Everything You Need to Know About High-Probability Breaker Blocks ⬇️ A Breaker Block forms when price trades through a previous Order Block (OB), invalidating it. What once acted as a zone of support or resistance now becomes the area where smart money re-enters the market.

$100K This guy did it in a week How? Thanks to bets on @Polymarket. The strategy is quite simple: choose bets with a 70-80% probability of success it's pretty easy and can bring in a lot of money, or just track bets from top traders

The Concept of Risk-to-Reward is Crazy When You Actually Understand It 📊🔥 Everyone wants to “never lose.” That’s not trading that’s fantasy. Losses will happen 💥 The real edge is knowing how to win despite them. Trading is a probability game 🎲 You’ll win some, lose some.

How to Catch a High Probability Turtle Soup Entry: 1. Identify a Higher Timeframe Sweep Start by identifying a sweep of liquidity on the higher timeframe either a significant high or low. This sets the foundation for a potential Turtle Soup (TS) setup. 2. Drop to a Lower

Good Morning! "If you torture the data long enough, it will confess to anything." - Ronald Coase

This comprehensive playlist (on YouTube) covers all the essential mathematics for deep learning - from linear algebra and calculus to probability theory and information theory. 18 lectures that will give you the mathematical foundation needed to understand modern AI systems.

Identifying a good setup is simple when you know what to look for: 🔸Clean price action in stage 2 stocks 🔸Strong volume footprint 🔸Setup trading above key EMA levels If these three conditions align and overall market health is solid, the probability of your setup working

$ETH needs to reclaim the key Moving Averages and R/S flip the Q4/2025 Timescape Levels to have a shot at a new ATH. Failure to do so increases the probability of a support test of the Yearly Open ~ $3,300.

This comprehensive Course will teach you all the mathematical foundations for Machine Learning. Link in comment 👇 - From Linear Algebra and Calculus to Probability, Optimization, and Python programming. - 39 lectures covering everything you need to get started with ML.

Probability Distributions

"Probability does not exist." This provocative quote is by the Italian statistician and probabilist Bruno de Finetti. It encapsulates the core idea of Subjectivism or Bayesianism, a major school of thought in probability. De Finetti argued that probability is not an objective

ANOVA (Analysis of Variance) is a statistical test that compares the means of three or more groups to determine if at least one is significantly different. In machine learning, it's a key tool for feature selection, checking if a categorical feature meaningfully impacts a

This setup was stacked with high probability.🎯

LLM Generation Parameters These are the primary controls used to influence the output of a Large Language Model. 1./ Temperature ◾ Controls the randomness of the output. It is applied to the probability distribution of the next possible tokens. ◾ Low Temperature (e.g., 0.2):

NEW: NIFTY Options Probability Indicator Backtested: NIFTY expires within ±2% range in 90% of weeks ✅ AUTO strategy switching (Bull Put/Bear Call/Strangle) ✅ Uses SuperTrend for trend detection ✅ Real-time alerts when strategy changes ✅ 64 probability levels for precision ✅

This book is just insane on Probability

ICT simply explaining what every High Probability Model requires. Read it.

Category theory is a mathematical language for describing how systems are built by composing parts. In machine learning, it offers a powerful framework for understanding the architecture of neural networks, viewing layers as functions that compose together. It also inspires

"Statistics is the science of learning from data, and of measuring, controlling, and communicating uncertainty." - David J. Hand