Best Data Modeling & Design
Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures.
Reviews
Find Best Price at Amazon"I highly recommend this book for any software engineer."
"Great theoretical overview, not enough practical material to justify the name "designing"."
"I've been looking forward to this book since I pre-ordered it last year. I've been working on this field on and off for the past few years."
"He dives deep into subjects like Btrees, LSM trees, SSTables, and concepts that would normally seem foreign, but because of the author's understanding he breaks it down into tangible bits. By reading this book, you get a clear understanding of real world big data architecture and the drawbacks of things like sharding, replication, lag as well as solutions."
"After that book, you can read the free article "Distributed Systems for Fun and Profit" and you are good to go for this amazing book :D."
"He starts from a functional 4 lines code to build a database to the way how one can interpret and implement concurrency, serializability, isolation and linearizability (the latter for distributed systems). That said, if you ever worked on data systems, especially across paradigms (IMS -> RDBMS -> NoSQL -> Map-Reduce -> Spark -> Streaming -> Polyglot), this book is pretty much only resource out there to tie the "loose ends" and paint a coherent narrative."
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.
Reviews
Find Best Price at Amazon"- It is *not* your standard "management" title on the cool tech du jour available at airport stands and meant to be read in one sitting (buzzwords, hype and overly enthusiastic statements making up for the dearth of actual content)."
"Example : A leading Trucking company used Data mining skill to predict which part of the truck is going to break next instead of replacing it at specific intervals, a Leading insurer predicted those who will complete their antibiotic course based on their home ownership history. If this type of stories and scope interests you, read the book "Big Data: A Revolution That Will Transform How We Live, Work, and Think". It is a text book and authors have taken lot of care so general audience can also benefit from it, and also not to dilute it's textbook value. When you are finished with the book, you should have a fairly good understanding of data science, For example, what type of analysis that needs to be done to identify. A. ( When the target is clear, if the person will default on his loan). E. What is the significance of entropy in Data Science ? G. Don't get defensive, be comfortable when your colleague sprinkles words like like Classification ,regression, Similarity Matching, Clustering, Modelling, Entropy etc. You can get real life examples to work on in coursesolve dot org ( ex: Analyze the sleep cycle). 4. I signed up for Amazon elastic map reduce which has a higher level abstraction (for developers it is the difference between using sqlplus vs TOAD). Try to be the "umbilical cord that looks for a stomach to plug ", look for a mentor, look for opportunity in your firm or elsewhere to grow your Data scientist skills."
"The institution strategy and goals need to be reflected in the procedures used to analyse the data base of the institution and the determination as to what data is relevant."
"The coverage is broad with both supervised and unsupervised methods in data mining. If you intend to follow the math that is included, perhaps the paper edition would be best."
IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms.
Reviews
Find Best Price at Amazon"I was hoping to learn how to translate the dplyr verbs (group_by, filter, select, mutate, summarize, arrange) into pandas, but this book doesn't provide that. You will learn the basics of grouping and aggregation, but your code is going to be a lot more verbose than it was in R. The machine learning case studies in chapter 5 are pretty nice - probably the only reason I would recommend this book."
"For those interested in machine learning I would recommend bying "Hands-On Machine Learning with Scikit-Learn and TensorFlow" by Geron as well as this book."
"In summary, if you want to do data-analysis and you already know Python read this book, if you do not know Python read Think Python by Allen B. Downey first and then read this book."
"On the other hand I realize that some readers might want this extra depth, so I'm just saying what I personally would have preferred. A related problem is that the material can quickly go out of date, I already found some options to be deprecated when running code. Thirdly, I question some of the organization of material, he often introduces some aspect, doesn't explain it properly, and then returns to it later on to explain it in more depth. An example is the Scikit-learn pipeline object, he starts using this leaving me puzzled and only later returned to explain it."
"When I first received this book, I was surprised that it didn't get to scikit-learn until the last third of the book."
Best Database Storage & Design
Whether you're an application developer, database administrator, web application designer, mobile app developer, or Microsoft Office users, a good working knowledge of SQL is an important part of interacting with databases. And Sams Teach Yourself SQL in 10 Minutes offers the straightforward, practical answers you need to help you do your job. Expert trainer and popular author Ben Forta teaches you just the parts of SQL you need to know–starting with simple data retrieval and quickly going on to more complex topics including the use of joins, subqueries, stored procedures, cursors, triggers, and table constraints. You'll learn methodically, systematically, and simply–in 22 short, quick lessons that will each take only 10 minutes or less to complete. With the Fourth Edition of this worldwide bestseller, the book has been thoroughly updated, expanded, and improved. Lessons now cover the latest versions of IBM DB2, Microsoft Access, Microsoft SQL Server, MySQL, Oracle, PostgreSQL, SQLite, MariaDB, and Apache Open Office Base. And new full-color SQL code listings help the beginner clearly see the elements and structure of the language. Construct complex SQL statements using multiple clauses and operators. He is the author of the best-selling Sams Teach Yourself SQL in 10 Minutes , spinoff titles on MySQL and SQL Server T-SQL, ColdFusion Web Application Construction Kit and Advanced ColdFusion Application Development (both published by Adobe Press), Sams Teach Yourself Regular Expressions in 10 Minutes , as well as books on Flash, Java, Windows, and other subjects.
Reviews
Find Best Price at Amazon"great quick ref for daily sql users or someone who is just starting to learn."
"), people looking for a book about databases (this book only goes into the basic SQL stuff, though it does mention a couple good practices for database structure), anyone who wants an in-depth book about SQL (it really does just cover the basics). In short, this book is for newbies who need to learn SQL quickly: just the basics, an intro into more advanced topics, it's very user friendly, easy to follow, and you can get through it in an afternoon if need be."
"This is a brilliantly colored guide that takes you step-by-step through the basic of learning SQL."
"Mr. Forta navigates effortlessly through the deeper constructs of SQL, illuminating such oddities as the the Cartesian Product with the same ease that he describes time-saving techniques like JOINS and SUBQUERIES."
"However, in practice, this is the first book I turn to when I need a quick reference for basic/intermediate SQL use."
"The Kindle versions also helpful because I don't have to carry the book with me everywhere."
"I don't really write review on product but today I decided to do that because this book is on point."
"Not good."
Best Data Mining
This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. Almost all of the chapters are revised.… The Material is nicely reorganized and repackaged, with the general layout being the same as that of the first edition.… If you bought the first edition, I suggest that you buy the second editon for maximum effect, and if you haven’t, then I still strongly recommend you have this book at your desk. … the book may also be of interest to a theoretically inclined reader looking for an entry point to the area and wanting to get an initial understanding of which mathematical issues are relevant in relation to practice. … this is a welcome update to an already fine book, which will surely reinforce its status as a reference.” (Gilles Blanchard, Mathematical Reviews, Issue 2012 d). You can flip the book open to any page, read a sentence or two and be hooked for the next hour or so.” (Peter Rabinovitch, The Mathematical Association of America, May, 2012).
Reviews
Find Best Price at Amazon"In addition to having excellent and correct mathematical derivations of important algorithms The Elements of Statistical Learning is fairly unique in that it actually uses the math to accomplish big things. This hard use of isomorphism allows amazing results such as Figure 3.15 (which shows how Least Angle Regression differs from Lasso regression, not just in algorithm description or history: but by picking different models from the same data) and section 3.5.2 (which can separate Partial Least Squares' design CLAIM of fixing the x-dominance found in principle components analysis from how effective it actually is as fixing such problems). Unlike some lesser machine learning books the math is not there for appearances or mere intimidating typesetting: it is there to allow the authors to organize many methods into a smaller number of consistent themes."
"A good book in this area."
"While no book I have seen covers every data mining methodology available, this one has the strongest coverage I have seen in additive models, non-linear regression, and CART/MART (regression/classification trees)."
"Good book, help me build a systematic knowledge on statistics and machine learning. Of course, you may need some basic knowledge before reading it if you are novice."
"This book is basically the bible for statistical learning."
"This book is an excellent survey of the huge area of statistics / computer science called statistical learning."
"I'm a machine learning person, and this book provides pretty thorough state-of-art and up-to-date (relatively well) summary of statistical methods being used in lots of pattern classification fields."
"I have a PhD in Math and more particularly stochastic processes and everytime I open this book I can't quite understand what the content is."
Best Data Warehousing
Updated new edition of Ralph Kimball's groundbreaking book on dimensional modeling for data warehousing and business intelligence! Fully updated with fresh insights and best practices, this book provides clear guidelines for designing dimensional models—and does so in a style that serves the needs of those new to data warehousing as well as experienced professionals. Practical design techniques—both basic and advanced—for dimension and fact tables 14 case studies, including retail sales, electronic commerce, customer relationship management, procurement, inventory, order management, accounting, human resources, financial services, healthcare, insurance, education, telecommunications, and transportation Sample data warehouse bus matrices for 12 case studies Dimensional modeling pitfalls and mistakes to avoid Enhanced slowly changing dimension techniques type 0 through 7 Bridge tables for ragged variable depth hierarchies and multivalued attributes Best practices for Big Data analytics Guidelines for collaborative, interactive design sessions with business stakeholders An overview of the Kimball DW/BI project lifecycle methodology Comprehensive review of extract, transformation, and load (ETL) systems and design considerations The 34 ETL subsystems and techniques to populate dimension and fact tables.
Reviews
Find Best Price at Amazon"still a goto reference when starting new data warehouse projects."
"A very good book, complete, and updated."
"A few editorial / typo mistakes and more practical big data examples away from 5 stars."
"I was pleasantly surprised to see how much of the content here has been updated to incorporate paradigm shifts and new technologies, while still holding to the well-defined and well-proven Business Dimensional Lifecycle techniques."
"This is a clear and thoughtful book."
"This book really helped me understand Business Intelligence and Data Warehouse strategies."
Best Computer Programming Structured Design
This fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms is the leading textbook on algorithms today and is widely used in colleges and universities worldwide. The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. Robert Sedgewick has been a Professor of Computer Science at Princeton University since 1985, where he was the founding Chairman of the Department of Computer Science.
Reviews
Find Best Price at Amazon"Pure, elegant coding."
"Great book on algorithms: the author explains basics, then goes dipper into the topic."
"Great book!!"
"Indispensable algorithms reference and textbook."
"I really enjoy reading this book."
"I thought I still had it, so when I find I needed the C version for a graduate class (this has since been upgraded to Algorithms in C++) I decided to sve beaucoup bucks in getting a used version."
"Every programmer should have the hard copy of this book in his/her library."
Best Desktop Database Books
Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures. Martin is a researcher in distributed systems at the University of Cambridge.
Reviews
Find Best Price at Amazon"Couldn't recommend a better book if you want to update in the latest trendings about data storage and manipulation and truly understand what's behind it."
"An excellent in-depth overview of what kind of persistency solutions are available today -- along with insights into the most important traits of their (implementational) logic, including pros and cons to support the design of data intensive applications."
"I highly recommend this book for any software engineer."
"Best book for getting up to date on databases."
"Great theoretical overview, not enough practical material to justify the name "designing"."
"Very good book with narratives and examples."
"I've been looking forward to this book since I pre-ordered it last year. I've been working on this field on and off for the past few years."
"He dives deep into subjects like Btrees, LSM trees, SSTables, and concepts that would normally seem foreign, but because of the author's understanding he breaks it down into tangible bits. By reading this book, you get a clear understanding of real world big data architecture and the drawbacks of things like sharding, replication, lag as well as solutions."
Best Web Services
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. It also explains other major Java 8 features including default methods, Optional, CompletableFuture, and the new Date and Time API. How to use Java 8's powerful new features Writing effective multicore-ready applications Refactoring, testing, and debugging Adopting functional-style programming Quizzes and quick-check questions. Passing code with behavior parameterization Lambda expressions PART 2 FUNCTIONAL-STYLE DATA PROCESSING Introducing streams Working with streams Collecting data with streams Parallel data processing and performance PART 3 EFFECTIVE JAVA 8 PROGRAMMING Refactoring, testing, and debugging Default methods Using Optional as a better alternative to null CompletableFuture: composable asynchronousprogramming New Date and Time API PART 4 BEYOND JAVA 8 Thinking functionally Functional programming techniques Blending OOP and FP: comparing Java 8 and Scala Conclusions and where next for Java APPENDIXES Miscellaneous language updates Miscellaneous library updates Performing multiple operations in parallelon a stream Lambdas and JVM bytecode. Raoul-Gabriel Urma has worked as a software engineer for Oracle's Java Platform Group, Google's Python team, Ebay, and Goldman Sachs as well as for several startup projects.
Reviews
Find Best Price at Amazon"Lots of useful info on the new features of Lambdas and Streams."
"An excellent but verbose companion book to the also excellent but terse "Java 8 for the Seriously Impatient", by Cay Horstman."
"I have read many programming books as a Java Hobbyist, this has to be one of the best I have read."
"I am almost half way through this book."
"One of the best book to go through features of java 8."
"Very useful book, coming back to it every time I need to recall some details."
"Perfect book and delivered on time."
Best Microsoft Excel Guides
Leading Microsoft BI consultants Marco Russo and Alberto Ferrari help you master everything from table functions through advanced code and model optimization. Marco Russo and Alberto Ferrari cofounded sqlbi.com, where they regularly publish articles about Microsoft PowerPivot, DAX, Power BI, and SQL Server Analysis Services.
Reviews
Find Best Price at Amazon"Great book if you want to learn DAX, I am still reading it, because is difficult to express a language in a short book, keep improving it!"
"Detailed and easy to read."
"Contains the details needed to truely understand DAX."
"This a great and comprehensive book for anyone using DAX."
"Nice book."
"Amazing book, gives solid foundation and also a reference book."
"If you want to learn DAX this is the book period."
Best Bioinformatics
This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorisation, and spectral clustering. Almost all of the chapters are revised.… The Material is nicely reorganized and repackaged, with the general layout being the same as that of the first edition.… If you bought the first edition, I suggest that you buy the second editon for maximum effect, and if you haven’t, then I still strongly recommend you have this book at your desk. … the book may also be of interest to a theoretically inclined reader looking for an entry point to the area and wanting to get an initial understanding of which mathematical issues are relevant in relation to practice. … this is a welcome update to an already fine book, which will surely reinforce its status as a reference.” (Gilles Blanchard, Mathematical Reviews, Issue 2012 d). You can flip the book open to any page, read a sentence or two and be hooked for the next hour or so.” (Peter Rabinovitch, The Mathematical Association of America, May, 2012).
Reviews
Find Best Price at Amazon"In addition to having excellent and correct mathematical derivations of important algorithms The Elements of Statistical Learning is fairly unique in that it actually uses the math to accomplish big things. This hard use of isomorphism allows amazing results such as Figure 3.15 (which shows how Least Angle Regression differs from Lasso regression, not just in algorithm description or history: but by picking different models from the same data) and section 3.5.2 (which can separate Partial Least Squares' design CLAIM of fixing the x-dominance found in principle components analysis from how effective it actually is as fixing such problems). Unlike some lesser machine learning books the math is not there for appearances or mere intimidating typesetting: it is there to allow the authors to organize many methods into a smaller number of consistent themes."
"A good book in this area."
"While no book I have seen covers every data mining methodology available, this one has the strongest coverage I have seen in additive models, non-linear regression, and CART/MART (regression/classification trees)."
"Good book, help me build a systematic knowledge on statistics and machine learning. Of course, you may need some basic knowledge before reading it if you are novice."
"This book is basically the bible for statistical learning."
"This book is an excellent survey of the huge area of statistics / computer science called statistical learning."
"I'm a machine learning person, and this book provides pretty thorough state-of-art and up-to-date (relatively well) summary of statistical methods being used in lots of pattern classification fields."
"I have a PhD in Math and more particularly stochastic processes and everytime I open this book I can't quite understand what the content is."