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Some time ago my friend, who worked with native English speakers, told me that when they worked with a colleague on a piece of technical documentation, the word “she” suddenly appeared referring to the “user.” They discu
Eggcorn of the day Bone apple tea → bon appétit
Hello everyone! I really appreciate that all of you have signed up for my channel. It's kinda touching, and I feel a little bit awkward just writing about GBDT and TFWR (but what else could I write about…). So, I’d like
TFWR. Navigation. In order to navigate the drone, there are get_pos_x(), get_pos_y(), and move() functions. move() takes East (x + 1), North (y + 1), West (x − 1), and South (y − 1) commands. get_world_size() is useful t
Memories Awakened by “The Farmer Was Replaced” It seems like a very trivial question: “What should a drone do if it is on the lower (South) edge of the field and it has a move(South) command to perform?” But, strangely,
The Farmer Was Replaced In one of ML channels I'm reading, I found a reference to the game "The Farmer Was Replaced". Here you are to write programs on a language which is quite similar to Python, but is not quite Python
Everybody wants to be like ewe [Track on youtube ](<https://youtu.be/LjQ0hO89xrw?si=8Ubzxl9JjMLISk9C&t=17>) Just a small reminder: 🐑Homophones - "you" and "ewe", same pronunciation but different meanings 🐑Homographs - sa
The Absolute Evil of Default Parameters Default parameters are evil. Seriously. It’s very convenient evil—so convenient that it crawled into my library. On the first image there is a call to train a model with: 🐴n_stages
Three out of eight Let's check three out of eight components. On the colored picture you can see the whole title. Let’s inspect three of the eight components (the colored figure shows the full title). The first component
Four basis functions. To build the MSE dataset I used four basis functions: 1, t, sin(50t), cos(50t). Why these four? 𐂅 Constant never hurts — it lets the curve shift up or down. 𐂅Linear captures any overall trend. 𐂅sin
Tree. From Gradient Boosted Decision Trees. In playing with some technology or algorithm, my favorite moment is that elusive, transitional state when it’s still a little bit “wtf?” and yet already a solid—though not yet
Retrophotos. Physics. It’s a photo from my previous life as a physicist. To be honest, it’s one of the greatest surprises of my life. You take a glass-clear piece of diamond—perfectly transparent and homogeneous. You put
The key graph in catching a culprit: basis functions. In wrong basis functions there wasn't any periods, just one slope.
The first group in the dataset
Some simple EDA steps: number of components in the whole dataset
It's alive! Finally I ran the full cycle of training and applying my EGBDT model in JupyterLab. I spent two days in a very unpleasant debug session because I broke a simple rule: Always do EDA! EDA—Exploratory Data Analy
How to set up openai helper in jupyterlab For quite a while I was procrastinating quite a simple task: to set up AI assistant in jupyter lab. Here I want to write down a sequence of steps for memory. * set up environment
Meta joke - joke about LLM cognition. To be honest, I didn't get this joke until asked iron friend to explain it.
The final dataset
The second dataset with all letters capital