the Nest of Students

Brian Hahn, Daniel Valentine ... 424 pages - Publisher: Academic Press; 5th edition (January, 2013) ... Language: English - ISBN-10: 0123943981 - ISBN-13: 978-0123943989 ...

The fifth edition of Essential MATLAB for Engineers and Scientists provides a concise, balanced overview of MATLAB's functionality that facilitates independent learning, with coverage of both the fundamentals and applications. The essentials of MATLAB are illustrated throughout, featuring complete coverage of the software's windows and menus. Program design and algorithm development are presented clearly and intuitively, along with many examples from a wide range of familiar scientific and engineering areas. This is an ideal book for a first course on MATLAB or for an engineering problem-solving course using MATLAB, as well as a self-learning tutorial for professionals and students expected to learn and apply MATLAB. Updated with the features of MATLAB R2012b + Expanded discussion of writing functions and scripts + Revised and expanded Part II: Applications + Expanded section on GUIs + More exercises and examples throughout + Companion website for students providing M-files used within the book and selected solutions to end-of-chapter problems.

The topics in this course come from an analysis of real requirements in data scientist job listings from the biggest tech employers. We'll cover the machine learning, AI, and data mining techniques real employers are looking for, including: Deep Learning / Neural Networks (MLP's, CNN's, RNN's) with TensorFlow and Keras + Sentiment analysis + Image recognition and classification + Regression analysis + K-Means Clustering + Principal Component Analysis + Train/Test and cross validation + Bayesian Methods + Decision Trees and Random Forests + Multivariate Regression + Multi-Level Models + Support Vector Machines + Reinforcement Learning + Collaborative Filtering + K-Nearest Neighbor + Bias/Variance Tradeoff + Ensemble Learning + Term Frequency / Inverse Document Frequency + Experimental Design and A/B Tests.

Machine Learning, Classification and Algorithms using MATLAB: Learn to Implement Classification Algorithms In One of the Most Power Tool used by Scientists and Engineer.

 This course is designed to cover one of the most interesting areas of machine learning called classification. I will take you step-by-step in this course and will first cover the basics of MATLAB. Following that we will look into the details of how to use different machine learning algorithms using MATLAB. Specifically, we will be looking at the MATLAB toolbox called statistic and machine learning toolbox. We will implement some of the most commonly used classification algorithms such as K-Nearest Neighbor, Naive Bayes, Discriminant Analysis, Decision Tress, Support Vector Machines, Error Correcting Output Codes and Ensembles. Following that we will be looking at how to cross validate these models and how to evaluate their performances. Intuition into the classification algorithms is also included so that a person with no mathematical background can still comprehend the essential ideas. The following are the course outlines. Segment 1: Grabbing and Importing Dataset + Segment 2: K-Nearest Neighbor + Segment 3: Naive Bayes + Segment 4: Decision Trees + Segment 5: Discriminant Analysis + Segment 6: Support Vector Machines + Segment 7: Error Correcting Output Codes + Segment 8: Classification with Ensembles + Segment 9: Validation Methods + Segment 10: Evaluating Performance.

Mohammed M. Alani, Hissam Tawfik, Mohammed Saeed, Obinna Anya ... 214 pages - Publisher: Springer; 1st edition (July, 2018) ... Language: English - ASIN: B07FP1J69L by Amazon ...

This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery.

Ashfaque Ahmed, Bhanu Prasad ... 475 pages - Publisher: Auerbach Publications; 1st edition (July, 2016) ... Language: English - ISBN-10: 1498737595 - ISBN-13: 978-1498737593 ...

The best way to learn software engineering is by understanding its core and peripheral areas. Foundations of Software Engineering provides in-depth coverage of the areas of software engineering that are essential for becoming proficient in the field. The book devotes a complete chapter to each of the core areas. Several peripheral areas are also explained by assigning a separate chapter to each of them. Rather than using UML or other formal notations, the content in this book is explained in easy-to-understand language. Basic programming knowledge using an object-oriented language is helpful to understand the material in this book. The knowledge gained from this book can be readily used in other relevant courses or in real-world software development environments. This textbook educates students in software engineering principles. It covers almost all facets of software engineering, including requirement engineering, system specifications, system modeling, system architecture, system implementation, and system testing. Emphasizing practical issues, such as feasibility studies, this book explains how to add and develop software requirements to evolve software systems. This book was written after receiving feedback from several professors and software engineers. What resulted is a textbook on software engineering that not only covers the theory of software engineering but also presents real-world insights to aid students in proper implementation. Students learn key concepts through carefully explained and illustrated theories, as well as concrete examples and a complete case study using Java. Source code is also available on the book’s website. The examples and case studies increase in complexity as the book progresses to help students build a practical understanding of the required theories and applications.

Stephen J. Chapman ... 592 pages - Publisher: CL Engineering; 4th edition (November, 2007) ... Language: English - ISBN-10: 049524449X - ISBN-13: 978-0495244493 ...

Emphasizing problem-solving skills throughout this very successful book, Stephen Chapman introduces the MATLAB language and shows how to use it to solve typical technical problems. The book teaches MATLAB as a technical programming language showing students how to write clean, efficient, and well-documented programs. It makes no pretense at being a complete description of all of MATLAB's hundreds of functions. Instead, it teaches students how to locate any desired function with MATLAB's extensive on line help facilities. Overall, students develop problem-solving skills and are equipped for future courses and careers using the power of MATLAB.

Stephen J. Chapman ... 432 pages - Publisher: CL Engineering; 2nd edition (November, 2008) ... Language: English - ISBN-10: 049529568X - ISBN-13: 978-0495295686 ...

Stephen Chapman's Essentials of MATLAB Programming is a successful freshman-level text that is useable in a wide range of courses. This brief text serves two purposes - it teaches how to program using MATLAB as a technical programming language as well as teaching students the basics of computer programming. Using top-down design methodology, the text encourages students to think about the proper design of a program before coding. Problem solving skills as well as the ability to locate desired functions within MATLAB are also presented making this text a useful reference tool.

Machine Learning Classification Algorithms using MatLab [Size: 580 MB] ... This course is designed to cover one of the most interesting areas of machine learning called classification. I will take you step-by-step in this course and will first cover the basics of MATLAB. Following that we will look into the details of how to use different machine learning algorithms using MATLAB. Specifically, we will be looking at the MATLAB toolbox called statistic and machine learning toolbox. We will implement some of the most commonly used classification algorithms such as K-Nearest Neighbor, Naive Bayes, Discriminant Analysis, Decision Tress, Support Vector Machines, Error Correcting Output Codes and Ensembles. Following that we will be looking at how to cross validate these models and how to evaluate their performances. Intuition into the classification algorithms is also included so that a person with no mathematical background can still comprehend the essential ideas. The following are the course outlines.

Table of Contents: - Segment 1: Instructor and Course Introduction - Segment 2: MATLAB Crash Course - Segment 3: Grabbing and Importing Dataset - Segment 4: K-Nearest Neighbor - Segment 5: Naive Bayes - Segment 6: Decision Trees - Segment 7: Discriminant Analysis - Segment 8: Support Vector Machines - Segment 9: Error Correcting Output Codes - Segment 10: Classification with Ensembles - Segment 11: Validation Methods - Segment 12: Evaluating Performance. This course is really good for a beginner. It will help you to start from the ground up and move on to more complicated areas. You receive knowledge from a Ph.D. in Computer science (machine learning) with over 10 years of teaching and research experience.

Stanley B. Lippman, Josée Lajoie ... 1264 pages - Publisher: Addison-Wesley Professional; 3rd edition (April, 1998) ... Language: English - ISBN-10: 0201824701 - ISBN-13: 978-0201824704

A completely rewritten tutorial driven by examples helps the novice C++ programmer solve problems in terms of choice of language features, implementation, and efficiency.

Eugeniy E. Mikhailov ... 266 pages - Publisher: CRC Press; 1st edition (February, 2018) ... Language: English - ISBN-10: 1498738281 - ISBN-13: 978-1498738286 ...

This book offers an introduction to the basics of MATLAB programming to scientists and engineers. The author leads with engaging examples to build a working knowledge, specifically geared to those with science and engineering backgrounds. The reader is empowered to model and simulate real systems, as well as present and analyze everyday data sets. In order to achieve those goals, the contents bypass excessive "under the hood" details, and instead gets right down to the essential, practical foundations for successful programming and modeling. Readers will benefit from the following features: Teaches programming to scientists and engineers using a problem-based approach, leading with illustrative and interesting examples. + Emphasizes a hands-on approach, with "must know" information and minimal technical details. + Utilizes examples from science and engineering to showcase the application of learned concepts on real problems. + Showcases modeling of real systems, gradually advancing from simpler to more challenging problems. + Highlights the practical uses of data processing and analysis in everyday life.

A Boltzmann machine is a network of symmetrically connected, neuron-like units that make stochastic decisions about whether to be on or off. Boltzmann machines have a simple learning algorithm that allows them to discover interesting features that represent complex regularities in the training data. The learning algorithm is very slow in networks with many layers of feature detectors, but it is fast in "restricted Boltzmann machines" that have a single layer of feature detectors. Many hidden layers can be learned efficiently by composing restricted Boltzmann machines, using the feature activations of one as the training data for the next. Boltzmann machines are used to solve two quite different computational problems. For a search problem, the weights on the connections are fixed and are used to represent a cost function. The stochastic dynamics of a Boltzmann machine then allow it to sample binary state vectors that have low values of the cost function. For a learning problem, the Boltzmann machine is shown a set of binary data vectors and it must learn to generate these vectors with high probability. To do this, it must find weights on the connections so that, relative to other possible binary vectors, the data vectors have low values of the cost function. To solve a learning problem, Boltzmann machines make many small updates to their weights, and each update requires them to solve many different search problems.

Narasimha Karumanchi ... 434 pages - Publisher: CareerMonk Plublications; 5th edition (August, 2016) ... Language: English - ISBN-10: 819324527X - ISBN-13: 978-8193245279 ...

A handy guide of sorts for any computer science professional, Data Structures And Algorithms Made Easy: Data Structure And Algorithmic Puzzles is a solution bank for various complex problems related to data structures and algorithms. It can be used as a reference manual by those readers in the computer science industry. The book has around 21 chapters and covers Recursion and Backtracking, Linked Lists, Stacks, Queues,Trees, Priority Queue and Heaps, Disjoint Sets ADT, Graph Algorithms, Sorting, Searching, Selection Algorithms [Medians], Symbol Tables, Hashing, String Algorithms, Algorithms Design Techniques, Greedy Algorithms, Divide and Conquer Algorithms, Dynamic Programming, Complexity Classes, and other Miscellaneous Concepts. Data Structures And Algorithms Made Easy: Data Structure And Algorithmic Puzzles by Narasimha Karumanchi was published in March, and it is coded in C/C++ language. This book serves as guide to prepare for interviews, exams, and campus work. It is also available in Java. In short, this book offers solutions to various complex data structures and algorithmic problems.

John J. Kinney ... 480 pages - Publisher: Wiley; 2nd edition (December, 2014) ... Language: English - ISBN-10: 1118947088 - ISBN-13: 978-1118947081.

Martin H. Trauth ... 427 pages ... Publisher: Springer; 4th edition (February, 2015) ... Language: English - AmazonSIN: B018C2STZU.

MATLAB® is used for a wide range of applications in geosciences, such as image processing in remote sensing, the generation and processing of digital elevation models and the analysis of time series. This book introduces methods of data analysis in geosciences using MATLAB, such as basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data and image analysis. The revised and updated Fourth Edition includes sixteen new sections and most chapters have greatly been expanded so that they now include a step by step discussion of all methods before demonstrating the methods with MATLAB functions. 

Rajendra Akerkar, Priti Srinivas Sajja ... 272 pages - Publisher: Springer; 1st edition (October, 2016) ... Language: English - ISBN-10: 3319292056 - ISBN-13: 978-3319292052 ...

This textbook provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. These embrace the family of neural networks, fuzzy systems and evolutionary computing in addition to other fields within machine learning, and will help in identifying, visualizing, classifying and analyzing data to support business decisions. The authors, discuss advantages and drawbacks of different approaches, and present a sound foundation for the reader to design and implement data analytic solutions for real‐world applications in an intelligent manner. Intelligent Techniques for Data Science also provides real-world cases of extracting value from data in various domains such as retail, health, aviation, telecommunication and tourism.

Ghassan Karame,‎ Elli Audroulaki ... 218 pages - Publisher: Artech House; (September, 2016) ... Language: English - ISBN-10: 1630810134 - ISBN-13: 978-1630810139 ...

There is a lot of buzz about Bitcoin and Blockchain lately, our expert authors will help to answer some imperative questions about the security involved in this new digital asset and ledger. This comprehensive new resource presents a thorough overview and analysis of the security and privacy provisions of Bitcoin and its underlying blockchain clients. This book goes beyond the analysis of reported vulnerabilities of Bitcoin, evaluating a number of countermeasures to deter threats on the system. Readers are given concrete solutions and recommendations on the best practices to use when relying on Bitcoin as a payment method.This resource provides a clear explanation of assumptions governing the security of Bitcoin, including the scalability measures adopted in Bitcoin, privacy for clients, and the proper means of securing Bitcoin wallets. Readers learn how the security and privacy provisions of other blockchain technologies compare to Bitcoin and the security lessons learned after extensive research of Bitcoin since the inception of the currency.

Giuseppe C. Calafiore,‎ Laurent El Ghaoui ... 650 pages - Publisher: Cambridge Univ. Press; 1st edition (October, 2014) ... Language: English ... ISBN-10: 1107050871 - ISBN-13: 978-1107050877 ...

Emphasizing practical understanding over the technicalities of specific algorithms, this elegant textbook is an accessible introduction to the field of optimization, focusing on powerful and reliable convex optimization techniques. Students and practitioners will learn how to recognize, simplify, model and solve optimization problems - and apply these principles to their own projects. A clear and self-contained introduction to linear algebra demonstrates core mathematical concepts in a way that is easy to follow, and helps students to understand their practical relevance. Requiring only a basic understanding of geometry, calculus, probability and statistics, and striking a careful balance between accessibility and rigor, it enables students to quickly understand the material, without being overwhelmed by complex mathematics. Accompanied by numerous end-of-chapter problems, an online solutions manual for instructors, and relevant examples from diverse fields including engineering, data science, economics, finance, and management, this is the perfect introduction to optimization for undergraduate and graduate students.

Luis Rabelo,‎ Sayli Bhide,‎ Edgar Gutierrez ... 350 pages - Publisher: Nova Science; (February, 2018) ... Language: English - ISBN-10: 1536126772 - ISBN-13: 978-1536126778.

After decades of basic research and more promises than impressive applications, artificial intelligence (AI) is starting to deliver benefits. Organizations around the world have been realizing that there are substantial performance gains and increases in productivity for the use of AI and predictive analytics techniques. Their use is bringing a new era of breakthrough innovation and opportunities. This book, compiles research insights and applications in diverse areas such as manufacturing, supply chain management, pricing, autonomous vehicles, healthcare, ecommerce, and aeronautics. Using classical and advanced tools in AI such as deep learning, particle swarm optimization, support vector machines and genetic programming among others. This is a very distinctive book which discusses important applications using a variety of paradigms from AI and outlines some of the research to be performed. The work supersedes similar books that do not cover as diversified a set of sophisticated applications. The authors present a comprehensive and articulated view of recent developments, identifies the applications gap by quoting from the experience of experts, and details suggested research areas. Artificial Intelligence: Advances in Research and Applications guides the reader through an intuitive understanding of the methodologies and tools for building and modeling intelligent systems. The book's coverage is broad, starting with clustering techniques with unsupervised ensemble learning, where the optimal combination strategy of individual partitions is robust in comparison to the selection of an algorithmic clustering pool. The book discusses how the use of AI can allow for productivity development and other benefits not just for businesses, but also for economies. Finally, you can find an interesting investigation of the "transhuman" dimension of AI. (Nova)

Josh Patterson, Adam Gibson ... 532 pages - Publisher: O'Reilly Media; 1st edition (August, 2017) - Language: English - ISBN-10: 1491914254 - ISBN-13: 978-1491914250 ...