On “The Sympathizer”


I made great progress and almost finish The Sympathizer. There is only one final knot to be untied, but I would write something about it now, otherwise I will be too lazy when I am done with it.

Usually I am highly reluctant to read trending books. Books, especially fictions, are written to sustain the test of time, hence if a book is good for today, it shouldn’t be too bad 10 years later, otherwise it isn’t worth it. Therefore, it usually isn’t worth the effort to read a book when you are not sure if it would last for 10 years (or 5 years, perhaps).

The Sympathizer is different though. Reading a fiction of one of your countrymen in a foreign language is a pretty weird experience, so weird that I simply couldn’t resist, especially when I was in short supply of good Vietnamese books.

Without spoiling the content, here are a few random comments on the book. It was very enjoyable and turned out to be a good investment.

The story told in the book was inspired by many events that are not too unfamiliar with many Vietnamese. Even the way the war was explained, although totally different from the way it was taught in Vietnam, is in fact, well-informed and thoughtful. Therefore, if you are a self-respected Vietnamese who cares to learn about history more than what being taught in schools, the story wouldn’t be too surprising.

The surprise for me though, was the writing style. Being a debut fiction, the book was remarkable. Readers are left with the feeling that the author puts effort in every single word appeared in the book. He would use bachelor to describe someone in celibacy, or use naïveté instead of naivety, perhaps just to make the narrator sounds a bit more French. In other scenario though, he would use tummy instead of stomach, just to highlight the intimacy of the plot being told. Sentences are often short, but he does not hesitate to write sentences that are one-page long, sometimes just to make a point. I haven’t read too many fictions in English, except a few from Charles Dickens, Jack London and Dan Brown (yea, I read Dan Brown too), so I might be bias, but this kind of dedication makes the book a pleasant read.

Many people praised the book for its satire and sense of humour, but those probably come from the brutal honesty of the unnamed narrator, speaking of whom, is quite a unique character.

The narrator is a hybrid, whose parent is a French priest and a Vietnamese maid. During the war, he found himself being an assistant to a General of the Army of South Vietnam, although he is actually a sleeper agent of the North. Like any other human being, he has his own weaknesses, in this case being his bastard status, which drives him nut every time it is mentioned by other people. Having studied in the US, he consumed the Western values and culture. The whole book is, therefore in some ways, his fight to find his true identity, the true home that he really belongs to. These existentialist questions are echoed by the fact that the book was opened with a quote from Friedrich Nietzsche.

Having such a complicated background, readers could easily expect him to be quite a man they could possibly have a beer with. He would make smart, provoking comments on every single chance, from the name of the USA to that of the USSR, from sex workers to how dating works, from wines to guns, from Saigon to Hollywood, from military to, you bet, politics, philosophy and arts. He could draw, or perhaps more precisely throw, deep philosophical thoughts on seemingly random events and stories. Having seen everything from both sides, perhaps multiple sides, his opinions are well-informed, brutal and amusing at the same time. He would take every chance to reflect and show the differences, or correspondences, between Oriental and Western world, as part of his identity crisis.

I still have couples of chapters left to work on, and therefore haven’t seen everything from the book yet. However, if there is anything to criticize, I would perhaps be concerned about how naive the narrator was when it comes to his loyalty with the North. Just in the same way he cracked the American politics and culture, as well as the war, it would be amazing if he spends a bit more effort to expose the Communist side. That would make the book a fair treatment on many sides involved in this bloody war.

Moreover, although the author was tactically smart about where to let the story speaks for itself and where to make comments, sometimes he made too much of a comment, making some part of the novel a bit heavy and overdone.

Nonetheless, The Sympathizer was a good book. For many Vietnamese who are not yet exposed to the minuscule details of the Vietnam war aftermaths, this is certainly a good read. For others, this is a refreshing book that probably will keep them thinking for a while after finishing it.


Linear Algebra textbook

For anyone who is serious about Machine Learning, Linear Algebra background is a must. I was asked several times by several people about a good introductory textbook in Linear Algebra, and every single time I struggled to recall the name of the textbook I used.

But here it is, I somewhat magically found it very recently


It is super concise and  greatly educational. Digesting the whole 300 pages will prepare you more than enough for pretty much any Linear Algebra stuff you will find in Machine Learning.

I learned Linear Algebra in undergraduate (with pretty decent professors I have to say), but it is in this book where my moment of enlightenment happened. Very early in the book, it presents how we should see the matrix multiplication in a slightly yet radically different view:  the multiplication A*x should not be interpreted as multiplying every row of A with x, but actually it is using elements of x to create a linear combination of the columns in A. This is the fundamental of all the reasoning in Linear Algebra, because with this view, Ax belong to the column space of A (a.k.a the range of A). Every Linear Algebra reasoning becomes super clean with this interpretation. Every matrix decomposition you find in Machine Learning (SVD, Cholesky, LU…) suddenly becomes all easy.

In other words, this is highly recommended for any newbie in Machine Learning. I believe you will enjoy it as much as I did.