Dirichlet Distribution - Explained скачать в хорошем качестве

Dirichlet Distribution - Explained

The Dirichlet distribution is a powerful tool in Bayesian statistics for modeling probabilities across multiple categories, extending the Beta distribution to more than two outcomes. In this video, we explain the Dirichlet distribution with intuitive examples, its relation to the Beta distribution, applications in machine learning, natural language processing, computational biology, and probability modeling, and how it helps capture uncertainty in categorical data. Related Videos ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Bayesian Optimization:    • Bayesian Optimization   Hyperparameters Tuning: Grid Search vs Random Search:    • Hyperparameters Tuning: Grid Search vs Ran...   The Kernel Trick:    • The Kernel Trick   Cross-Entropy - Explained:    • Cross-Entropy - Explained   Dropout - Explained:    • Dropout in Neural Networks - Explained   Overfitting vs Underfitting:    • Overfitting vs Underfitting - Explained   Why Models Overfit and Underfit - The Bias Variance Trade-off:    • Bias-Variance Trade-off - Explained   Least Squares vs Maximum Likelihood:    • Least Squares vs Maximum Likelihood   XGBoost Explained in Under 3 Minutes:    • XGBoost Explained in Under 3 Minutes   Contents ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 00:00 - Intro 00:50 - Two categories example 01:42 - Three categories example 02:14 - The Dirichlet distribution 02:45 - Drawing from Dirichlet 03:23 - Mathematical intuition 04:15 - Convergence properties 04:51 - Bayesian statistics 05:37 - The probability simplex 06:28 - Alpha concentration 07:50 - Outro Follow Me ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 🐦 Twitter: @datamlistic   / datamlistic   📸 Instagram: @datamlistic   / datamlistic   📱 TikTok: @datamlistic   / datamlistic   👔 Linkedin:   / datamlistic   Channel Support ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ The best way to support the channel is to share the content. ;) If you'd like to also support the channel financially, donating the price of a coffee is always warmly welcomed! (completely optional and voluntary) ► Patreon:   / datamlistic   ► Bitcoin (BTC): 3C6Pkzyb5CjAUYrJxmpCaaNPVRgRVxxyTq ► Ethereum (ETH): 0x9Ac4eB94386C3e02b96599C05B7a8C71773c9281 ► Cardano (ADA): addr1v95rfxlslfzkvd8sr3exkh7st4qmgj4ywf5zcaxgqgdyunsj5juw5 ► Tether (USDT): 0xeC261d9b2EE4B6997a6a424067af165BAA4afE1a #bayestheorem #probability #statistics #machinelearning #datascience