Neural Networks 9

Introduction to Intelligent Marketing is a comprehensive guide to advanced marketing automation for marketing strategists, data scientists, product managers, and software engineers. It summarizes va……続きを見る

Artificial intelligence, including machine learning, has emerged as a transformational science and engineering discipline. This book presents AI using a coherent framework to study the design of int……続きを見る

This book covers the field of artificial intelligence and machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is int……続きを見る

"Artificial intelligence" is the buzzword of the day. You've no doubt read your fair share of media hype either proclaiming doom and gloom where robots seize our jobs or prophesying a new utopia whe……続きを見る

The term "Artificial Intelligence" has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact defini……続きを見る

Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natura……続きを見る

Demonstrate fundamentals of Deep Learning and neural network methodologies using Keras 2.xKey FeaturesExperimental projects showcasing the implementation of high-performance deep learning models wit……続きを見る

Create end-to-end systems that can power robots with artificial vision and deep learning techniquesKey FeaturesStudy ROS, the main development framework for robotics, in detailLearn all about convol……続きを見る

Take your neural networks to a whole new level with the simplicity and modularity of Keras, the most commonly used high-level neural networks API.Key FeaturesSolve complex machine learning problems ……続きを見る

***** BUY NOW (will soon return to 12.99$) ***** Are you thinking of learning data science from scratch using Python? (For Beginners) If you are looking for a complete step-by-step guide to data sci……続きを見る

**** ACHETER MAINTENANT (le prix reviendra bientôt à 13.98 euros) ***** Etes-vous un débutant en Data science et Avez-vous envie d’apprendre et de pratiquer le Data Science en utilisant Python ? Si ……続きを見る

Learn the ropes of supervised machine learning with R by studying popular real-world use cases, and understand how it drives object detection in driverless cars, customer churn, and loan default pre……続きを見る

This book covers the issues related to optimization of engineering and management problems using soft computing techniques with an industrial outlook. It covers a broad area related to real life com……続きを見る

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 dif……続きを見る

Implement neural network architectures by building them from scratch for multiple real-world applications.Key FeaturesFrom scratch, build multiple neural network architectures such as CNN, RNN, LSTM……続きを見る

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)……続きを見る

This unique compendium presents a comprehensive and self-contained theory of material development under imperfect information and its applications. The book describes new approaches to synthesis and……続きを見る

Toward Deep Neural Networks: WASD Neuronet Models, Algorithms, and Applications introduces the outlook and extension toward deep neural networks, with a focus on the weights-and-structure determinat……続きを見る

Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering how you can use deep learning models in your software appli……続きを見る

Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks.Key FeaturesTrain your own models for effective prediction, using high-level Keras……続きを見る

Your one-stop guide to learning and implementing artificial neural networks with Keras effectivelyKey FeaturesDesign and create neural network architectures on different domains using KerasIntegrate……続きを見る

Gain expertise in ML techniques with AWS to create interactive apps using SageMaker, Apache Spark, and TensorFlow.Key FeaturesBuild machine learning apps on AWS using SageMaker, Apache Spark, and Te……続きを見る

The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence and Machine Learning.This must-have compendium presents th……続きを見る

Bio-inspired computing (BIC) focuses on the designs and developments of computer algorithms and models based on biological mechanisms and living phenomena. It is now a major subfield of natural comp……続きを見る

Apply modern reinforcement learning and deep reinforcement learning methods using Python and its powerful libraries Key Features Your entry point into the world of artificial intelligence using the……続きを見る

Leverage the power of reward-based training for your deep learning models with PythonKey FeaturesUnderstand Q-learning algorithms to train neural networks using Markov Decision Process (MDP)Study pr……続きを見る

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 com……続きを見る

Understand how machine learning works and get hands-on experience of using R to build algorithms that can solve various real-world problemsKey FeaturesGain a comprehensive overview of different mach……続きを見る

Künstliche Intelligenz und maschinelles Lernen, neuronale Netzwerke und Deep Learning – nichts davon ist wirklich neu. Und doch ist die Zahl der Vorträge und Veröffentlichungen, der Onlinekurse und ……続きを見る

Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features Get to grips with the fundamentals of deep learning and neural networks Use R 3.5 a……続きを見る