Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Applied Statistics: Theory and Problem Solutions with R
Applied Statistics: Theory and Problem Solutions with R

Instructs readers on how to use methods of statistics and experimental design with R software 

Applied statistics covers both the theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce, and research. It proceeds...

A Beginner's Guide to R (Use R!)
A Beginner's Guide to R (Use R!)

Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum.

...
Data Analytics for Engineering and Construction  Project Risk Management (Risk, Systems and Decisions)
Data Analytics for Engineering and Construction Project Risk Management (Risk, Systems and Decisions)

This book provides a step-by-step guidance on how to implement analytical methods in project risk management. The text focuses on engineering design and construction projects and as such is suitable for graduate students in engineering, construction, or project management, as well as practitioners aiming to develop, improve,...

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...
Introduction to Statistics Through Resampling Methods and R
Introduction to Statistics Through Resampling Methods and R
A highly accessible alternative approach to basic statistics Praise for the First Edition:  "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."?Technometrics 

Written in a
...
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications...
Applied Bayesian Statistics: With R and OpenBUGS Examples (Springer Texts in Statistics)
Applied Bayesian Statistics: With R and OpenBUGS Examples (Springer Texts in Statistics)

This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been used by students of different levels and disciplines, including advanced undergraduates studying Mathematics and Statistics and students in graduate programs  in Statistics, Biostatistics, Engineering, Economics,...

Forest Analytics with R: An Introduction (Use R!)
Forest Analytics with R: An Introduction (Use R!)
R is an open-source and free software environment for statistical computing and graphics. R compiles and runs on a wide variety of UNIX platforms (e.g., GNU/Linux and FreeBSD), Windows, and Mac OSX. Since the late 1990s, R has been developed by hundreds of contributors and new capabilities are added each month....
Data Science Fundamentals for Python and MongoDB
Data Science Fundamentals for Python and MongoDB
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This example-driven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate....
Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks
Deep Learning By Example: A hands-on guide to implementing advanced machine learning algorithms and neural networks

Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner

Key Features

  • Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide
  • Train different types of neural networks using Tensorflow for...
Mathematical Statistics with Resampling and R
Mathematical Statistics with Resampling and R
This book bridges the latest software applications with the benefits of modern resampling techniques

Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. This groundbreaking book shows how to apply modern resampling techniques...

Instant HTML5 2D Platformer
Instant HTML5 2D Platformer

Learn how to develop a 2D HTML5 platformer that is capable of running in modern browsers

Overview

  • Learn something new in an Instant! A short, fast, focused guide delivering immediate results
  • Learn about HTML5 2D game development and how to create your own HTML5 games
  • ...
Result Page: 73 72 71 70 69 68 67 66 65 64 
©2019 LearnIT (support@pdfchm.net) - Privacy Policy