#bayesianstatistics

[aicollider]

Explaining Bayesian Statistics using Queen

Return exactly the same text but decorate important words and names with markdown. Be creative. Use bold, italic and insert relevant links: Bayesian statistics, like Queen, is regal and authoritative in its approach to analyzing data. Just like how Queen Elizabeth II rules with grace and wisdom, Bayesian statistics provides a powerful framework for making inferences and predictions by combining…

[yasudai]

#ウイル・カート 「 #楽しみながら学ぶ #ベイズ統計 」 #水谷淳 訳 読了。 タイトル通り、楽しくベイズ統計の基本を学ぶことができた。また本書で、確率を論理演算の拡張として捉える考え方を知り、新鮮に感じた。 (統計ソフト #R の基礎も復習できて嬉しいです。😉) 理解を定着させるために、じっくりと再読したい。 #willkurt #bayesianstatistics #thefunway #R https://www.instagram.com/p/CGh2iEmAxJs/?igshid=1l8ywdxlygo53

[expertlytics]

———————————————————————— A mostly complete chart of Neural Networks ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datamining #dataprocessing #datavisualization #dataviz #machinelearning #ensemblelearning #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics #neuralnetwork #deeplearning (at United States)

[cortogantese]

Bayesian doodle

[phungthaihy]

Probability and Statistics: Conditional Probability http://ehelpdesk.tk/wp-content/uploads/2020/02/logo-header.png [ad_1] This tutorial provides an introd... #365datascience #365datascience #academics #bayesformula #bayesrule #bayestheorem #bayesiananalysis #bayesianinference #bayesianprobability #bayesianstatistics #calculus #chineselanguage #conditionalprobability #conditionalprobabilityformula #conditionalprobabilityinreallife #conditionalprobabilityproblems #datascience #datastructures #englishconversation #englishgrammar #englishlanguage #frenchlanguage #germanlanguage #ielts #japaneselanguage #linearalgebra #math #probability #probabilityandstatistics #probabilitydistribution #probabilityformula #probabilityproblems #probabilityquestions #signlanguage #spanishlanguage #statistics #statisticstutorials #teaching #thebible

[statdude-blog]

A complete course on Bayesian Statistics by Ben Lambert at Ox educ

[expertlytics]

———————————————————————— One of the important assumption of linear regression is that conditional variance of Y (Conditioned by X) is same across the levels of independent variable X. This is called as Homoscedasticity. — If this assumption fails (Not equal variance across the levels of independent variable - Heterosedasticity), the estimate produces by OLS (Ordinary Least Square) will be no longer minimum variance estimate. ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datamining #dataprocessing #datavisualization #dataviz #machinelearning #ensemblelearning #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics (at United States)

[expertlytics]

———————————————————————— Multicollinearity means that some of the regressors(Independent variables) are highly correlated with each other. — It will make the estimate highly in-stable. This instability will increase the variance of estimates. It means that if there is a small change in X, produces large changes in estimate. ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datamining #dataprocessing #datavisualization #dataviz #machinelearning #ensemblelearning #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #multicollinearity #predictiveanalytics (at United States)

[expertlytics]

———————————————————————— Statistical inference makes propositions about a population, using data drawn from the population with some form of sampling. Given a hypothesis about a population, for which we wish to draw inferences, statistical inference consists of (firstly) selecting a statistical model of the process that generates the data and (secondly) deducing propositions from the model. ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datamining #dataprocessing #datavisualization #dataviz #machinelearning #ensemblelearning #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics (at United States)

[expertlytics]

———————————————————————— It is a classification technique based on Bayes’ Theorem with an assumption of independence among predictors. In simple terms, a Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature. — For example, a fruit may be considered to be an apple if it is red, round, and about 3 inches in diameter. Even if these features depend on each other or upon the existence of the other features, all of these properties independently contribute to the probability that this fruit is an apple and that is why it is known as ‘Naive’. Naive Bayes model is easy to build and particularly useful for very large data sets. Along with simplicity, Naive Bayes is known to outperform even highly sophisticated classification methods. — How Naive Bayes algorithm works? — Step 1: Convert the data set into a frequency table — Step 2: Create Likelihood table by finding the probabilities. — Step 3: Now, use Naive Bayesian equation to calculate the posterior probability for each class. The class with the highest posterior probability is the outcome of prediction. ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datamining #dataprocessing #datavisualization #dataviz #machinelearning #ensemblelearning #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics (at United States)

[expertlytics]

———————————————————————— Linear Discriminant Analysis (LDA) is most commonly used as dimensionality reduction technique in the pre-processing step for pattern-classification and machine learning applications. — The goal is to project a dataset onto a lower-dimensional space with good class-separability in order avoid overfitting (“curse of dimensionality”) and also reduce computational costs. — ‪The general LDA approach is very similar to a Principal Component Analysis, but in addition to finding the component axes that maximize the variance of our data (PCA), we are additionally interested in the axes that maximize the separation between multiple classes (LDA).‬ ‪—‬ So, in a nutshell, often the goal of an LDA is to project a feature space (a dataset n-dimensional samples) onto a smaller subspace. ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datamining #dataprocessing #datavisualization #dataviz #machinelearning #lda #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics #математика #физика #lineardiscriminantanalysis #dimensionalityreduction (at United States)

[expertlytics]

———————————————————————— And yet another set of various 3D visualizations ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datavisualization #dataviz #datamining #machinelearning #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics #calculations #математика #физика #наука #статистика (at United States)

[expertlytics]

———————————————————————— Various 3D visualizations ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datavisualization #dataviz #datamining #machinelearning #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics #calculations #математика #физика #наука #статистика (at United States)

[expertlytics]

———————————————————————— Bayes’ theorem is a way to figure out conditional probability. Conditional probability is the probability of an event happening, given that it has some relationship to one or more other events. — For example, your probability of getting a parking space is connected to the time of day you park, where you park, and what conventions are going on at any time. — Bayes’ theorem is slightly more nuanced. In a nutshell, it gives you the actual probability of an event given information about tests. ———————————————————————— #data #datascience #datascientist #datamining #datavisualization #dataviz #bigdata #bigdataanalytics #coding #statistics #probability #machinelearning #artificialintelligence #database #mathematics #math #science #research #scientist #studygram #learning #computerscience #analysis #analytics #visualization #bayes #математика #статистика #bayestheorem #bayesianstatistics (at United States)

[expertlytics]

———————————————————————— Additional set of Data Science 3D various visualizations ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datavisualization #dataviz #datamining #machinelearning #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics #calculations #математика #физика #наука #статистика (at United States)

[expertlytics]

———————————————————————— Intuitive explanation of Gradient Descent Algorithm: - Suppose you are on the top of a mountain. You want to climb down from the mountain. What will you do? You will take a fewer steps downwards until you reach to the base of the mountain. - Here there are two cases: - i) Take small steps(very tiny) : Well you will die of hunger before you reach to the base. - ii) Take huge steps(gigantic..really) : Well you jump off the cliff and the next thing a chopper will find your shattered pieces of body. You don’t want to die obviously.. so you take steps enough to reach the base in time. ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datavisualization #dataviz #datamining #machinelearning #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics #calculations #математика #физика #наука #статистика (at United States)