used in domains including games, robotics, and simulationsBook DescriptionNeuroevolution is a form of artificial intelligence learning that uses evolutionary algorithms to simplify the process of solving complex tasks in domains such as games, robotics, and the simulation of natural processes.
Learn how to use R to apply powerful machine learning methods and gain insight into real-world applications using clustering, logistic regressions, random forests, support vector machine, and more.
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.
Take your machine learning models to the next level by learning how to leverage hyperparameter tuning, allowing you to control the model's finest detailsKey FeaturesGain a deep understanding of how hyperparameter tuning worksExplore exhaustive search, heuristic search, and Bayesian and multi-fidelity optimization methodsLearn which method should be used to solve a specific situation or problemBook DescriptionHyperparameters are an important element in building useful machine learning models.
100 recipes that teach you how to perform various machine learning tasks in the real worldKey Features[*]Understand which algorithms to use in a given context with the help of this exciting recipe-based guide[*]Learn about perceptrons and see how they are used to build neural networks[*]Stuck while making sense of images, text, speech, and real estate?
Think about your data intelligently and ask the right questionsKey FeaturesMaster data cleaning techniques necessary to perform real-world data science and machine learning tasksSpot common problems with dirty data and develop flexible solutions from first principlesTest and refine your newly acquired skills through detailed exercises at the end of each chapterBook DescriptionData cleaning is the all-important first step to successful data science, data analysis, and machine learning.
Comprehensive recipes to give you valuable insights on Transformers, Reinforcement Learning, and moreKey FeaturesDeep Learning solutions from Kaggle Masters and Google Developer ExpertsGet to grips with the fundamentals including variables, matrices, and data sourcesLearn advanced techniques to make your algorithms faster and more accurateBook DescriptionThe independent recipes in Machine Learning Using TensorFlow Cookbook will teach you how to perform complex data computations and gain valuable insights into your data.
This groundbreaking book transcends traditional machine learning approaches by introducing information measurement methodologies that revolutionize the field.
Perform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and PollyKey FeaturesExplore popular machine learning and deep learning services with their underlying algorithmsDiscover readily available artificial intelligence(AI) APIs on AWS like Vision and Language ServicesDesign robust architectures to enable experimentation, extensibility, and maintainability of AI appsBook DescriptionFrom data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS.
A practical guide to mastering reinforcement learning algorithms using KerasKey FeaturesBuild projects across robotics, gaming, and finance fields, putting reinforcement learning (RL) into actionGet to grips with Keras and practice on real-world unstructured datasetsUncover advanced deep learning algorithms such as Monte Carlo, Markov Decision, and Q-learningBook DescriptionReinforcement learning has evolved a lot in the last couple of years and proven to be a successful technique in building smart and intelligent AI networks.
Incorporate intelligence to your data-driven business insights and high accuracy business solutionsKey FeaturesExplore IBM Watson capabilities such as Natural Language Processing (NLP) and machine learningBuild projects to adopt IBM Watson across retail, banking, and healthcareLearn forecasting, anomaly detection, and pattern recognition with ML techniquesBook DescriptionIBM Watson provides fast, intelligent insight in ways that the human brain simply can't match.
Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examplesKey FeaturesAI-based examples to guide you in designing and implementing machine intelligenceBuild machine intelligence from scratch using artificial intelligence examplesDevelop machine intelligence from scratch using real artificial intelligenceBook DescriptionAI has the potential to replicate humans in every field.
Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and librariesKey FeaturesLearn, develop, and deploy advanced reinforcement learning algorithms to solve a variety of tasksUnderstand and develop model-free and model-based algorithms for building self-learning agentsWork with advanced Reinforcement Learning concepts and algorithms such as imitation learning and evolution strategiesBook DescriptionReinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements.
Explore various Generative Adversarial Network architectures using the Python ecosystemKey FeaturesUse different datasets to build advanced projects in the Generative Adversarial Network domainImplement projects ranging from generating 3D shapes to a face aging applicationExplore the power of GANs to contribute in open source research and projectsBook DescriptionGenerative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data.
Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in PythonKey FeaturesDiscover neural network architectures (like CNN and LSTM) that are driving recent advancements in AIBuild expert neural networks in Python using popular libraries such as KerasIncludes projects such as object detection, face identification, sentiment analysis, and moreBook DescriptionNeural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more.
Skip the theory and get the most out of Tensorflow to build production-ready machine learning modelsKey FeaturesExploit the features of Tensorflow to build and deploy machine learning modelsTrain neural networks to tackle real-world problems in Computer Vision and NLPHandy techniques to write production-ready code for your Tensorflow modelsBook DescriptionTensorFlow is an open source software library for Machine Intelligence.
Learn how to use R to apply powerful machine learning methods and gain insight into real-world applications using clustering, logistic regressions, random forests, support vector machine, and more.
Comprehensive recipes to give you valuable insights on Transformers, Reinforcement Learning, and moreKey FeaturesDeep Learning solutions from Kaggle Masters and Google Developer ExpertsGet to grips with the fundamentals including variables, matrices, and data sourcesLearn advanced techniques to make your algorithms faster and more accurateBook DescriptionThe independent recipes in Machine Learning Using TensorFlow Cookbook will teach you how to perform complex data computations and gain valuable insights into your data.
Become a master at penetration testing using machine learning with PythonKey Features Identify ambiguities and breach intelligent security systems Perform unique cyber attacks to breach robust systems Learn to leverage machine learning algorithmsBook DescriptionCyber security is crucial for both businesses and individuals.
In the rapidly evolving landscape of finance and governance, the integration of blockchain technology and artificial intelligence is reshaping the way we perceive and interact with traditional systems.
Leverage the full potential of SAS to get unique, actionable insights from your dataKey FeaturesBuild enterprise-class data solutions using SAS and become well-versed in SAS programmingWork with different data structures, and run SQL queries to manipulate your dataExplore essential concepts and techniques with practical examples to confidently pass the SAS certification examBook DescriptionSAS is one of the leading enterprise tools in the world today when it comes to data management and analysis.
Leverage the power of deep learning and Keras to develop smarter and more efficient data modelsKey FeaturesUnderstand different neural networks and their implementation using KerasExplore recipes for training and fine-tuning your neural network modelsPut your deep learning knowledge to practice with real-world use-cases, tips, and tricksBook DescriptionKeras has quickly emerged as a popular deep learning library.
Leverage the power of Java and its associated machine learning libraries to build powerful predictive modelsKey FeaturesSolve predictive modeling problems using the most popular machine learning Java libraries Explore data processing, machine learning, and NLP concepts using JavaML, WEKA, MALLET librariesPractical examples, tips, and tricks to help you understand applied machine learning in JavaBook DescriptionAs the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations.
A solution-based guide to put your deep learning models into production with the power of Apache SparkKey FeaturesDiscover practical recipes for distributed deep learning with Apache SparkLearn to use libraries such as Keras and TensorFlow Solve problems in order to train your deep learning models on Apache SparkBook DescriptionWith deep learning gaining rapid mainstream adoption in modern-day industries, organizations are looking for ways to unite popular big data tools with highly efficient deep learning libraries.
A solution-based guide to put your deep learning models into production with the power of Apache SparkKey FeaturesDiscover practical recipes for distributed deep learning with Apache SparkLearn to use libraries such as Keras and TensorFlow Solve problems in order to train your deep learning models on Apache SparkBook DescriptionWith deep learning gaining rapid mainstream adoption in modern-day industries, organizations are looking for ways to unite popular big data tools with highly efficient deep learning libraries.
Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today's computational world.
Perform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and PollyKey FeaturesExplore popular machine learning and deep learning services with their underlying algorithmsDiscover readily available artificial intelligence(AI) APIs on AWS like Vision and Language ServicesDesign robust architectures to enable experimentation, extensibility, and maintainability of AI appsBook DescriptionFrom data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS.
Deep Learning for EEG-Based Brain-Computer Interfaces is an exciting book that describes how emerging deep learning improves the future development of Brain-Computer Interfaces (BCI) in terms of representations, algorithms and applications.
Advance your skills in efficient data analysis and data processing using the powerful tools of Scala, Spark, and HadoopKey Features[*] This is a primer on functional-programming-style techniques to help you efficiently process and analyze all of your data[*] Get acquainted with the best and newest tools available such as Scala, Spark, Parquet and MLlib for machine learning[*] Learn the best practices to incorporate new Big Data machine learning in your data-driven enterprise to gain future scalability and maintainabilityBook DescriptionSince the advent of object-oriented programming, new technologies related to Big Data are constantly popping up on the market.
Explore the web and make smarter predictions using PythonKey Features[*]Targets two big and prominent markets where sophisticated web apps are of need and importance.
Solve challenging data science problems by mastering cutting-edge machine learning techniques in PythonKey Features[*] Resolve complex machine learning problems and explore deep learning[*] Learn to use Python code for implementing a range of machine learning algorithms and techniques[*] A practical tutorial that tackles real-world computing problems through a rigorous and effective approachBook DescriptionDesigned to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential.
