Materials are everywhere. Right now, sitting at my desk, I am surrounded by a variety of typical office objects made out an almost unfathomable varietMaterials are everywhere. Right now, sitting at my desk, I am surrounded by a variety of typical office objects made out an almost unfathomable variety of materials: metal, glass, plastic, fiber, ceramics, paper, etc. Our lives, our culture and our civilization are almost completely determined and shaped by the materials that we use. It is our human ability to create and fashion materials in order to serve our multifaceted needs that distinguish us most visibly from all other creatures.
This very short introduction is a gentle yet deep and informative introduction to materials. It takes the reader on a journey through history, chemistry, physics and biology of various materials that we encounter. It pulls out many fascinating facts that I either did not know or never even stopped to think about (it's because of bronze's unique composition that bells have their distinct sound, and only thanks to some very special features of silver salts was photographic process possible to occur.)
One of this book's greatest virtues is its scope - all too often a material scientist has a very particular predilection for his/her own special class of substances, and focuses most of his attention to that topic. However, this short book is very comprehensive and covers pretty much everything that can be classified as material.
The other great aspect of this book is its easy and erudite writing style. The book is highly accessible and easy to follow, even for those who may not happen to be total science nerds.
Overall this is a decent introduction to "Liberalism," or at least to the general idea of what goes by that nomenclature these. Like most overarchingOverall this is a decent introduction to "Liberalism," or at least to the general idea of what goes by that nomenclature these. Like most overarching political ideologies, Liberalism can mean many different things depending on who the target audience is. The author of this short introduction tries to come up with a very layered and ad-hoc description of liberalism, but comes across as very strained and designed to purposefully justify including and excluding particular movements from the category. Overall, the book feels more self-serving and ideological, thana cool and objective assessment of a political category. In particular, I wish it had taken into the account recent research by Jonathan Haidt on moral clusterings and the way they pertain to different political affinities. ...more
Our ability to access, process, and analyze large quantities of data has been increasing at a dizzying pace over the last few years. This data-drivenOur ability to access, process, and analyze large quantities of data has been increasing at a dizzying pace over the last few years. This data-driven revolution is fundamentally changing many professional and academic fields. Many people, especially the long-term practitioners in humanities and similar disciplines, find this change worrying, and in many ways exactly contrary to the spirit of these disciplines. Pouring over long and demanding texts, while internalizing them and becoming personally immersed in them, seems to be at the very core of what these disciplines are all about. And yet, as both a lover of humanities and a die-hard techy, I find this latest development incredibly exciting.
The title of this short book makes it eminently clear who the intended audience is: students of literature who are interested in using R for textual analysis. R is a very powerful programming language used for statistical analysis. Textual analysis is a very prominent aspect of modern data science, so there are many well-known and established tools and techniques that can help one with this task. However, the aim of this book is neither to teach R or programming, but to give the Literature students just the most basic tools needed to do some relatively straightforward textual analysis. The book jumps straight into the examples almost from the very first page. The obvious virtue of this approach is that you can start doing some interesting work rather quickly, and as long as your own research doesn’t depart dramatically from the examples given in the book you should be able to use the books as a reference and a primer for your own work. However, if you have some slightly more demanding problems that you are trying to work on, then after finishing this book you might want to go to a specialized book on R programming that will give you enough foundation to work on a larger variety of problems.
The book takes the freely available text file of “Moby Dick” and runs a variety of textual analysis on it: simple word count and word frequencies, correlations between various “special” words, context analysis, etc. In the latter chapters it moves from a single book to a corpus of books for more interesting look at themes across many texts. I found the last chapter on topic modeling especially fascinating, but way too brief. I guess I will now have to take a look at other sources to learn more about this line of analysis.
This books is very pedagogical in its style. Oftentimes the author would present two different solutions to a particular problem - one using a very simple yet hard to understand R command, and another broken down into several self-contained chunks. I find this approach very educational and helpful.
Even though this is primarily a book intended for literature students, I would actually strongly recommend it to anyone interested in text mining, text analysis and natural language processing. It is a very gentle and approachable introduction to the whole world of textual analysis.
**** Electronic version of the book provided for review purposes. ****...more
Artificial Intelligence is by now a relatively old field, having originated in the early days of the digital computer revolution. However, it has hadArtificial Intelligence is by now a relatively old field, having originated in the early days of the digital computer revolution. However, it has had a very rocky and turbulent history, going through several cycles of overblown expectations followed by almost equally dramatic swings towards disillusionment and skepticism. In recent years, though, it has matured into a very solid and practical discipline that exercises an ever growing importance across a wide breadth of technologies and professions. We increasingly take speech recognition, handwriting recognition, and natural language search for granted. Basic familiarity with what Artificial Intelligence is, and what tools and techniques fall under its domain, are becoming ever important aspect of a variety of professions and occupations.
There is no shortage of books and resources on Artificial Intelligence. However, most of them fall squarely into two main camps: discursive overviews for the general audience, and highly advanced textbooks requiring deep familiarity with many advanced technical concepts. Ertel’s “Introduction to Artificial Intelligence,” even though it’s pretty technical in its own right, is still fairly accessible introduction to this field for anyone with solid grasp of basic college-level math and computer science concepts.
The book is organized somewhat chronologically along the lines of topics that have historically formed the main organizing principles for the study of Artificial Intelligence - first and second order logic, propositional calculus, PROLOG, machine learning, neural networks. Some of the earlier chapters’ material is a bit dated, and in some cases unfamiliar to students and practitioners in North America. For instance, it seems that PROLOG never quite got a hold on this side of Atlantic. There are a few more or less amusing examples of how quickly technology ages, such as references to Google Video links, which haven’t been around for a few years now. I would have also liked a substantially more material on machine learning and neural nets, maybe at the expense of the earlier chapters. These topics have a lot of practical applications today, and seem to be the guiding paradigms for Artificial Intelligence as a whole for a foreseeable future. Nonetheless, the book overall is very readable and relevant.
One of the most valuable aspects of this book are the worked out examples and numerous (solved) exercises. Working through problems is, by far, the best way to learn any new material, and this book provides the reader with numerous and wide-ranging opportunity to do exactly that.
Overall, this is a very well written and pedagogical book that fills an important niche in the Artificial Intelligence educational literature. Highly recommended.
**** Electronic version of the book provided by the publisher for review purposes. ****...more
“Data Science” is the most exciting research and professional fields these days. It is creating a lot of buzz, both within the academy as well as in t“Data Science” is the most exciting research and professional fields these days. It is creating a lot of buzz, both within the academy as well as in the business world. Detractors like to point out that most of the topics and techniques used by people who call themselves Data Scientists have been around for decades if not longer. However, has often been the case that a combination of topics and methodologies becomes important and concrete enough that a truly new subfield emerges.
Predictive Modeling is a particularly exciting subfield of Data Science. Thanks to the few recent high profile news grabbing success stories (the 2012 US presidential election, the Netflix prize, etc.) it has attracted a lot of attention and prominence. Thanks to the increased use and availability of data in all walks of life we are increasingly able to make reliable predictions and estimates regarding topics and issues that affect us in very substantive ways. This ability may sometimes seem almost magical, but behind it lay some very accessible ideas and techniques. “Applied Predictive Modeling” aims to expose many of these techniques in a very readable and self-contained book.
This is a very applied and hands-on book. It guides the reader through many examples that serve to illustrate main points, and it raises possible issues and considerations that are oftentimes overlooked or not sufficiently reflected upon. For instance, the way we model as simple of a data as a calendar date can have a significant impact on the kind of analysis and predictive model we choose. This is the kind of information that is often not discussed in other modeling books and can sometimes take years of practical experience before its impact is fully appreciated.
The book has a fairly low access bar, but it is definitely not intended for a complete novice. It assumes a fairly decent background in statistics, R language, and at least a passing understanding of machine learning. Many of these techniques are covered in this book, but mainly as summaries and refreshers. Each one of them could use up a book of its own, ore even a whole collection of books.
One of the best features of this book is that the authors understand that predictive modeling is not just a bunch of statistical and computational techniques. Understanding the data, how to obtain it, manipulate it, and format it, are some of the most crucial steps for predictive modeling (and other data-driven fields), and are often overlooked and not sufficiently explained in many other books and papers that I have come across. The same can be said about the model selection - the choice of a model and its predictive power will crucially depend on the kind of phenomena that we are predicting, as well as on what exactly are we trying to predict. This book does an excellent job in guiding the reader along these paths and installing the necessary intuitions required for successful predictive modeling. Here too, like with most things in life, there is no substitute for years of experience working with actual real world problems, but going through this book will ensure that you don’t have to stumble too much with your first steps.
**** Book provided for review purposes. ****...more
At the center of Christian life and ministry is the Bible, and at the center of the Bible are the Gospels. These powerful narratives of birth, life, dAt the center of Christian life and ministry is the Bible, and at the center of the Bible are the Gospels. These powerful narratives of birth, life, death and resurrection of Jesus were written by the first century Christians in order to inform and instruct the new and aspiring followers about the essential aspect of Jesus’ unique message and mission.
Among the four canonical Gospels, the Gospel of Mark is usually assumed to be the earliest one written, and a source and inspiration for the other two “synoptic” Gospels. It is the shortest and in many respects the rawest of all the Gospels. It uses very direct and even unrefined language and narrative structure. The Jesus that Mark presents to us can sometimes seem very rough. This is not the “nice” Jesus that has pervaded many modern sentimentalist ideas about Him, and influenced much of the “moralistic therapeutic deism” that passes for Christianity in many circles these days.
In “Face to Face with Jesus” Bruno Forte takes Mark’s Gospel as the starting point for his more intimate exploration of Jesus and what a genuine encounter with Him means for our lives. This very short book is not meant to be a commentary on Mark’s Gospel. Forte uses several passages from this Gospel in order to illustrate his points and evince insights, sometimes quoting the passages at length. The familiarity with Mark’s Gospel is of course desirable, but not necessary, for full appreciation of this book. Rereading it would probably be a good idea though. The book reads like a very well written extended homily. Forte’s style is very erudite and yet approachable - this is by no means a recondite theological thesis. “Face to Face with Jesus” makes demands on us to take Jesus’ work and ministry very seriously and open ourselves to the possibility of radical inner transformation that He asks from us.
Forte is also very clear in promoting a very strong emphasis on the radically different and supernatural nature of Jesus’ message and life. Many Christians, even the most faithful ones, fall into the trap of conceptually and rhetorically sacrificing Jesus’ divinity in order to make him more accessible and intelligible in terms of modern social and cultural categories. “Face to Face with Jesus” is, fortunately, not one of those books.
Even though this is a very short book, the reader should really take his time to go through it thoughtfully and deliberately. Anything else would not do it justice. As a spiritual nourishment I highly recommend it to everyone wanting to grow in their faith.
**** Book provided by the publisher for review purposes. ****...more