Artificial Intelligence / Machine Learning

GIT HUB PAGES: PROCEDURE TO CREATE PAGES ON GITHUB

INTRODUCTION: * You may build and host static web pages straight from your repository using GitHub Pages, a platform-integrated functionality. * GitHub Pages provides an effortless way to do so, whether you want to advertise a project, compile a group of projects, or publish documents. * We'll walk you through the process of

API MANAGEMENT: ENABLING TECHNOLOGY & AVAILABILITY

INTRODUCTION: * Application Programming Interfaces (APIs), which permit effortless communication and information exchange throughout many systems, have evolved into the foundation of digital communities in modern digital environment. * Organizations are confronted with the problem of successfully managing, protecting and optimizing their API infrastructure as the number of APIs continues to rise

Chatbots Comparison

In recent years our dependence on artificial intelligence has gone up due to the value that it brings to the table. With improvements in AI, businesses can optimize their resources in a better way than in the past. Chatbots have helped companies decrease the costs that they incur on customer

Individual Conditional Expectation(ICE) in Structured Classification

In the previous article, we discussed partial dependence plots and their working. In this article, we will discuss Individual Conditional Expectation(ICE). Similar to Partial Dependence Plots, Individual Conditional Expectation is also a model visualization technique. Drawbacks of Partial Dependence Plots Before jumping into the ICE let us discuss the

Tesla Car Crash in Autopilot Mode

Machine learning is one field that has grown exponentially over the last decade creating a large pool of opportunities and solving real-world problems. Companies have started adopting machine learning practices in their existing systems. Machine learning has many use cases from image classification, Natural Language Processing(NLP) to house price

Career opportunities in Data Science

Data science is just not a concept for the future but, it is our present now and we heavily depend on it. Data science has been there since the 1990s, but its value was understood only when businesses and companies were unable to use the enormous amount of data for

source- Google (https://www.varaklaw.com/wp-content/uploads/for-sale-sign-1024x682.jpg)

Artificial Intelligence / Machine Learning

Disaster due to untested Data and ML Model

Machine learning has been impacting a business revenue in a huge way, be it a top product-based company like Netflix where a recommondation system is worth $1 Billion, or any medium-scale company where machine learning models play a vital role in business decisions. By knowing its contribution towards revenue, should

Artificial Intelligence / Machine Learning

Accumulated Local Effects (ALE) Plot in Audio Classification

Model explainability refers to the concept of being able to understand the machine learning model. Being able to interpret a model increases trust in AI. There are two ways to interpret a model i.e. Global vs Local Interpretation. Global interpretation helps us in understanding how a model makes decisions

Artificial Intelligence / Machine Learning

Gradient-based Model Explainability Technique, GradCAM, for Object Detection Models

Image Analysis is one of the most demanding tools to achieve automation in various sectors. Image Classification, Captioning, Detection, Segmentation, etc., are very crucial in various demanding technologies like self-driving cars. These image analysis tools are very crucial in today's HITECH world. Inside Image analysis software contains algorithms that execute

Artificial Intelligence / Machine Learning

LIME For Regression Problems

LIME stands for Local Interpretable Model Agnostic Explanations. Lime is one of the techniques of visualization that helps to explain individual predictions with model interpretability. Now, let's look what LIME means.. Local surrogate models are interpretable models used to explain individual predictions of black box models in machine learning. LIME

Artificial Intelligence / Machine Learning

The Importance of PDP in Regression Problems

Model interpretability is becoming a progressively appreciated aspect. Though, when handling large models with complex relationships, interpretation is always a tedious task but is a very important part. PDP is a part of Interpretability which can be put on Supervised and Unsupervised Learning problems. Partial dependence plots show how each

Artificial Intelligence / Machine Learning

SHAP Instance Level Importance for Text Classification

SHAP stands for SHapley Additive exPlanations. It uses Shapley values as its core to explain individual predictions. Shapley values come from Game Theory where each feature present in the data is the player in the game and the final reward is the prediction that is made.

Artificial Intelligence / Machine Learning

Model Explainability using SHAP for Regression Problems

Nowadays we are able to solve various problems using AI. We have built a model that can predict the price of a house in an area, a model which can predict the team that is most likely to win the IPL using data, and predict who will qualify for NFL

Artificial Intelligence / Machine Learning

Coefficients Based On Feature Importance in Text Classification

In this post, we will showcase one more Feature importance based on the Logistic regression model. If I say one more there must be an article previous to this i.e on shap feature importance if you have not gone through it here is the link. let's take a simple

Artificial Intelligence / Machine Learning

Overview of ChatBot Testing

What is chatbot? A software or computer program that simulates human conversation. Chatbot testing is necessary to make sure that an effective and efficient chatbot is deployed. Testing experts analyze if all the necessary features are implemented correctly or not, and make sure they can appropriately answer each user's queries.

Artificial Intelligence / Machine Learning

SHAP Feature Importance in Structured Classification

Recently the European Union (EU) through the High-Level Expert Group on Artificial Intelligence (AI-HLEG) and the General Data Protection Regulation (GDPR) has recently posed an interesting challenge to the AI community, by demanding a more user-centered approach to explaining Automated Decision-Making systems (ADMs) using explainable AI(XAI) XAI is a

Artificial Intelligence / Machine Learning

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

Artificial Intelligence / Machine Learning

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.

Artificial Intelligence / Machine Learning

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.

Artificial Intelligence / Machine Learning

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.

Artificial Intelligence / Machine Learning

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

Artificial Intelligence / Machine Learning

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

Artificial Intelligence / Machine Learning

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 comprehensive guide to what’

Artificial Intelligence / Machine Learning

Model Agnostic vs Model Specific Explainability

In recent past there is a trend of supplementing complex machine learning and deep learning algorithms with augmented explanations for the decisions taken by the complex ML models. This notion termed as XAI Explainable AI is a recent trend which has emerged to counter the criticism of complex AI models

Artificial Intelligence / Machine Learning

Explain vs Interpret: What to choose?

In recent past one of the hot areas in AI has been the domain of Explainable AI also known as XAI. This initiative started by Darpa in US is aimed at making AI and decisions taken by AI systems more acceptable to humans. A key thought process underlying this is