ChatGPT: Unpacking the constructs ChatGPT is quite a popular LLM (Large Language Model) that is widely used these days across various lines of engagement from article editing (no need to write a fresh, just edit generated text), coding prototypes (e.g.
Sentiment Analysis (Climate Summit-COP26): Jumpstart with ML coding
Machine Learning coding is considered to be the easiest of all coding landscapes whether you choose Python, Java, or R . We are aggressively moving to the era of minimum coding with maximum efficiency where we have tons of endpoints,
SVD to PCA: Technique to improve XAI (Explainable AI) (Part 2)
AI explainability (XAI) continues to challenge business to explain underlying reasons of a ML model behavior. With the advancement of various algorithm such as DL (Deep Learning – ANN, RNN, CNN, GPT, LSTM etc.) predictability has been increasing while inferabilty/explainability
SVD to PCA: Technique to improve XAI (Explainable AI) (Part 1)
XAI demand continues to grow across all industries primarily in finance and medical science. Before we decline loan, increase EMI amount or suggest some medical treatment (as a proactive measure), we need to have all pertinent data, indicators and logic
Support Vector Machine: Part 3 (Machine Learning with Kernel implementation)
Up until last article, I discussed about SVM and its underlying mathematics using very simple linear separable dataset involving only two features (), thereby expressing the effect of classifier in simple XY coordinates. SVM is one of the most successful
Support Vector Machine : Part 2 (Build intuition before applying mathematics)
As discussed in previous part, we continue building intuition before jumping into its (SVM) underlying mathematics. Please read previous part before reading this post. Our goal is to find the optimal hyperplane (it could be line, plane or hyperplane depending
Support Vector Machine : Part 1(Build intuition before applying mathematics)
Machine learning (ML) is the heart of AI products (Alexa, Siri, Cortana, Driverless Car etc.), algorithms are the core component of ML and mathematics is brain behind these algorithms. While data scientists can build model without requiring to deep dive
Data Science vs AI: Get to the Fundamentals
Introduction: Deriving meaningful information out of heap of data is the minimal requirement for any establishment today for its survival & sustenance. There are many terminologies and buzz words related to this area that blurs the meaning leaving people confused,
Automation through Advance Analytics: Financial Services
Fintech industries have been catching up quite well in blending advance analytics with RPA (Robotic Process Automation) implementation in its business process in the journey of digital transformation. Human time is too expensive to be wasted in carrying out mundane and
Artificial Intelligence: Core to the Digital and Managed Learning
Artificial Intelligence and related terms such as Cognitive computing, Data Science, Robotics, Predictive Analysis, Machine Learning etc. have been drawing attention over the past few years of almost all institutions and not limiting to only business, technical or academics. AI