Learn IT - Books tags clustering

Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R

Apress, 2018

Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in Excel so...

Recent Trends in Signal and Image Processing: Proceedings of ISSIP 2018 (Advances in Intelligent Systems and Computing (922))

Springer, 2019

This book presents fascinating, state-of-the-art research findings in the field of signal and image processing. It includes conference papers covering a wide range of signal processing applications involving filtering, encoding, classification, segmentation, clustering, feature extraction, denoising, watermarking, object recognition,...

Soft Computing for Problem Solving: SocProS 2018, Volume 2 (Advances in Intelligent Systems and Computing)

Springer, 2019

This two-volume book presents the outcomes of the 8th International Conference on Soft Computing for Problem Solving, SocProS 2018. This conference was a joint technical collaboration between the Soft Computing Research Society, Liverpool Hope University (UK), and Vellore Institute of Technology (India), and brought together researchers,...

Hybrid Imaging and Visualization: Employing Machine Learning with Mathematica - Python

Springer, 2019

The book introduces the latest methods and algorithms developed in machine and deep learning (hybrid symbolic-numeric computations, robust statistical techniques for clustering and eliminating data as well as convolutional neural networks) dealing not only with images and the use of computers, but also their applications to visualization tasks...

Challenges in Social Network Research: Methods and Applications (Lecture Notes in Social Networks)

Springer, 2019

The book includes both invited and contributed chapters dealing with advanced methods and theoretical development for the analysis of social networks and applications in numerous disciplines. Some authors explore new trends related to network measures, multilevel networks and clustering on networks, while other contributions deepen...

Information Retrieval: Data Structures and Algorithms

Prentice Hall, 1992

Information retrieval is a sub-field of computer science that deals with the automated storage and retrieval of documents. Providing the latest information retrieval techniques, this guide discusses Information Retrieval data structures and algorithms, including implementations in C. Aimed at software engineers building systems with...

Machine Learning with PySpark: With Natural Language Processing and Recommender Systems

Apress, 2018

Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges. This book starts with the fundamentals of Spark and its evolution and then covers the entire spectrum of traditional machine learning algorithms along...

Practical Machine Learning with Python: A Problem-Solver's Guide to Building Real-World Intelligent Systems

Apress, 2017

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner....

Mastering TensorFlow 1.x: Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

Packt Publishing, 2018

Build, scale, and deploy deep neural network models using the star libraries in Python

Key Features

Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras

Build, deploy, and scale end-to-end deep neural network models in a production...

Data Mining Algorithms in C++: Data Patterns and Algorithms for Modern Applications

Apress, 2017

Discover hidden relationships among the variables in your data, and learn how to exploit these relationships. This book presents a collection of data-mining algorithms that are effective in a wide variety of prediction and classification applications. All algorithms include an intuitive explanation of operation, essential...

Scala Machine Learning Projects: Build real-world machine learning and deep learning projects with Scala

Packt Publishing, 2018

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming.

Key Features

Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j

...

Temporal Data Mining (Chapman & Hall/CRC Data Mining and Knowledge Discovery)

CRC Press, 2010

Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business organizations have increased the importance of temporal information in data today.

From basic data mining concepts to state-of-the-art advances, Temporal Data Mining covers...

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