I see people make the same mistakes over and over again when learning Rust. Here are my thoughts (ordered by importance) on how you can ease the learning process. My goal is to help you save time and frustration. Let Your Guard Down Stop resisting. That’s the most important lesson. Accept that learning Rust requires adopting a completely different mental model than what you’re used to. There are a
This year’s Advent of Code has been brutal (compare the stats of 2023 with that of 2022, especially day 1 part 1 vs. day 1 part 2). It included a problem to solve with dynamic programming as soon as day 12, which discouraged some people I know. This specific problem was particularly gnarly for Advent of Code, with multiple special cases to take into account, making it basically intractable if you
From my perspective, one of the biggest open problems in implementing programming languages is how to add a type system to the language without significantly complicating the implementation. For example, in my tutorial Fall-from-Grace implementation the type checker logic accounts for over half of the code. In the following lines of code report I’ve highlighted the modules responsible for type-che
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Why APL is a language worth knowing
“A language that doesn't affect the way you think about programming, is not worth knowing.”, by Alan J. Perlis. Why APL is a language worth knowing Alan Perlis, the computer scientist recipient of the first Turing award, wrote “A language that doesn't affect the way you think about programming, is not worth knowing.” ― Alan J. Perlis, 1982. Special feature: Epigrams on programming. ACM Sigplan Not
Reindex, Transform, and Aggregate datasets using pandas Library
Most of the time, the dataset we will get from the business will be dirty and cannot be used straight forward to train machine learning models. Therefore, we must treat the dataset and bring it to the desired form to input it into an algorithm. This tutorial discusses reindexing, transforming, and aggregating datasets in Pandas. What are Reindexing, Transforming, and Aggregating?Reindexing, transf
An AI-native software engineer is one who deeply integrates AI into their daily workflow, treating it as a partner to amplify their abilities. This requires a fundamental mindset shift. Instead of thinking “AI might replace me” an AI-native engineer asks for every task: “Could AI help me do this faster, better, or differently?”. The mindset is optimistic and proactive - you see AI as a multiplier
Python Interview Questions
Here is a list of common Python interview questions with detailed answers to help you prepare for the interview as a Python developer. Python, with its versatile use cases and straightforward syntax, has seen its popularity growing continuously in software development, data science, artificial intelligence, and many other fields. As such, interviews for Python-related positions are designed not on
NumPy library on Python is an essential tool for data scientists to work on numerical data, especially when they deal with data arrays, especially multi-dimensional, and need a memory-efficient fast indexing of arrays, However, knowing about other useful packages when solving data science problems is essential. So, let’s see which packages are available in Python programming language and are used
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Flattening Rust's Learning Curve | corrode Rust Consulting
Dynamic Programming is not Black Magic - Quentin Santos
Unification-free ("keyword") type checking
Vim9 script for Python Developers · GitHub
The AI-Native Software Engineer
NumPy for Data Science Beginners in Python