Zak Varty
Zak Varty
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Supervised Learning: 9.1 Polynomial Regression
Supervised Learning: 9.1 Polynomial Regression
Переглядів: 13

Відео

Supervised Learning: 8.4 Dimension Reduction Techniques11:59Supervised Learning: 8.4 Dimension Reduction Techniques
Supervised Learning: 8.4 Dimension Reduction Techniques
Переглядів 149 місяців тому
Supervised Learning: 8.4 Dimension Reduction Techniques
Supervised Learning: 8.1 More Predictors More Problems12:52Supervised Learning: 8.1 More Predictors More Problems
Supervised Learning: 8.1 More Predictors More Problems
Переглядів 139 місяців тому
Supervised Learning: 8.1 More Predictors More Problems
Supervised Learning: 5.3 Iteratively Reweighted Least Squares10:27Supervised Learning: 5.3 Iteratively Reweighted Least Squares
Supervised Learning: 5.3 Iteratively Reweighted Least Squares
Переглядів 3599 місяців тому
Supervised Learning: 5.3 Iteratively Reweighted Least Squares
Supervised Learning: 5.2 Generalised Linear Models9:18Supervised Learning: 5.2 Generalised Linear Models
Supervised Learning: 5.2 Generalised Linear Models
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Supervised Learning: 5.2 Generalised Linear Models
Supervised Learning: 5.1 The Exponential Family12:36Supervised Learning: 5.1 The Exponential Family
Supervised Learning: 5.1 The Exponential Family
Переглядів 139 місяців тому
Supervised Learning: 5.1 The Exponential Family
Supervised Learning: 4.3 Multinomial Regression14:06Supervised Learning: 4.3 Multinomial Regression
Supervised Learning: 4.3 Multinomial Regression
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Supervised Learning: 4.3 Multinomial Regression
Supervised Learning: 3.3 Logistic Regression MLE11:15Supervised Learning: 3.3 Logistic Regression MLE
Supervised Learning: 3.3 Logistic Regression MLE
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Supervised Learning: 3.3 Logistic Regression MLE
Supervised Learning: 3.2 Logistic Regression11:58Supervised Learning: 3.2 Logistic Regression
Supervised Learning: 3.2 Logistic Regression
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Supervised Learning: 3.2 Logistic Regression
Supervised Learning: 1.5 Supervised Learning Fundamentals13:13Supervised Learning: 1.5 Supervised Learning Fundamentals
Supervised Learning: 1.5 Supervised Learning Fundamentals
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Supervised Learning: 1.5 Supervised Learning Fundamentals
Supervised Learning 1.4: Model Compexity and the Bias-Variance Trade-off11:03Supervised Learning 1.4: Model Compexity and the Bias-Variance Trade-off
Supervised Learning 1.4: Model Compexity and the Bias-Variance Trade-off
Переглядів 19 місяців тому
Supervised Learning 1.4: Model Compexity and the Bias-Variance Trade-off
Supervised Learning 1.3: Metrics, Loss Functions and Optimisation18:33Supervised Learning 1.3: Metrics, Loss Functions and Optimisation
Supervised Learning 1.3: Metrics, Loss Functions and Optimisation
Переглядів 59 місяців тому
Supervised Learning 1.3: Metrics, Loss Functions and Optimisation
Supervised Learning 1.2: Types of Data11:23Supervised Learning 1.2: Types of Data
Supervised Learning 1.2: Types of Data
Переглядів 119 місяців тому
Supervised Learning 1.2: Types of Data
Supervised Learning 1.1: What is Supervised Learning11:42Supervised Learning 1.1: What is Supervised Learning
Supervised Learning 1.1: What is Supervised Learning
Переглядів 199 місяців тому
Supervised Learning 1.1: What is Supervised Learning
Effective Data Science - reproducibility25:58Effective Data Science - reproducibility
Effective Data Science - reproducibility
Переглядів 211 місяців тому
Effective Data Science - reproducibility
Effective Data Science - explainability16:09Effective Data Science - explainability
Effective Data Science - explainability
Переглядів 1511 місяців тому
Effective Data Science - explainability
Effective Data Science - scalability29:38Effective Data Science - scalability
Effective Data Science - scalability
Переглядів 211 місяців тому
Effective Data Science - scalability
Effective Data Science - data visualisation27:09Effective Data Science - data visualisation
Effective Data Science - data visualisation
Переглядів 411 місяців тому
Effective Data Science - data visualisation
Effective Data Science - data exploration19:57Effective Data Science - data exploration
Effective Data Science - data exploration
Переглядів 311 місяців тому
Effective Data Science - data exploration
Effective Data Science - data wrangling in R24:29Effective Data Science - data wrangling in R
Effective Data Science - data wrangling in R
Переглядів 911 місяців тому
Effective Data Science - data wrangling in R
Effective Data Science - accessing APIs26:42Effective Data Science - accessing APIs
Effective Data Science - accessing APIs
Переглядів 911 місяців тому
Effective Data Science - accessing APIs
Effective Data Science - web scraping21:58Effective Data Science - web scraping
Effective Data Science - web scraping
Переглядів 811 місяців тому
Effective Data Science - web scraping
Effective Data Science - tabular data25:16Effective Data Science - tabular data
Effective Data Science - tabular data
Переглядів 311 місяців тому
Effective Data Science - tabular data
Extreme Value Theory: 5.3 Beyond univariate extremes18:32Extreme Value Theory: 5.3 Beyond univariate extremes
Extreme Value Theory: 5.3 Beyond univariate extremes
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Extreme Value Theory: 5.3 Beyond univariate extremes
Extreme Value Theory: 5.2 Financial metrics and extreme value theory16:56Extreme Value Theory: 5.2 Financial metrics and extreme value theory
Extreme Value Theory: 5.2 Financial metrics and extreme value theory
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Extreme Value Theory: 5.2 Financial metrics and extreme value theory
Extreme Value Theory: 5.1 Hill estimation for heavy-tailed data8:14Extreme Value Theory: 5.1 Hill estimation for heavy-tailed data
Extreme Value Theory: 5.1 Hill estimation for heavy-tailed data
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Extreme Value Theory: 5.1 Hill estimation for heavy-tailed data
Extreme Value Theory: 4.3 Inference for extremes of stationary processes11:01Extreme Value Theory: 4.3 Inference for extremes of stationary processes
Extreme Value Theory: 4.3 Inference for extremes of stationary processes
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Extreme Value Theory: 4.3 Inference for extremes of stationary processes
Extreme Value Theory: 4.2 POT and point process models for extremes of stationary processes6:58Extreme Value Theory: 4.2 POT and point process models for extremes of stationary processes
Extreme Value Theory: 4.2 POT and point process models for extremes of stationary processes
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Extreme Value Theory: 4.2 POT and point process models for extremes of stationary processes
Extreme Value Theory: 4.1 Block maxima for stationary sequences8:56Extreme Value Theory: 4.1 Block maxima for stationary sequences
Extreme Value Theory: 4.1 Block maxima for stationary sequences
Переглядів 77Рік тому
Extreme Value Theory: 4.1 Block maxima for stationary sequences
Extreme Value Theory: 3.2 Modelling non-identically distributed extremes in R18:27Extreme Value Theory: 3.2 Modelling non-identically distributed extremes in R
Extreme Value Theory: 3.2 Modelling non-identically distributed extremes in R
Переглядів 108Рік тому
Extreme Value Theory: 3.2 Modelling non-identically distributed extremes in R

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