Book Review: The JavaScript Handbook by Flavio Copes

If you're a competent programmer but have been away from JavaScript for some time and want an extremely brief overview of the updates to JavaScript, in bite size form, then this book (The JavaScript Handbook) is for you.

Flavio goes over all the new features in JavaScript from ES6 to ES2018. Listing out each feature or change and giving an extremely brief description of it.

This book reads like a collection of very short blog posts though. And would benefit from more editing, both on a sentence level and on an overall topic cohesiveness level. That's a small nitpick in what is overwise a good set of writing.

There's definitely two major parts to the book. First part is extremely brief in describing the changes in each version of ECMAscript.

Second part basically goes over all the changes, again, but this time in more detail. Not a lot more, but sufficient for a competent programmer to know enough.

E.g. if you don't know that much about async and promises on a conceptual level, this book isn't going to teach you enough to really use those features productively.

Or if you don't really know the problems with the "this" keyword in JavaScript, the book's description of it in relation to how it works and how it's changed with arrow functions isn't the most enlightening. Some sentences on it, superficially without a deeper understanding of how programming languages work, are downright contradictory sounding.

All in all though, I went through it cover to cover, and the book does a good job for reviewing changes to JavaScript for the competent programmer.

For next to free (i.e. email signup), it's hard to beat.

Clojure Programming Cookbook - a Book Review

It's been a while since I've looked into programming Clojure again, having been preoccupied with C++ lately.  With the new Clojure Programming Cookbook, I've gotten to see a number of new developments in the Clojure ecosystem that is quite exciting.

The book is very example oriented, basically being a collection of code recipes for accomplishing common programming tasks with Clojure.  I like how it starts from very basic interactive programming and macro usage (this is a Lisp after all), all the way to talking about concurrency, parallel processing, and cloud-based tasks.  Each recipe is accompanied by brief explanations, preambles, and some cross references to related recipes in the book.

Each recipe is basically self-contained, so I wouldn't necessarily recommend reading the book like a book, but instead to use it as a "random access" set of references.  The ebook version is probably best in terms of allowing for full-text searching for key terms, and for clicking on relevant topics in the table of contents to look up useful recipes.  I'd personally prefer having the PDF ebook, but that's just me.

As a reference book, it's great if you already have familiarity with Clojure, but this book is probably okay for those of you programmers who don't yet know Clojure and want to learn it.  I'm not sure it's that great if you just don't know how to program and want to learn programming starting from nothing.  On the other hand, I could imagine a course instructor might be able to bootstrap the book with additional content to help absolute beginners get started, then point out recipes in the book to try out from time to time.

What's neat about this book for me is that as I've been away from Clojure for a few years, looking at this book I see recipes for topics I'd like to try out.  Topics I've heard of but just haven't followed along with over the years.  Like Transducers, and Om.Next.  So it's nice to see some self-contained examples of these exciting new developments in the Clojure ecosystem.  But given that it is just a cookbook, it doesn't seem to get deep enough into any specific particular topic for me to feel like I really know what's going on.  For that, I'd need to look to additional resources.

So there's definitely some caveats, but it is a pretty decent and easy going kind of book.  For a lower intermediate Clojure programmer, it's definitely a good resource to look into, maybe to help get you from programming on a single machine to programming for the cloud (AWS, etc.).  For upper intermediate programmers who's been away from Clojure for a while and want to see some new Clojure developments, I'd definitely see about getting it if you chance upon a sale.  The book lives up to its name as a cookbook.

Haskell Data Analysis Cookbook - a Book Review

As with my previous post, Clojure Data Analysis Cookbook - a Book Review, I was this time offered to review Haskell Data Analysis Cookbook by Nishant Shukla.  First impressions: those are two very similar and related books that have some overlapping ideas, but not only are the programming languages used totally different in "genre", the content itself also cover some different data analysis grounds and could be treated as complementary books in that way.

The book itself is very example oriented (much like the Clojure Data Analysis Cookbook), basically being a collection of code recipes for accomplishing various common tasks for data analysis.  It does give you some quick explanations of why and what else to "see also".

It gives you recipes to take in raw data in the form of CSV, JSON, XML, or whatever, including data that lives on web servers (via HTTP GET or POST requests).  Then there are recipes to build up datasets in MongoDB, or SQLite databases.  To recipes to clean up that data, do analysis (e.g. clustering with k-means), to visualizing, presenting, and exporting that analysis.

Each recipe is more or less self-contained, without much in building on top of previous recipes.  It makes the book more "random access".  It's less a book to read through cover to cover, and more of a handy reference to use by full-text searching for key terms, clicking on the relevant topic in the table of contents, or by looking up terms in the index.  It's definitely a book I'd rather have as a PDF ebook so that I can access it anywhere in the world, and so I can do full-text search in.  It does come in Mobi as well as ePub formats, and code samples are provided in a separate zipped download as well.

Having said that, you can tell whether a book was made to be seriously used as a reference or not by looking at its index.  There are 9 pages of indices, equivalent to about 2.9% of the number of pages previous to the index.  This book can certainly be used as a reference.

As a reference book, it's great for people who have already a familiarity with Haskell in general.  If you don't know Haskell, this book won't teach it to you.  That is, unfortunately, possibly a missed marketing opportunity, as those who don't know Haskell (but have knowledge of another programming language) really only needs a small bit to understand enough of how functions are written in Haskell to pick up what's going on in the book.  This means if you know another programming language, know a bit about data analysis, you could use this book to learn some Haskell so long as you pick up the basic syntax with another tutorial in hand (so it's really not a show stopper to using this book).

Similarly, I'd say you had best be familiar with how to do data analysis as a discipline in itself.  If you don't know whether to do clustering or regression, or whether to use a K-NN or K-means, this book won't teach it to you.

Much of that is, of course, echoing the Clojure Data Analysis Cookbook.  Where the Haskell Data Analysis Cookbook differs, makes the two books have a set of complementary ideas.  Whereas both books talk about concurrency and parallelism, the Clojure DAC goes into those topics (including distributed computing) in much more detail.

On the other hand, whereas both books talk about preparing and processing data (prior to performing statistics or machine learning on it), the Haskell DAC goes into much more detail on topics like processing strings with more advanced algorithms (as in computing the Jaro-Winkler distance between strings, not like doing substring/concat operations), computing hashes and using bloom filters, and working with trees and graphs (as in node-and-link graph theory graphs, not grade-school bar graphs).

So in some sense, the Haskell Data Analysis Cookbook has more theory heavy topics (graphs and trees!), whilst the Clojure Data Analysis Cookbook has more "engineering" topics (concurrency, parallelism, and distributed computing).

Neither books are comprehensive treatise on the topic, but someone who needs a practical refresher on working with graphs and trees may find Haskell Data Analysis Cookbook to be quite useful.

All in all, I'd say this is a decent book, because if you have some familiarity of Haskell, have some familiarity with some of the basic technologies like JSON, MongoDB, or SQLite, have taken a class or two of data analysis or machine learning in university (or a MOOC?), and aren't expecting a lot of hand holding from the book, then this book is a great guide to start you off to doing some data analysis with Haskell.

Clojure Data Analysis Cookbook - a Book Review

Like yogthos, I was recently asked to review Clojure Data Analysis Cookbook.  With Incanter, data analysis has been one of the "selling points" of Clojure as a practical language.  A practical lisp for practical data analysis.

(Edit 2016: a second edition is available!)

The book is very example oriented, basically being a collection of code recipes for accomplishing apparently common tasks for data analysis.  It gives you recipes to go from taking raw data in the form of CSV, JSON, or whatever, to making an Incanter dataset, to doing analysis on those datasets (e.g. clustering the data by using a self-organizing map), to saving, viewing, or charting the resultant data.  Each recipe is accompanied by brief explanations, and cross-references to other related recipes in the book.

Each recipe is more or less self-contained, without much in building on top of previous recipes.  It makes the book more "random access".  It's less a book to read through cover to cover, and more of a handy reference to use by full-text searching for key terms, clicking on the relevant topic in the table of contents, or by looking up terms in the index.  It's definitely a book I'd rather have as a PDF ebook so that I can access it anywhere in the world, and so I can do full-text search in.

Having said that, you can tell whether a book was made to be seriously used as a reference or not by looking at its index.  There are 10 pages of indices, equivalent to about 3.2% of the number of pages previous to the index.  This counts as a book to be seriously used as a reference.

As a reference book, it's great for people who have already a familiarity with Clojure (and better yet, Incanter) in general.  If you don't know Clojure, this book won't teach it to you.  If you don't know Incanter, you can pick it up from this book if you're a fast learner (don't expect a lot of hand holding in learning Incanter though).

Similarly, I'd say you had best be familiar with how to do data analysis as a discipline in itself.  If you don't know whether to do clustering or regression, or whether to use a SOM or K-means, this book won't teach it to you.

Also, as a reference book, it is not comprehensive.  For example, as far as neural networks go, it only includes self-organizing maps.  There are no other kinds mentioned.  If you want another kind of neural network, you best know where to look for another Java or Clojure library.

Even with all those caveats, I'd still say this is a pretty decent book.  Why?  Because if you have some familiarity of Clojure, played around with Incanter for a bit to learn that library, have taken a class or two of data analysis in university, and aren't expecting a lot of hand holding from the book, then this book is a great guide to start you off on the road to doing data analysis with Clojure, Incanter, Weka, OpenCL, Cascalog, etc.

Book Review: Art and Science of Teaching

The Art and Science of Teaching by Robert Marzano is subtitled, "A Comprehensive Framework for Effective Instruction." I would suggest emphasizing "Framework" in that description over "Comprehensive", but that is not to say the book is bad. In fact, I recommend this book, especially for the big ideas it discusses in some detail on effective teaching.

I've been meaning to write a brief review of this book as it's been given to me as a gift a long time ago.  It's a solid book of big ideas with adequate examples of how those ideas might be implemented in a classroom.  Ideas regarding, for example, how a teacher can "establish and maintain effective relationships with students," and how to "help students practice and deepen their understanding of new knowledge."

The ideas are great, and examples are good, and the ideas are backed up by research (that's the science part of the book).  I'd love to try employing more of these ideas into my own classroom in the future.  There are, however, two major flaws in the book I should mention.

Book Review: Introduction to Algorithms

Introduction to Algorithms, by Cormen, Leiserson, Rivest, and Stein, is a good introductory textbook to algorithm design and analysis for the undergraduate student in their first course on the study of algorithms.

It is a good learning text in that the writing style offers more explanations and has a more "conversational" tone (as compared to other texts that are much more succinct). Having said that, this is still a textbook and assumes students to have a fairly decent math background and ability to think in a mathematical manner.

It would not be far off to say that this is more of a math text than a programmers' text. That is to say, this is not a cookbook with code that can be copied to make things work. This is a text to help students learn to think and reason about algorithms.

For a first course in formal algorithms for undergraduates, this would be a good text. If you want a more rigorous, mathematical, and succinct reference or introduction, Algorithm Design by Kleinberg and Tardos (which I have reviewed) may be a better fit for you.

Book Review: Algorithm Design

Algorithm Design by Kleinberg and Tardos is a good handbook on algorithms, the best I've seen so far in terms of balancing theoretical understanding and practical concerns. Examples that are given often have a realism lacking in other texts, showing a concern for practitioners who may want to see how these algorithms could actually be useful.

On the other hand, the succinctness of the writing style meant I had to read passages several times to understand fully the concepts being explained (ie, it required a close reading, as we might say in philosophy writing). This is, I think, a good thing: rereading well written passages is more effective than reading repetitious passages once through anyway.

Especially in the chapters regarding NP completeness and approximation algorithms, the "tone" of the writing definitely turned much more mathematical, and that's especially when a good mathematical background is helpful.

Largely because of the succinctness of the writing style and assumed mathematical background, I would say this is more of an advanced upper-undergraduate level textbook, or a good introductory text at the graduate level. I'm afraid at the introductory level for undergraduates, this text may serve more to instil confusion (a better text at the undergraduate introductory level may be Introduction to Algorithms, which I also reviewed).

If you're looking for an advanced algorithms textbook, I would definitely recommend it.

Book Review: Artificial Intelligence: A Modern Approach

Artificial Intelligence: A Modern Approach by Stuart Russell (Professor of Computer Science at University of California,
Berkeley) and Peter Norvig (Director of Research at Google) is the standard introductory textbook to AI theory and application at the undergraduate level.

It's friendly in the sense that it requires less mathematical maturity, and assumes less mathematical background. It does have a very comprehensive and broad survey of the entire field, which is good in that it gives the student a sense of the entire field, but bad in that there is much less depth in any single area.

If you are looking for a single good introductory textbook to get started into research, there are probably better alternatives (such as Pattern Recognition and Machine Learning, which I also reviewed). But if you are looking for a single good introductory textbook to understand the field better, and not necessarily to prepare to do original research, this is probably a great book to start with and I recommend it highly.

A word of caution of the term "artificial intelligence" though. Much of the algorithms and techniques referred to in this text are probably more accurately described as machine learning or statistical pattern recognition algorithms. If you are looking for a book on artificial general intelligence, you will be disappointed.

Book Review: Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning is by Christopher Bishop (Chief Research Scientist at Microsoft Research Cambridge, and Professor of Computer Science at the University of Edinburgh).

It's a heavy read on machine learning algorithms in that it is very math intensive. It would not be too far off to call this an applied math textbook rather than a computer science textbook, and it is definitely aimed at the graduate level student with a good amount of mathematical maturity.

Having said that, if you are a machine learning researcher in need of learning all sorts of mathematical details of the algorithms you are using, this book is a good place to start. It is by no means a complete reference, but certainly a good introduction at the graduate level.

If you are an undergraduate student, there are other textbooks available that might be more suitable (such as Artificial Intelligence: A Modern Approach, which I also reviewed). If you just want cookbook style text on the libraries you could use to employ machine learning algorithms, there are probably other resources that would be more suitable.

If you are starting out in researching machine learning algorithms, or are using it as a large part of your computing science research, this is the right book. Just be prepared to learn and use a lot of math!

Book Review: "Coders at Work"

Coders at Work is for programmers and computing scientists interested in how some very well known coders think about their art or craft. It is a series of interviews of some of the top coders of our time. It includes their thoughts on some very controversial issues on coding style, algorithm development, testing, documentation, etc.

It's a great book to read to get a sense of how some of these people think about those issues, and it's incredibly rewarding if you already know the names of some of the coders interviewed. I was especially excited to read the interviews of Peter Norvig, Guy Steele, Ken Thompson, and Donald Knuth. The other interviews were great too, and better if you already know something about those people.

Now just because some of these people think one way or another on an issue doesn't mean I would go and imitate them. The main thing is to read their explanation of what they're thinking, the why's and how's, and examine it to understand how they're thinking about an issue. Now how they think about issues — that is possibly worthy of imitation.

Definitely recommended for programmers and computing scientists wanting to improve their game!

Book Review: "Hyperspace: A Scientific Odyssey Through Parallel Universes, Time Warps, and the 10th Dimension"

Wow, what can I say about this book? It inspired me to learn more science, specifically physics. Hyperspace: A Scientific Odyssey Through Parallel Universes, Time Warps, and the 10th Dimension has vivid analogies that I was able to, more or less, understand when I was about 11 years old.

The thought experiments Kaku talked about made me imagine the possibilities of the universe. It's a great book to get kids interested in science since it explains the intuitions without being stuck in the precise details.

Intuitions of what? Well, intuitions of space, time, and ultimately spacetime of more than three dimensions. It has nice thought experiments to help develop intuitions of what it's like to have more than three dimensions. Kaku also explains the intuitions around string theory, which is fascinating as well (even if it turns out that string theory is wrong, it's still fun to imagine the universe in a different way).

A great book, especially for kids. Highly recommended!

Book Review: "Philosophy of Mind"

Philosophy of Mind (Dimensions of Philosophy) is a fantastic introduction to the subject, and to the basic fundamental issues surrounding any topic that relates to the mind, including cognitive science, artificial intelligence as it relates to cognitive science, psychology, etc.

It covers a lot of ground without presuming specialist knowledge of terminologies, and it briefly explains all related concepts that are required to understand the issues at play (eg, concepts from as far afield as philosophy of science, language, or the computing science concept of a Turing machine).

Book Review: "Difficult Conversations: How to Discuss what Matters Most"

Difficult Conversations: How to Discuss what Matters Most is a good book offering an objective analysis of what goes on and into difficult conversations. Difficult conversations are those on topics that may be difficult and uncomfortable because of its ability to cause pain and negative, if not destructive, results.

By dissecting such conversations into three pieces that people can affect, viz, the "what happened" conversation, the "feelings" conversation, and the "identity" conversation, this book provides recommendations on how to diffuse and create constructive conversations instead.

This book provides examples of what to do and what not to do in some realistically common situations and this improves readers' understanding of the theories they lay out. The focus on actionable behaviours makes this book useful and insightful for the general audience, rather than merely inspirational.

Book Review: "Religion and Science"

Religion and Science (Gifford Lectures Series) is an excellent introduction to historical and contemporary issues and views in the interaction of science, religion, and society.

Very detailed in its presentation of scientific topics, although for those who are already well versed in various popular general scientific topics, certain sections describing relativity, quantum theory, astronomy, etc, might be a bit repetitive.

The same could probably be said of the theological topics for those already well versed in them. That is, of course, why this book makes for an excellent introductory text.

This book is not a one or two sided view but instead presents many of the nuances in the interface between science and religion in society. I recommend this book, and especially more so in conjunction with Midgley's Science as Salvation: A Modern Myth and its Meaning, which I've reviewed as well.

Book Review: "Science as Salvation: A Modern Myth and its Meaning"

Science as Salvation: A Modern Myth and its Meaning is a fantastic book about the development of science and its advancement in Western culture. It contains a lot of deep and thought provoking discussions on the position science holds in current Western culture, and its metaphysical and epistemological nature.

In particular, it looks at the notion of science as a societal, cultural, and even spiritual force, a notion that is sometimes thrust onto science and perpetuated by certain science writers. To some, the building of this notion tends towards using science as part of a myth constructed by people to shape and understand how to live in an age of an over abundance of information; perhaps it even seems to be displacing the role of religion.

Neither entirely anti-science nor pro-science, Midgley presents a nuanced view of the interaction of science, religion, and society. Midgley encourages a rethinking of the role and importance of science, and its relationship to how we live and how we ought to decide to live.

On the whole, this is a book I recommend on the philosophy of science and society. I also recommend reading this in conjunction with Barbour's Religion and Science (Gifford Lectures Series), which I will be reviewing as well.

Book Review: "Blink: The Power of Thinking Without Thinking"

Malcolm Gladwell's Blink: The Power of Thinking Without Thinking presents some interesting ideas and anecdotes to help better understand how good decisions and snap judgements are made when people are faced with overwhelming data.

Plenty of skepticism ought to accompany you as you read this book. The stories are well written and may seduce you into believing his theories all too easily. Pack along some salt for a better taste. (If you are thinking of reading Think!: Why Crucial Decisions Can't Be Made in the Blink of an Eye, you might want to read my review of that one first.)

Especially important is to look into his explanation of how, why, and when the snap judgements worked in the cases he presents. He doesn't make the absurd claim that all snap judgements in all cases under all circumstances are better than thought out judgements. If you've carefully read Gladwell's Outliers: The Story of Success (which I've reviewed previously), you may notice that Gladwell's point in the narratives he shares are often subtle and sometimes easy to misinterpret. Maybe that's why it makes for such an enjoyable and engaging read!

Book Review: "Think!: Why Crucial Decisions Can't Be Made in the Blink of an Eye"

Think!: Why Crucial Decisions Can't Be Made in the Blink of an Eye was a book I anticipated would be a good counterpoint to Malcolm Gladwell's Blink: The Power of Thinking Without Thinking (which I've also reviewed).  Unfortunately, it just didn't have a strongly written narrative to tie together the too many various ideas presented.

Also unfortunate was how most of the ideas LeGault presents seemed entirely concerned with the USA.  This is in itself fine, of course, but for readers outside the US, it does make for a less interesting read.

This book also read like an outright attack on Gladwell's "Blink," but written in such haste that LeGault's apparent contempt for "Blink" and its ideas hasn't subsided.  It made the book have a vindictive tone that wasn't effective in persuading or moving me, unlike Gladwell's writing.

Book Review: "Tribes: We Need You to Lead Us"

Seth Godin in Tribes: We Need You to Lead Us has some interesting ideas about how leaders come to be and how ideas spread, stressing that change comes about through groups of people organized like a tribe: an interconnected group of people with a leader and an idea.

The difference between a tribe and just a group is explained in the book in terms of how they're formed, in that the leader of a tribe finds similarly minded people to form into a movement for an idea.

This is packed with case studies to explain what Godin sees as effective means to create change in and out of a corporation.  It is, unfortunately, a little repetitious, almost like Godin was adapting a speech into a book form.  So I recommend listening to the unabridged audiobook if you can instead.

Book Review: "Outliers: The Story of Success"

Outliers: The Story of Success is an excellent book giving insight as to why certain people succeed under certain social and other conditions, explaining the significance of cultural legacies and hard work to success, and illustrating how knowing this can assist educators in helping more people succeed.

It's probably best to read this book carefully to understand what it is Gladwell is asserting.  This is because it's all too easy, as some seem to have done, to understand Gladwell's arguments as asserting that people succeed only due to environmental factors.  At one point, he even seems to explain how hard working a person is as being a product of the person's cultural heritage!

Book Review: "Change or Die: The Three Keys to Change at Work and in Life"

The book Change or Die: The Three Keys to Change at Work and in Life first started off as an article in Fast Company. It encourages us to see how we can help others change their behaviour, help them make changes to their own lives, for the better, through three critical keys: relate, repeat, and reframe. These keys addresses the need to build positive relationships, to recommend specific behaviours, and to support the mindset created in this process, which underlie the changed behaviours. Filled with analysis and theory of specific case studies. A great read, and a book I recommend to all educators.