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Partial Dependence Plots in Structured Classification

Interpreting machine learning models can be defined as a process of identifying the different characteristics of that particular model. The main reason for interpreting/explaining the machine learning model is that the user wants to know how the model works and has trust issues. There are several interpretability techniques, which

Grad-CAM++: White Box Explainability for Image Classification

Grad-CAM++: White Box Explainability for Image Classification

Grad-CAM ++ is one of the most reliable and widely used explainability techniques for CNN because of its lucidity and efficaciousness.

LIME Technique for Text Classification

LIME Technique for Text Classification

LIME stands for Local Interpretable Model agnostic Explanations. Local means related to a single prediction. Now, to the term model agnostic. It means that there is no need for information regarding the internal structure of the model.

Lime for Image Classification

Lime for Image Classification

You can not come to conclusion based only on numerical features. LIME helps to overcome this issue and gives you explanation about your AI model.

SHAP Feature Importance in Audio Classification

SHAP Feature Importance in Audio Classification

Audio Classification is one of the most widely used applications nowadays and a lot of research has been done on classifying audio using different kinds of features and neural network architectures. Some real-world applications of this is Speaker Recognition, Music Genre Classification, and Bird Sound Classification. The most commonly used

Guided Grad-CAM for White Box Explainability of Image Classifiers

Convolution Neural Network expanded its task from Image classification to Image captioning. With the expansion of this task, the architecture of CNN has been evolving into a more complex structure. With the increase in complexity, interpretability has been a major challenge. Because of these interpretability issues, should we trust CNN

SHAP Feature Importance in Text Classification

SHAP Feature Importance in Text Classification

In this blog, we'll be primarily focused on the text classification task of Natural language processing (NLP). We'll be using quality entertainment resources called Rotten Tomatoes and the Tomato meter score online aggregator of movie and TV show reviews from critics, which provide fans with a