Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Information Retrieval: Data Structures and Algorithms
Information Retrieval: Data Structures and Algorithms

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 Algorithms: Popular algorithms for data science and machine learning, 2nd Edition
Machine Learning Algorithms: Popular algorithms for data science and machine learning, 2nd Edition

An easy-to-follow, step-by-step guide for getting to grips with the real-world application of machine learning algorithms

Key Features

  • Explore statistics and complex mathematics for data-intensive applications
  • Discover new developments in EM algorithm, PCA, and bayesian...
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances

Create AI applications in Python and lay the foundations for your career in data science

Key Features

  • Practical examples that explain key machine learning algorithms
  • Explore neural networks in detail with interesting examples
  • Master core AI concepts with...
DevOps with Kubernetes: Accelerating software delivery with container orchestrators
DevOps with Kubernetes: Accelerating software delivery with container orchestrators

Learn to implement DevOps using Docker & Kubernetes.

About This Book

  • Learning DevOps, container, and Kubernetes within one book.
  • Leverage Kubernetes as a platform to deploy, scale, and run containers efficiently.
  • A practical guide towards container management and...
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most...

Machine Learning in Action
Machine Learning in Action

After college I went to work for Intel in California and mainland China. Originally my plan was to go back to grad school after two years, but time flies when you are having fun, and two years turned into six. I realized I had to go back at that point, and I didn’t want to do night school or online learning, I wanted to sit on...

From Curve Fitting to Machine Learning: An Illustrative Guide to Scientific Data Analysis and Computational Intelligence
From Curve Fitting to Machine Learning: An Illustrative Guide to Scientific Data Analysis and Computational Intelligence

The analysis of experimental data is at heart of science from its beginnings. But it was the advent of digital computers in the second half of the 20th century that revolutionized scientific data analysis twofold: Tedious pencil and paper work could be successively transferred to the emerging software applications so sweat and tears...

Machine Learning with PySpark: With Natural Language Processing and Recommender Systems
Machine Learning with PySpark: With Natural Language Processing and Recommender Systems
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...
Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python
Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

About This Book

  • A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices
  • Get to grips with the basics of Predictive...
Learning SciPy for Numerical and Scientific Computing Second Edition
Learning SciPy for Numerical and Scientific Computing Second Edition

Quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy

About This Book

  • Use different modules and routines from the SciPy library quickly and efficiently
  • Create vectors and matrices and learn how to perform standard mathematical operations...
JBoss in Action: Configuring the JBoss Application Server
JBoss in Action: Configuring the JBoss Application Server
JBoss in Action is the first book to focus on teaching readers in detail how to use the JBoss application server. Unlike other titles about JBoss, the authors of JBoss in Action go deeper into the advanced features and configuration of the server. In particular, it focuses on enterprise-class topics, such as high availability,...
R Deep Learning Projects: Master the techniques to design and develop neural network models in R
R Deep Learning Projects: Master the techniques to design and develop neural network models in R

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...
Result Page: 28 27 26 25 24 23 22 21 20 19 
©2019 LearnIT (support@pdfchm.net) - Privacy Policy