Learn Bayesian
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CS3105 AI
CS3105 AI
By: Tom Hardern
1: Search, 2: Logic, 3: Attacks on AI ...8Decks388Flashcards5Learners -
Machine Learning
Machine Learning
By: Unknown Unknown
Lecture 9 - Bayesian inference: approximation & sampling, Lecture 10 - Clustering: K-Means, Lecture 11 - Clustering: EM Algorithm for GMM ...10Decks155Flashcards1Learner -
BioStats
BioStats
By: Adjmal Sarwary
Descriptive Statistics, Inferential Statistics, Probability Distributions ...14Decks560Flashcards2Learners -
PhD
PhD
By: Catherine Holland
PhD, Compositional Data, Distributions ...7Decks69Flashcards1Learner -
statistics
statistics
By: Lasse Alsbirk
Introduction, Parametric models, Bayesian inference ...11Decks124Flashcards1Learner -
Research Methods and Stats 4
Research Methods and Stats 4
By: Hannah Bricklebank
1. Thematic Analysis, 2. Grounded Theory, Interpretative Phenomenological Analysis ...10Decks141Flashcards1Learner -
Interim 4
Interim 4
By: Lauranne Kloos
Agresti chapter 3, Agresti chapter 12, Agresti chapter 14 ...5Decks34Flashcards1Learner -
STA3030F
STA3030F
By: Mbongeni Sibanda
Generalized Linear Models, Bayesian Inference & Decision Theory, Machine Learning ...4Decks140Flashcards8Learners -
Probability for ML
Probability for ML
By: Mahsa Zamanifard
Chapter 4 Joint, Marginal, and Conditional Probability, Chapter 7 Probability Distributions, Chapter 8 Discrete Probability Distributions ...21Decks287Flashcards21Learners -
ETC2560
ETC2560
By: Cindy Patricia
exploratory data analysis (week 1-2), Linear regression (week 3-5), Generalised Linear Model (week 6-8) ...4Decks146Flashcards1Learner -
Statistical Concepts - Epiphany
Statistical Concepts - Epiphany
By: Hollie Pilkington
Distribution Theory, Comparing two samples, Bayesian Statistics ...4Decks158Flashcards3Learners -
Econometrics 2 - Phd
Econometrics 2 - Phd
By: Christian Lundqvist
Shift-share IV, DiD & Synthetic Controls, Clustering and bootstrap ...6Decks107Flashcards1Learner -
MATH2715 Statistical Methods
MATH2715 Statistical Methods
By: Sophie Wilkinson
1. Probability, 2. Random Variables, 3. Joint Distributions ...10Decks184Flashcards20Learners -
Statistical Theory
Statistical Theory
By: Daniel Vegara
Review, Principles of point estimation, Likelihood-based estimation ...7Decks74Flashcards3Learners -
BMS2042
BMS2042
By: Chiara Piazzese
TOPIC 1: MENDEL AND EXTENSIONS TO MENDEL, WEEK 4, WEEK 3: LINKAGE, RECOMB, AND GENETIC MAPPING ...11Decks783Flashcards13Learners -
Statistics for Machine Learning
Statistics for Machine Learning
By: Ozzy Campos
1. Fundamentals of Probability, 2. Probability Distributions, 3. Descriptive Statistics ...9Decks893Flashcards1Learner -
STATS Lectures Flashcards
STATS Lectures Flashcards
By: Sterre Van Driesten
Lecture 10: ANOVA, Lecture 12: ANCOVA, Lecture 13: Factorial ANOVA ...7Decks83Flashcards1Learner -
Scientific and Statistical Reasoning 2
Scientific and Statistical Reasoning 2
By: Megan H
Lecture 10: ANOVA: F distribution and one way independent, Lecture 11 Critical thinking about psychological research, Lecture 16: Chi-square t4est ...11Decks588Flashcards1Learner -
Artificial intelligence
Artificial intelligence
By: Klara :D
2 - agents, 3 - uninformed search, 4 - informed search ...10Decks78Flashcards3Learners -
STAT20180
STAT20180
By: Sarah Oliver
Chapter 1 : Probability recap, Chapter 2 Bayesian Inference, Chapter 3 Monte Carlo Approximation ...5Decks104Flashcards1Learner -
KCL Elements of Statistical Learning
KCL Elements of Statistical Learning
By: tyrion lannister
Week 2 (MLE, MAP, Bayesian Curve, Entropy), Week 5 (GMM), Week 6 ( (Fishers/)Linear Discriminant) ...10Decks115Flashcards1Learner -
365 Data Science - Probability
365 Data Science - Probability
By: R W
1. The Basics of Probability, Combinatorics, Bayesian Inference ...6Decks222Flashcards3Learners -
Data Science & Big Data Analytics
Data Science & Big Data Analytics
By: Tom Burgoyne
01. Introduction to Big Data Analytics, 12. The Endgame, or Putting It All Together, 11. SQL Essentials & Advanced ...14Decks231Flashcards42Learners -
Algorithms For Machine Learning And Inference
Algorithms For Machine Learning And Inference
By: Rasmus Johansson
Linear Modeling and Regression, Probabilistic Linear Regression, Bayesian linear regression ...15Decks434Flashcards1Learner -
PSYG1004 - Intro to RM and Analysis
PSYG1004 - Intro to RM and Analysis
By: S K
Variables, Design and Hypothesis, Descriptive Statistics, Distributions and Probability ...16Decks344Flashcards1Learner -
Interim Exam 4
Interim Exam 4
By: oisin mcelwain
Cognitive: Motor control and Action, Statistics: Analysis of Variance methods, Cognition: Problem solving ...12Decks451Flashcards3Learners -
US presidential election
US presidential election
By: Marie Sofie Spanggaard Jespersen
F1 Introduction to forecast modelling, F2 Structural fundamentals, F3 Fundamentals model ...13Decks248Flashcards4Learners -
AQM
AQM
By: Micia Sanghera
Psychological model fitting, SEM- structural equation modelling, Logistic regression ...5Decks131Flashcards4Learners -
research methods year 1 set 2
research methods year 1 set 2
By: georgie kafton
Significance and power, ANOVA (between groups), ANOVA (within-subjects) ...9Decks139Flashcards2Learners -
Machine Learning Engineering
Machine Learning Engineering
By: Sander Moonemans
Linear Models, Kernelization, Data Preprocessing ...4Decks45Flashcards4Learners