stataholic

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stataholic

stataholic

@stataholic

Data Scientist, Forbes. Research about application of Machine Learning in Sports.

Data World Katılım Mart 2018
810 Takip Edilen102 Takipçiler
stataholic
stataholic@stataholic·
Every {}, "field", :, and comma in JSON becomes tokens. LLMs tokenize JSON poorly, inflating both latency and API cost. TOON removes the noise and keeps only the meaning. #ToonStream
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stataholic
stataholic@stataholic·
Meet Toonstream, the library that implementing TOON (Token-Oriented Object Notation) — a serialization format built to make structured LLM inputs far more token-efficient than JSON. ! pip install toonstream #LLM #AiAgents
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stataholic
stataholic@stataholic·
LLMs aren’t expensive. Your JSON is. Switching from JSON → TOON cuts token usage by: 55% on flat data 38% on arrays 15% on nested objects Here’s why this matters — and how much you can save. 👇 #LLM #AI #AGENTS #RAG
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Hudl Statsbomb
Hudl Statsbomb@Statsbomb·
Update: 49/52 shots have an xG value of 7% or less
Hudl Statsbomb@Statsbomb

Ahead of #MNF tonight, here's all the shots Arsenal have conceded in the Premier League in 2024 Not only have they conceded the fewest shots per game (7.8) in that time, the quality of the shots has also been the lowest in the league 45/48 shots have an xG value of 7% or less

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stataholic
stataholic@stataholic·
Tuesday is the new friday.
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stataholic
stataholic@stataholic·
I have a classification problem, and XGBOOST is the best model. I have calibrated the model outputs as well and saved both the models. Say, I am creating a pipeline to predict for future values. Which model should I use? Normal or calibrated model ? @tunguz #DataScience
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Leif Denby
Leif Denby@leifdenby·
`plt.subplot_mosaic(...)` is the single-most amazing @matplotlib function I'd never heard of 😍🤓🌍 Can't believe I've used Python for more than a decade and only just discovered it! Subplots will never be the same again 🌟 #matplotlib.pyplot.subplot_mosaic" target="_blank" rel="nofollow noopener">matplotlib.org/stable/api/_as…
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stataholic
stataholic@stataholic·
@haltakov evaluation metric is totally depend on the type of data we have. If it's balanced data, we can use accuracy. If it's imbalance, we can either use precision or recall depends on the use case.
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Vlad Haltakov
Vlad Haltakov@haltakov·
How to evaluate your ML model? 📏 Your accuracy is 97%, so this is pretty good, right? Right? No! ❌ Just looking at the model accuracy is not enough. Let me tell you about some other metrics: ▪️ Recall ▪️ Precision ▪️ F1 score ▪️ Confusion matrix Let's go 👇 #RepostFriday
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stataholic
stataholic@stataholic·
@tunguz How to become a Data Scientist in one month ?
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Bojan Tunguz
Bojan Tunguz@tunguz·
Offend a Data Scientist in one tweet.
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Hudl Statsbomb
Hudl Statsbomb@Statsbomb·
ANNOUNCED: The #StatsBombConference Live-Stream Schedule! We want to make the Conference accessible to the wider community, so we'll be streaming some of the talks LIVE from Stamford Bridge We'll post the stream link on Twitter tomorrow morning prior to the event 🎥
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Thibault Clérice (ponteineptique on Ciel Bleu )
Python 3.10 is out, every damn programmer is in love with the new structural pattern matching. But for anyone teaching python out there, the new error messages are what's up. (Before/After)
Thibault Clérice (ponteineptique on Ciel Bleu ) tweet mediaThibault Clérice (ponteineptique on Ciel Bleu ) tweet media
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stataholic
stataholic@stataholic·
Ecstatic to announce that I have joined Forbes as a Data Scientist. I am blessed to have landed in 5 offers (Data Scientist, MLE) from 1000+ applications, 30+ recruiter calls, 20+ technical interviews, 15+ Online assessments & 10+ final rounds. #DataScience #machinelearning
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Carrie Ann
Carrie Ann@barelycarrie·
slacking a coworker during a meeting and watching them have to suppress a laugh is my absolute greatest joy
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