Azure-Databricks-NYC-Taxi-Workshop
lila
| Azure-Databricks-NYC-Taxi-Workshop | lila | |
|---|---|---|
| 1 | 795 | |
| 98 | 14,655 | |
| - | 1.2% | |
| 0.0 | 10.0 | |
| about 1 year ago | 6 days ago | |
| Scala | Scala | |
| MIT License | GNU Affero General Public License v3.0 |
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Azure-Databricks-NYC-Taxi-Workshop
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What the FUCK do people with office jobs do for work?
Depends if you need to do a lot of intermediate processing on your data; like spatial joins, or doing more more interesting modeling of the data.
lila
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How to make a Lichess bot in Python
Once you’re finished, we’re going to set up a lichess bot account. Head over to https://lichess.org/ and create a new account.
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Lessons from Open-Source Game Projects
Lichess - Online Chess Server. Scala, TypeScript
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Avoid blundering: 80% of a winning strategy
> the player who committed more blunders lost 86% of the time
In some sense this is almost tautological. While finding an exact definition for a chess blunder isn't straightforward, here is one example from the Lichess UI:
https://github.com/lichess-org/lila/blob/b527746b179cdde6438...
Basically, if you make a move which decreases your winning probability more than 14% over the best move, that's a blunder. But winning probability is a nonlinear function of stockfish centipawns. A drop in 100 centipawns when you're up 15 points isn't a blunder. When the game was equal, it is.
Point is, by the time you know it's a blunder you already know something about the outcome of that move, that it swung the winning probability by more than 14%. So the analysis is kind of just measuring some function of winning probability and saying that it is highly correlated with winning probability.
- How I hacked chess.com with a rookie exploit
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So bad at chess that it’s genuinely upsetting at this point, I need some hope
If you want to improve make it your goal to play the best chess you can, not increase an arbitrary number. Watch YouTube series like John Bartholomew's "Climb the Rating Ladder" for some general insight into what you might be doing wrong. Read Irving Chernev's "Logical Chess: Move By Move" to see the thinking process of high level players. Do lots of puzzles (I like lichess.org for puzzles). And always analyze your games. When you analyze make it your goal to find at least two things you could have improved.
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Humans vs. Stockfish’s eval function
The easiest way to play against Stockfish is perhaps on https://lichess.org/, but it's not the only chess engine that evaluates positions with a neural network.
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Venruki’s take on the current issues with PvP
Lichess.com
- Death wants to take you, but you can challenge it to a game (virtual or not) to stay. what do you play?
- Ask HN: What fuel for my data furnace?
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The DGPT season opener will be sponsored by chess.com!
if you actually like chess, try lichess.org, the free and open-source, no ads ever, premium alternative
What are some alternatives?
spark-extension - A library that provides useful extensions to Apache Spark and PySpark.
listudy - Listudy - chess training server
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]
Anki-Chess-2.0 - An interactive chess template for anki.
spark-nlp - State of the Art Natural Language Processing
Mindustry - The automation tower defense RTS
SynapseML - Simple and Distributed Machine Learning
katrain - Improve your Baduk skills by training with KataGo!
scala - Scala 2 compiler and standard library. Bugs at https://github.com/scala/bug; Scala 3 at https://github.com/scala/scala3
monkeytype - The most customizable typing website with a minimalistic design and a ton of features. Test yourself in various modes, track your progress and improve your speed.
logseq - A local-first, non-linear, outliner notebook for organizing and sharing your personal knowledge base. Use it to organize your todo list, to write your journals, or to record your unique life.
maia-chess - Maia is a human-like neural network chess engine trained on millions of human games.