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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...
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...

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....
Linear Control System Analysis and Design with MATLAB® (Automation and Control Engineering)
Linear Control System Analysis and Design with MATLAB® (Automation and Control Engineering)

Thoroughly classroom-tested and proven to be a valuable self-study companion, Linear Control System Analysis and Design: Sixth Edition provides an intensive overview of modern control theory and conventional control system design using in-depth explanations, diagrams, calculations, and tables.

Keeping mathematics...

Probability and Algorithms
Probability and Algorithms

Some of the hardest computational problems have been successfully attacked through the use of probabilistic algorithms, which have an element of randomness to them. Concepts from the field of probability are also increasingly useful in analyzing the performance of algorithms, broadening our understanding beyond that provided by the...

Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks
Applied Deep Learning: A Case-Based Approach to Understanding Deep Neural Networks

Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and...

Applied Econometrics with R (Use R!)
Applied Econometrics with R (Use R!)

Here is the first book on applied econometrics using the R system for statistical computing and graphics. It presents hands-on examples for a wide range of models, from classical linear regression models for cross-section to recent semiparametric extensions.

R is a language and environment for data analysis and
...
Building WordPress Themes from Scratch
Building WordPress Themes from Scratch

Walk through the steps you need to build your very own WordPress theme! Included with the book is a WordPress theme and other necessary files, so roll up your sleeves and let Joe take you through the process explaining what you need to do - and why you’re doing it - every step of the way. Hi, I’m Joe, the author of Building...

Dynamic Programming for Impulse Feedback and Fast Controls: The Linear Systems Case (Lecture Notes in Control and Information Sciences)
Dynamic Programming for Impulse Feedback and Fast Controls: The Linear Systems Case (Lecture Notes in Control and Information Sciences)
Dynamic Programming for Impulse Feedback and Fast Controls offers a description of feedback control in the class of impulsive inputs. This book deals with the problem of closed-loop impulse control based on generalization of dynamic programming techniques in the form of variational inequalities of the...
Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition
Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.

Key Features

  • Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow
  • Explore deep neural...
Automatic Control of Atmospheric and Space Flight Vehicles: Design and Analysis with MATLAB® and Simulink® (Control Engineering)
Automatic Control of Atmospheric and Space Flight Vehicles: Design and Analysis with MATLAB® and Simulink® (Control Engineering)
The main purpose of writing this book is to present a unified approach for automatic control of atmospheric and space flight vehicles. Such an outlook has become more necessary nowthan ever,with the advent of aerospace vehicleswhose singlemission covers operation as aircraft, rocket, and spacecraft at various instants....
Scientific Computing with MATLAB and Octave (Texts in Computational Science and Engineering)
Scientific Computing with MATLAB and Octave (Texts in Computational Science and Engineering)

This textbook is an introduction to Scientific Computing, in which several numerical methods for the computer-based solution of certain classes of mathematical problems are illustrated. The authors show how to compute the zeros or the integrals of continuous functions, solve linear systems, approximate functions using polynomials and...

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