Knowledge of probability theory commonly used in machine learning - Code World

Knowledge of probability theory commonly used in machine learning

Mobile 2023-07-30 05:30:16 views: null

This article is well written.
Prior probability: refers to the probability obtained based on past experience and analysis. Posterior probability: based on new information, the probability estimation likelihood function
obtained after correcting the original prior probability is closer to the actual situation.
:

Guess you like

Origin blog.csdn.net/qq_45560230/article/details/130903001

Knowledge of probability theory commonly used in machine learning

Machine learning some basic knowledge of probability theory

Review of Probability Theory Knowledge Involved in Machine Learning (2)

Review of Probability Theory Knowledge Involved in Machine Learning (1)

[Probability Theory] Commonly used continuous distributions (1)

[Machine Learning] Basic Probability Theory and Information Theory

Mathematical foundations of machine learning - Probability Theory

Linear algebra and probability theory - the basis of machine learning

Distances commonly used in machine learning

Summary of probability and statistics knowledge points in machine learning

Some knowledge of probability theory

Machine learning commonly used variable names

Machine Learning Method for processing data commonly used

Finishing machine learning commonly used loss function

Summary of commonly used python machine learning libraries

Comparison of classifiers commonly used in machine learning

Probability Theory and Mathematical Statistics Study Notes - Lecture 39 - Statistics, Commonly Used Statistics

[] Machine learning machine learning to commonly used terms and explanations

Learning and sorting out probability theory and stochastic processes 20: I know conditional probability, but what is conditional expectation? can be used to solve recursive problems

Introduction to machine learning theory and pre-requisite knowledge

Commonly used knowledge in Unity

Stanford CS229 Machine Learning Course Mathematics Foundation (Probability Theory) translation completed

Machine Learning Algorithm (3) Classification Method Based on Probability Theory: Naive Bayes

Python implementation of Kalman filtering and application case analysis - probability theory series of machine learning

Hertz Futures Quantitative Trading Software: Data Science and Machine Learning (Part 11): Naive Bayes, Probability Theory in Trading

Applying Probability Theory and Fuzzy Systems: Accurate Predictions from Machine Learning Models

Machine Learning Practice Chapter 4 Classification Method Based on Probability Theory: Naive Bayes

Probability Theory and Mathematical Statistics (Overview of Knowledge Points)

Some basic knowledge about probability theory

Probability theory knowledge supplement-Gaussian distribution

Recommended

Ranking

Empire cms smart tag calls four first-level recommended articles, starting from the fourth article

Linux environment installation and configuration Elasticsearch7.17

Big Data processing architecture and Lambda Kappa architecture

Explore the top of the AI large model platform - Wenxin Qianfan

Beijing car PK10 lucky airship Guanya size and value of the odd and even tips

W3B x Sui Hacker House｜In-depth understanding of Sui and Move language

Know almost Ko Chan: Chinese what any decent open source software products? (Finishing from my original answer)

Comprehensively improve AD domain security authentication | Zhuyun IDaaS

Android Update Engine Analysis (24) What happened when making the downgrade package?

Spark Architecture and Operating Mechanism (1) - System Architecture

Daily

More

2024-05-07(34)

2024-05-06(6)

2024-05-05(0)

2024-05-04(18)

2024-05-03(8)

2024-05-02(0)

2024-05-01(4)

2024-04-30(36)

2024-04-29(5)

2024-04-28(12)