Our website is made possible by displaying online advertisements to our visitors.
Please consider supporting us by disabling your ad blocker.

Download links will be available after you disable the ad blocker and reload the page.
Showing: 31-40 results of 8819

How Strategy Works in an Interconnected, Automated World Leaders already know that the classic approach to strategy--analyze, plan, execute--is losing relevance. But they don't yet know what replaces it. As everyone and everything becomes more interconnected and digitized, how do you operate, compete, and win? Ming Zeng, the former Chief of Staff and strategy adviser to Alibaba Group's founder Jack Ma, explains how the latest... more...

About the book: In Computer Sciences there is currently a gold rush mood due to a new field called "Deep Learning". But what is Deep Learning? This book is an introduction to Neural Networks and the most important Deep Learning model - the Convolutional Neural Network model including a description of tricks that can be used to train such models more quickly. We start with the biological role model: the Neuron. About 86.000.000.000 of these simple... more...

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 simulator Key Features Explore the OpenAI Gym toolkit and interface to use over 700 learning tasks Implement agents to solve simple to complex AI problems Study learning environments and discover how to create your own Book Description Many... more...

Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various... more...

5 real-world projects to help you master deep learning concepts Key Features Master the different deep learning paradigms and build real-world projects related to text generation, sentiment analysis, fraud detection, and more Get to grips with R's impressive range of Deep Learning libraries and frameworks such as deepnet, MXNetR, Tensorflow, H2O, Keras, and text2vec Practical projects that show you how to implement... more...


Explore the current state of the production, processing, and manufacturing industries and discover what it will take to achieve re-industrialization of the former industrial powerhouses that can counterbalance the benefits of cheap labor providers dominating the industrial sector. This book explores the potential for the Internet of Things (IoT), Big Data, Cyber-Physical Systems (CPS), and Smart Factory technologies to replace the... more...

This book constitutes the refereed proceedings of the 19th International Conference on Theory and Applications of Satisfiability Testing, SAT 2016, held in Bordeaux, France, in July 2016. The 31 regular papers, 5 tool papers presented together with 3 invited talks were carefully reviewed and selected from 70 submissions. The papers address different aspects of SAT, including complexity, satisfiability solving,... more...

Key Features Over 100 recipes on mathematical theory of each deep learning algorithm , its implementation and a bunch of related techniques for using them Provides explanation with examples covering deep learning algorithms using popular python frameworks like TensorFlow, Caffe, Keras, Theano Your ideal companion to train models involving neural networks problem and tuning it for a completely different problem, and getting... more...

Focusing on up-to-date artificial intelligence models to solve building energy problems, Artificial Intelligence for Building Energy Analysis reviews recently developed models for solving these issues, including detailed and simplified engineering methods, statistical methods, and artificial intelligence methods. The text also simulates energy consumption profiles for single and multiple buildings. Based on these datasets, Support Vector Machine (SVM)... more...

Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate "rules of thumb." A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech... more...