2 Plamen Parvanov Angelov
Handbook On Computational Intelligence (In 2 Volumes)
商品説明：With the Internet, the proliferation of Big Data, and autonomous systems, mankind has entered into an era of 'digital obesity'. In this century, computational intelligence, such as thinking machines, have been brought forth to process complex human problems in a wide scope of areas ー from social sciences, economics and biology, medicine and social networks, to cyber security.The Handbook of Comput...
3 Michael Munn/David Pitman
Explainable AI for Practitioners
商品説明：Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best...
4 Frank Millstein
Deep Learning with Keras: Beginner’s Guide to Deep Learning with Keras
商品説明：This book will introduce you to various supervised and unsupervised deep learning algorithms like the multilayer perceptron, linear regression and other more advanced deep convolutional and recurrent neural networks. You will also learn about image processing, handwritten recognition, object recognition and much more.Furthermore, you will get familiar with recurrent neural networks like LSTM and G...
6 Giuseppe Bonaccorso
Hands-On Unsupervised Learning with Python
商品説明：Discover the skill-sets required to implement various approaches to Machine Learning with Python Key Features Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more Build your own neural network models using modern Python libraries Practical examples show you how to implement different machine learning and deep learning techniques Book Description Un...
7 Raghava Shankar/Srikanth RC cherukupalli-M.TECH
商品説明：Artificial Nеurаl Nеtwоrkѕ (ANNѕ) аrе biоlоgiсаllу inspired. Specifically, thеу bоrrоw ideas frоm thе mаnnеr in whiсh the humаn brаin wоrkѕ. The humаn brаin iѕ соmроѕеd оf special сеllѕ саllеd nеurоnѕ. Eѕtimаtеѕ оf thе numbеr оf nеurоnѕ in a humаn brаin cover a widе rаngе (up tо 150 billion), аnd thеrе are mоrе thаn a hundrеd diffеrеnt kinds оf nеurоnѕ, separated intо groups called networks. Eасh ...
8 Dario Mazzeo
Intelligenza artificiale: classificare la corrispondenza
商品説明：Questo lavoro prende in esame la corrispondenza di un'Organizzazione, per creare un'intelligenza artificiale capace di riconoscere il messaggio ricevuto ed attribuirlo ad un ufficio di competenza. Dopo un primo studio della problematica, verranno proposte le varie fasi implementative in linguaggio Perl, che permetteranno al lettore di realizzare una rete neurale artificiale facilmente integrabile ...
9 Robert Laganiere/David Millan Escriva
OpenCV 4 Computer Vision Application Programming Cookbook
商品説明：Discover interesting recipes to help you understand the concepts of object detection, image processing, and facial detection Key Features Explore the latest features and APIs in OpenCV 4 and build computer vision algorithms Develop effective, robust, and fail-safe vision for your applications Build computer vision algorithms with machine learning capabilities Book Description OpenCV is an image ...
10 Jojo Moolayil/Karthik Ramasubramanian
Applied Supervised Learning with R
商品説明：Learn the ropes of supervised machine learning with R by studying popular real-world use-cases, and understand how it drives object detection in driver less cars, customer churn, and loan default prediction. Key Features Study supervised learning algorithms by using real-world datasets Fine tune optimal parameters with hyperparameter optimization Select the best algorithm using the model evaluati...
11 Marcus Du Sautoy
The Creativity Code
商品説明：“A brilliant travel guide to the coming world of AI.” ーJeanette Winterson What does it mean to be creative? Can creativity be trained? Is it uniquely human, or could AI be considered creative? Mathematical genius and exuberant polymath Marcus du Sautoy plunges us into the world of artificial intelligence and algorithmic learning in this essential guide to the future of creativity. He considers the...
13 Gaetano Francesco Anastasi
I computer sanno di essere più intelligenti di noi?
商品説明：I computer odierni sono così tanto intelligenti da essere più bravi di noi in una partita a scacchi o nel giocare ad un videogame. Ma essi sanno di essere così intelligenti? Hanno coscienza di sé e degli altri? Sono capaci di interiorizzare le esperienze del mondo circostante? Scopo di questo saggio è appunto quello di analizzare il rapporto tra intelligenza artificiale e coscienza artificiale, ce...
14 Neil Wilkins
Robotics: What Beginners Need to Know about Robotic Process Automation, Mobile Robots, Artificial Intelligence, Machine Learning, Autonomous Vehicles, Speech Recognition, Drones, and Our Future
商品説明：Are you curious about robotics? Perhaps you want to take advantage of robot-based technology for your business or household? Or you simply want to know how artificially intelligent machines, drone technology and self-driving vehicles will shape the coming times? If you want to learn the basics of artificial intelligence and modern robotics, then keep reading! Robotics are slowly creeping into our ...
15 Denis Rothman
Hands-On Explainable AI (XAI) with Python
商品説明：Resolve the black box models in your AI applications to make them fair, trustworthy, and secure. Familiarize yourself with the basic principles and tools to deploy Explainable AI (XAI) into your apps and reporting interfaces. Key Features Learn explainable AI tools and techniques to process trustworthy AI results Understand how to detect, handle, and avoid common issues with AI ethics and bias In...
16 Claudio Stamile/Aldo Marzullo/Enrico Deusebio
Graph Machine Learning
商品説明：Build machine learning algorithms using graph data and efficiently exploit topological information within your models Key Features Implement machine learning techniques and algorithms in graph data Identify the relationship between nodes in order to make better business decisions Apply graph-based machine learning methods to solve real-life problems Book Description Graph Machine Learning will i...
17 Indra den Bakker
Python Deep Learning Cookbook
商品説明：Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide About This Book Practical recipes on training different neural network models and tuning them for optimal performance Use Python frameworks like TensorFlow, Caffe, Keras, Theano for Natural Language Processing, Computer Vision, and more A hands-on guide covering the common as w...
18 Susana Guzman/Bo Wang/Cristian Mitroi
Neural Search - From Prototype to Production with Jina
商品説明：Implement neural search systems on the cloud by leveraging Jina design patterns Key Features Identify the different search techniques and discover applications of neural search Gain a solid understanding of vector representation and apply your knowledge in neural search Unlock deeper levels of knowledge of Jina for neural search Book Description Search is a big and ever-growing part of the tech ...
19 Kence Anderson
Designing Autonomous AI
商品説明：Early rules-based artificial intelligence demonstrated intriguing decision-making capabilities but lacked perception and didn't learn. AI today, primed with machine learning perception and deep reinforcement learning capabilities, can perform superhuman decision-making for specific tasks. This book shows you how to combine the practicality of early AI with deep learning capabilities and industrial...
20 Pedro Domingos
The Master Algorithm
商品説明：**Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own** In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm,...