Announcement 📢 Releasing dlpackrs

DLPack is the standard in-memory data format that facilitates zero-cost tensor transfer across major Deep Learning frameworks (PyTorch, TensorFlow and TVM) and the supported Python Array processing frameworks such as Numpy, CuPy. The dlpackrs provides a safe idiomatic Rust binding where Rust ndarray and tensor frameworks can use it to gain the same kind of … Continue reading Announcement 📢 Releasing dlpackrs

Announcement 📢 Releasing smartalloc

If you happen to write unsafe code in Rust where normal static checks are not available and want better UX for detecting memory issues along side using various sanitizers, checkout my new crate smartalloc which provides idiomatic Rust binding for the original C version here. Beside the reason in README, note that MIRI can't be … Continue reading Announcement 📢 Releasing smartalloc

The most influential book I have ever read

Summary The book Dopamine Nation starts with the idea that studying addictions and addicts teaches us about the boundaries of the human behaviours i.e. ourselves. The author who is a well-known psychiatrist, goes on describing various addiction cases who were her patients and interestingly about her case too. The book taught me about the pleasure-pain … Continue reading The most influential book I have ever read

How to have an honest self-evaluation

Intro I've been frustrated many times when one's capabilities don't match with what's been advertised or promised or promoted. Competing for job positions in the Linkedin era have made it worse. This behavior is mostly visible in the Data Science field where it suffers from bloated and exaggerated skills set. My views on Data Science … Continue reading How to have an honest self-evaluation

Announcement 📢 Create your own programming language with Rust

After almost a year from my last blog post, in this short post I'm very happy to announce that I'm writing a free online book where early chapters are available now. I've explained my motivations and goals in the introduction. The accompanying codes are also available on my GitHub. Feedbacks are welcome and happy learning. … Continue reading Announcement 📢 Create your own programming language with Rust

Rust std study series: Interior mutability

Continuing the standard library study, it's time for Cell<T>! Rust compiler enforces multiple reads access and a single write access mutually exclusive, i.e. either multiple shared references & or one and only one mutable reference & mut. So essentially, Rust prevents the evil of aliasing and mutation between multiple threads. Cell<T> is a sharable mutable … Continue reading Rust std study series: Interior mutability

Rust std study series: LinkedList

Continuing from Rust standard library study series, it's time for LinkedList<T>. Note that implementation are taken from Rust stable v1.33.0. A doubly-linked list with owned nodes. The LinkedList allows pushing and popping elements at either end in constant time. Almost always it is better to use Vec or VecDeque instead of LinkedList. In general, array-based … Continue reading Rust std study series: LinkedList

Variance in Rust: An intuitive explanation

Recently I've made a presentation about subtyping and variance in Rust for our local Vancouver Rust meetup, but I still think intuition was rather lost in the formalism, so here's my shot at explaining it as intuitively as I can. For more succinct definitions, please checkout the presentation or the resources at the end. First, … Continue reading Variance in Rust: An intuitive explanation

NIPS, AI hype and the lost rigor

Warning: This post contains a mixture of excitements, frustrations and rants! Today, Machine Learning/Deep Learning people have been sharing their great excitements over Ali Rahimi's talk at NIPS (from min 57 onwards). Undoubtedly, it's a great talk and you should check it out if you care about fundamental issues and the lost rigor in Deep Learning … Continue reading NIPS, AI hype and the lost rigor

Overview of Andrew Ng’s deeplearning.ai courses

In this post, I'm going to briefly write about the recently launched Andrew Ng's coursera courses in Neural Network and Deep Learning that I just finished with certificates. I want to argue that there's merit in taking these courses even if you're already familiar with some good portion of the syllabi. First a short relevant … Continue reading Overview of Andrew Ng’s deeplearning.ai courses

From Machine Learning to Formal Math and Type Theory

The idea of this post was sparkled from the new paper Developing Bug-Free Machine Learning Systems with Formal Mathematics. Meanwhile, I have had the idea of writing about what you're going to read for a long time and this paper happily forced me to do it finally! The first and final parts are about my journey and … Continue reading From Machine Learning to Formal Math and Type Theory