A Data Odyssey

@UChsoWqJbEjBwrn00Zvghi4w - 10.9K subscribers

Data exploration, interpretable machine learning, explainable AI and algorithm fairness

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Applying LIME with Python & Captum — Explaining Image Classification Models

Applying LIME with Python & Captum — Explaining Image Classification Models A Data Odyssey

948 views - 2 months ago

How LIME Works for Computer Vision | Superpixels, Perturbations & Surrogate Models

How LIME Works for Computer Vision | Superpixels, Perturbations & Surrogate Models A Data Odyssey

271 views - 2 months ago

Limitations of Explainable AI - Why You Should Be Sceptical of Saliency Maps

Limitations of Explainable AI - Why You Should Be Sceptical of Saliency Maps A Data Odyssey

1.1K views - 2 months ago

Axioms for Explainable AI — Comparing Integrated Gradients, SHAP & DeepLIFT

Axioms for Explainable AI — Comparing Integrated Gradients, SHAP & DeepLIFT A Data Odyssey

338 views - 2 months ago

Evaluating Explainable AI — From User Studies to Sanity Checks (Deep Learning)

Evaluating Explainable AI — From User Studies to Sanity Checks (Deep Learning) A Data Odyssey

362 views - 3 months ago

Integrated Gradients Explained — Theory, Axioms & Python Implementation

Integrated Gradients Explained — Theory, Axioms & Python Implementation A Data Odyssey

1K views - 3 months ago

DeepLIFT with Python — How Baseline Choice Affects Attributions

DeepLIFT with Python — How Baseline Choice Affects Attributions A Data Odyssey

145 views - 3 months ago

How DeepLIFT Explains Neural Network Predictions | Explainable AI for Computer Vision

How DeepLIFT Explains Neural Network Predictions | Explainable AI for Computer Vision A Data Odyssey

844 views - 3 months ago

Guided Grad-CAM with Python (Captum) — Class-Discriminative Saliency Maps Made Simple

Guided Grad-CAM with Python (Captum) — Class-Discriminative Saliency Maps Made Simple A Data Odyssey

500 views - 3 months ago

SmoothGrad Explained: How Adding Noise Removes Noise in Saliency Maps

SmoothGrad Explained: How Adding Noise Removes Noise in Saliency Maps A Data Odyssey

376 views - 4 months ago

Input X Gradients Explained: Why This XAI Method Can Mislead You

Input X Gradients Explained: Why This XAI Method Can Mislead You A Data Odyssey

347 views - 4 months ago

Channel Update | Free Course, Future Videos & PhD Progress

Channel Update | Free Course, Future Videos & PhD Progress A Data Odyssey

585 views - 4 months ago

The limitations of Vanilla Gradients | Explainable AI for Computer Vision

The limitations of Vanilla Gradients | Explainable AI for Computer Vision A Data Odyssey

588 views - 11 months ago

Occlusion in Practice with Python and Captum | XAI for Computer Vision

Occlusion in Practice with Python and Captum | XAI for Computer Vision A Data Odyssey

622 views - 11 months ago

Occlusion-Based Saliency Maps | Explainable AI for Computer Vision

Occlusion-Based Saliency Maps | Explainable AI for Computer Vision A Data Odyssey

2.3K views - 1 year ago

Taxonomy of Explainable AI Methods in Computer Vision | Free XAI Course

Taxonomy of Explainable AI Methods in Computer Vision | Free XAI Course A Data Odyssey

1K views - 1 year ago

Build Class Activation Maps (CAMs) from Scratch with Python & PyTorch Hooks | Free XAI Course

Build Class Activation Maps (CAMs) from Scratch with Python & PyTorch Hooks | Free XAI Course A Data Odyssey

901 views - 1 year ago

Understanding Class Activation Maps (CAMs) for Deep Learning Interpretability | Free XAI Course

Understanding Class Activation Maps (CAMs) for Deep Learning Interpretability | Free XAI Course A Data Odyssey

2.7K views - 1 year ago

Implementing Guided Backpropagation from Scratch | PyTorch Hooks & Deep Learning Interpretability

Implementing Guided Backpropagation from Scratch | PyTorch Hooks & Deep Learning Interpretability A Data Odyssey

1.1K views - 1 year ago

Guided Backpropagation theory | FREE Explainable AI (XAI) Course with Python

Guided Backpropagation theory | FREE Explainable AI (XAI) Course with Python A Data Odyssey

1.7K views - 1 year ago

Grad-CAM with Python | FREE XAI Course | L7 - Gradient-weighted Class Activation Mapping

Grad-CAM with Python | FREE XAI Course | L7 - Gradient-weighted Class Activation Mapping A Data Odyssey

5K views - 1 year ago

Grad-CAM Explained | FREE XAI Course | L7 - Gradient-weighted Class Activation Mapping

Grad-CAM Explained | FREE XAI Course | L7 - Gradient-weighted Class Activation Mapping A Data Odyssey

21K views - 1 year ago

Debugging a Pot Plant Detector | FREE Python Course | L1 - The Importance of XAI in Computer Vision

Debugging a Pot Plant Detector | FREE Python Course | L1 - The Importance of XAI in Computer Vision A Data Odyssey

644 views - 1 year ago

Applying Permutation Channel Importance (PCI) to a Remote Sensing Model | Python Tutorial

Applying Permutation Channel Importance (PCI) to a Remote Sensing Model | Python Tutorial A Data Odyssey

469 views - 1 year ago

Explaining Computer Vision Models with PCI

Explaining Computer Vision Models with PCI A Data Odyssey

1.2K views - 1 year ago

Explaining Anomalies with Isolation Forest and SHAP | Python Tutorial

Explaining Anomalies with Isolation Forest and SHAP | Python Tutorial A Data Odyssey

16K views - 1 year ago

SHAP with CatBoostClassifier for Categorical Features | Python Tutorial

SHAP with CatBoostClassifier for Categorical Features | Python Tutorial A Data Odyssey

5.2K views - 1 year ago

Applying LIME with Python | Local & Global Interpretations

Applying LIME with Python | Local & Global Interpretations A Data Odyssey

4.6K views - 2 years ago

An introduction to LIME for local interpretations | Intuition and Algorithm |

An introduction to LIME for local interpretations | Intuition and Algorithm | A Data Odyssey

16K views - 2 years ago

Friedman's H-statistic Python Tutorial | Artemis Package

Friedman's H-statistic Python Tutorial | Artemis Package A Data Odyssey

1.7K views - 2 years ago

Friedman's H-statistic for Analysing Interactions | Maths and Intuition

Friedman's H-statistic for Analysing Interactions | Maths and Intuition A Data Odyssey

3.9K views - 2 years ago

Accumulated Local Effect Plots (ALEs) | Explanation & Python Code

Accumulated Local Effect Plots (ALEs) | Explanation & Python Code A Data Odyssey

4K views - 2 years ago

PDPs and ICE Plots | Python Code | scikit-learn Package

PDPs and ICE Plots | Python Code | scikit-learn Package A Data Odyssey

2.9K views - 2 years ago

Partial Dependence (PDPs) and Individual Conditional Expectation (ICE) Plots | Intuition and Math

Partial Dependence (PDPs) and Individual Conditional Expectation (ICE) Plots | Intuition and Math A Data Odyssey

8.5K views - 2 years ago

Permutation Feature Importance from Scratch | Explanation & Python Code

Permutation Feature Importance from Scratch | Explanation & Python Code A Data Odyssey

5.2K views - 2 years ago

Model Agnostic Methods for XAI | Global v.s. Local | Permutation v.s. Surrogate Models

Model Agnostic Methods for XAI | Global v.s. Local | Permutation v.s. Surrogate Models A Data Odyssey

1.7K views - 2 years ago

8 Plots for Explaining Linear Regression | Residuals, Weight, Effect & SHAP

8 Plots for Explaining Linear Regression | Residuals, Weight, Effect & SHAP A Data Odyssey

2.4K views - 2 years ago

Feature Selection using Hierarchical Clustering | Python Tutorial

Feature Selection using Hierarchical Clustering | Python Tutorial A Data Odyssey

7.2K views - 2 years ago

8 Characteristics of a Good Machine Learning Feature | Predictive, Variety, Interpretability, Ethics

8 Characteristics of a Good Machine Learning Feature | Predictive, Variety, Interpretability, Ethics A Data Odyssey

1K views - 2 years ago

Interpretable Feature Engineering | How to Build Intuitive Machine Learning Features

Interpretable Feature Engineering | How to Build Intuitive Machine Learning Features A Data Odyssey

1.4K views - 2 years ago

Modelling Non-linear Relationships with Regression

Modelling Non-linear Relationships with Regression A Data Odyssey

2.1K views - 2 years ago

Explaining Machine Learning to a Non-technical Audience

Explaining Machine Learning to a Non-technical Audience A Data Odyssey

2.2K views - 2 years ago

Get more out of Explainable AI (XAI): 10 Tips

Get more out of Explainable AI (XAI): 10 Tips A Data Odyssey

2.6K views - 2 years ago

The 6 Benefits of Explainable AI (XAI) | Improve accuracy, decrease harm and tell better stories

The 6 Benefits of Explainable AI (XAI) | Improve accuracy, decrease harm and tell better stories A Data Odyssey

4.6K views - 2 years ago

Introduction to Explainable AI (XAI) | Interpretable models, agnostic methods, counterfactuals

Introduction to Explainable AI (XAI) | Interpretable models, agnostic methods, counterfactuals A Data Odyssey

23K views - 2 years ago

Data Science vs Science | Differences & Bridging the Gap

Data Science vs Science | Differences & Bridging the Gap A Data Odyssey

390 views - 2 years ago

About the Channel and my Background | ML, XAI and Remote Sensing

About the Channel and my Background | ML, XAI and Remote Sensing A Data Odyssey

2.8K views - 2 years ago

SHAP for Binary and Multiclass Target Variables | Code and Explanations for Classification Problems

SHAP for Binary and Multiclass Target Variables | Code and Explanations for Classification Problems A Data Odyssey

23K views - 2 years ago

Introduction to Algorithm Fairness | Causes, Measuring & Preventing Unfairness in Machine Learning

Introduction to Algorithm Fairness | Causes, Measuring & Preventing Unfairness in Machine Learning A Data Odyssey

5.5K views - 2 years ago

SHAP Violin and Heatmap Plots | Interpretations and New Insights

SHAP Violin and Heatmap Plots | Interpretations and New Insights A Data Odyssey

11K views - 2 years ago

Correcting Unfairness in Machine Learning | Pre-processing, In-processing, Post-processing

Correcting Unfairness in Machine Learning | Pre-processing, In-processing, Post-processing A Data Odyssey

2.9K views - 2 years ago

Definitions of Fairness in Machine Learning | Equal Opportunity, Equalized Odds & Disparate Impact

Definitions of Fairness in Machine Learning | Equal Opportunity, Equalized Odds & Disparate Impact A Data Odyssey

9.3K views - 2 years ago

Exploratory Fairness Analysis | Quantifying Unfairness in Data

Exploratory Fairness Analysis | Quantifying Unfairness in Data A Data Odyssey

1.9K views - 2 years ago

5 Reasons for Unfair Models | Proxy Variables, Unbalanced Samples & Negative Feedback Loops

5 Reasons for Unfair Models | Proxy Variables, Unbalanced Samples & Negative Feedback Loops A Data Odyssey

3K views - 2 years ago

Feature Engineering with Image Data | Aims, Techniques & Limitations

Feature Engineering with Image Data | Aims, Techniques & Limitations A Data Odyssey

1.7K views - 3 years ago

Image Augmentation for Deep Learning | Benefits, Techniques & Best Practices

Image Augmentation for Deep Learning | Benefits, Techniques & Best Practices A Data Odyssey

4.5K views - 3 years ago

Interpretable vs Explainable Machine Learning

Interpretable vs Explainable Machine Learning A Data Odyssey

48K views - 3 years ago

4 Significant Limitations of SHAP

4 Significant Limitations of SHAP A Data Odyssey

22K views - 3 years ago

Shapley Values for Machine Learning

Shapley Values for Machine Learning A Data Odyssey

34K views - 3 years ago

The mathematics behind Shapley Values

The mathematics behind Shapley Values A Data Odyssey

68K views - 3 years ago