๐24H FREE Trial | Premium 4K & Ultra HD IPTV โข Live TV from ๐บ๐ธ USA,๐ฌ๐ง UK, ๐จ๐ฆ Canada, ๐ซ๐ท France, ๐ช๐บ Europe & ๐ Arabic. Sports, Movies, Series & More
๐บ Stream your favorite channels on Fire TV, Android TV, Smart TV, Google TV, MAG & mobile devices! ๐ท
โฝ Live Sports | ๐ท Movies | ๐ท
๐ฉ DM for available plans & setup details.
Who need 8k/4k/UHD Premium UK IPTV Subscription?
W.A me ๐ฉ
Available for...
(Firestick, Android TVs, Smart TVs iOS Devices, LaptopPhone Samsung TvTivimate) UK USA)๐ฌ๐ง๐ฎ๐ช๐บ๐ธ
I found 5 free Polymarket weather trading bots on GitHub (from simple automation to a full machine learning model)โฆ
Each of these repos comes with a detailed step by step setup guide and can also be used for trading on other prediction market platforms.
> For beginners (5 min setup):
1. A Hermes weather trading bot.
This is an autonomous bot that collects weather data from multiple sources and uses a Gaussian Bucket strategy - for example, if the forecast is 69F, it estimates that the final temperature will be between 68F and 70F.
Then it compares this range with current Polymarket prices and sends you trading signals directly to Telegram.
The best feature - this bot can track and analyze its own results, learn from them and improve its strategy over time.
GitHub: https://t.co/thJFzc3T3v
2. NWS forecast bot + Kelly strategy.
This bot scans the latest NWS temperature data for a selected city and compares it with current odds on Polymarket.
After that, it uses the Kelly sizing to calculate the best trade size based on how strong this edge is and automatically executes trades.
GitHub: https://t.co/OBdsje8MAm
> More advanced bots:
3. GFS based trading bot.
It uses 31 different forecast scenarios from the Global Forecast System to estimate the most likely temperature for a specific city and day.
This bot also has a web dashboard where you can track all its trades, forecasts, pnl, win rate and more.
GitHub: https://t.co/MivMwpDYcF
4. Real time weather analysis bot.
It scans multiple sources like public airport data and aviation observations (METAR + SPECI) to get the latest available temperature data.
Then it generates a detailed weather report for a whole day/week/month for any city and day.
GitHub: https://t.co/No3sBcqMg1
5. A Machine Learning weather model.
It was built by a Boston University cs student for his bachelors thesis.
How it works:
Instead of blindly trusting weather forecasts, this model learns from their historical errors.
For example, if the NWS repeatedly predicted a high of 75F in Chicago, but the actual daily high was closer to 70F, the model learns that this source overestimates temperatures in Chicago by around 5F under similar conditions.
And when a new forecast comes in, the model adjusts it using what it learned from previous errors and produces a more accurate temperature estimate.
GitHub: https://t.co/9DnTPu5iKE
All of these bots include a simulation mode, so you can test them on real markets without risking any funds.
The destination is no longer a secret.
MEXC0808 Stock Season registration is officially open.
Be among the first to unlock exclusive rewards.
Register now โ
Your Obsidian vault burns 300,000 tokens to answer one question. A graph reads 3 files and answers in under a second
Ask AI one question in a flat vault and it reads every note. 2,000 files, hundreds of thousands of tokens, for one answer. Slow, expensive, still grabs the wrong file half the time.
A second brain is only as good as the graph underneath it, not the vault.
This breaks down the 11-step build:
router > index > nodes > edges, and the logic that lets Fable 5 open 2-3 files instead of the whole folder.
The result from one real build: cost drops sharply, answers come back faster on almost every question.
The graph view everyone screenshots is a poster. The index is the engine.
Save this before you rebuild your vault from scratch ๐
Looking for premium IPTV in the ๐ฌ๐ง UK | USA | Australia? ๐ฆ๐บ
๐บ Live TV โข Sports โข Movies โข Series โข
International channels ๐ท Firestick โข Smart TV
Android โข Apple TV โข Roku ๐ท
DM now!๐ฅ๐ฌ๐ง๐บ๐ธ