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Articles by Arun Nanda
India’s corporate climate moment
Indian business is standing at a decisive moment. Across the country, climate impacts are no longer abstract projections—they are operational realities. Record-breaking heatwaves are straining productivity and public health. Flooding and extreme rainfall are disrupting logistics, infrastructure and supply chains. Air pollution continues to impose real economic and social costs on our cities. For Indian companies, climate risk is no longer distant—it is business risk today.
Indian business has reached its climate moment - and the next five years will decide who wins
Indian business is standing at a decisive moment. Across the country, climate impacts are no longer abstract projections—they are operational realities. Record-breaking heatwaves are straining productivity and public health. Flooding and extreme rainfall are disrupting logistics, infrastructure and supply chains. Air pollution continues to impose real economic and social costs on our cities. For Indian companies, climate risk is no longer distant—it is business risk today.
The Role of Contract Law in Shaping the Pharmaceutical Sector: A Legal Study
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. The International Journal of Drug Regulatory affairs require a formal written transfer of copyright from the author(s) for each article published. We therefore ask you to complete and return this form, retaining a copy for your records. Your cooperation is essential and appreciated. Any delay will result in a delay in publication.
Action Value Function: A Guide With Python Examples
Tutorial Learn the fundamentals of reinforcement learning through the analogy of a cat learning to use a scratch post. Tutorial Learn about the most popular model-free reinforcement learning algorithm with a Python tutorial. Tutorial Learn SARSA, an on-policy reinforcement learning algorithm. Understand its update rule, hyperparameters, and differences from Q-learning with practical Python examples and its implementation.
Enhancing Large Language Models with Knowledge Graphs
How Knowledge Graphs and LLMs Work Together Now, let’s see how knowledge graphs can be used to enhance LLMs. Knowledge graphs for contextual understanding LLMs are capable of generating well-written text, but they cannot assess its factual accuracy. In most cases, the original training dataset did not have information (such as a specific user manual) relevant to a practical task (such as answering user queries about how to use a specific tool).
Azure Blob Storage: How to Upload, Secure, and Manage Your Data
Accessing and Securing Azure Blob Storage Security is paramount in enterprise storage systems. There are various ways to securely access Azure Blob Storage, such as SAS tokens, access keys, and enterprise accounts. Access control with SAS tokens In production environments, you restrict access to files and data stored in Blob Storage. You generally don’t want it to be publicly accessible. Shared Access Signatures (SAS) offer a secure method of managing access to your Blob Storage data.
Azure Storage Explorer: Connect, Upload, and Organize Files
If you’ve ever found managing cloud storage through the Azure portal a bit clunky or overwhelming, you’re not alone. That’s where Azure Storage Explorer comes in—a user-friendly desktop application that lets you interact with your Azure Storage resources without needing to navigate the full Azure interface.
Intelligent Transportation Systems and Reinforcement Learning
Image generated using Pixlr Arun Nanda · Follow 5 min read · -- Intelligent transportation systems (ITS) use AI to control and manage networks and vehicles with minimal human intervention. Many transportation problems can be modeled as an agent interacting with a dynamic environment to optimize long-term rewards. For example, a self-driving car aims to safely drive through traffic and reach the destination quickly.
Amazon Lex Tutorial: A Beginner’s Guide to AI Chatbots
An introduction to building chatbots with Amazon Lex. Learn how to set up and configure a bot, use it with backend services, and deploy it on different platforms. Arun Nanda Feb 24, 2025 · 15 min read Create Your Free Account Practice and track your progress. Continue with Google By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA. AWS Cloud Practitioner Learn to optimize AWS services for cost efficiency and performance.
Azure OpenAI: A Step-by-Step Getting Started Guide
Setting Up Azure OpenAI In this section, I show how to set up Azure OpenAI. I assume you have some experience with using Azure. Note that user interfaces change frequently. So, the layout and text of various sections and titles in the instructions and screenshots can change over time or from region to region. Step 1: Create an Azure account Go to the Azure OpenAI homepage and select Sign in at the top right. Log in with your Microsoft account.
Getting Started with TorchRL for Deep Reinforcement Learning
PyTorch Lightning: A Comprehensive Hands-On Tutorial This comprehensive, hands-on tutorial teaches you how to simplify deep learning model development with PyTorch Lightning. Perfect for beginners and experienced developers alike, it covers environment setup, model training, and practical examples. Bexruz (Bex) Tuychiev 14 min Deep Learning on Rails with PyTorch Lightning In this session, you'll learn how to create a simple deep learning model using PyTorch Lightning.
Quantizing Neural Network Models
Understanding post-training quantization, quantization-aware training, and the straight through estimator Large AI models are resource-intensive. This makes them expensive to use and very expensive to train. A current area of active research, therefore, is about reducing the size of these models while retaining their accuracy. Quantization has emerged as one of the most promising approaches to achieve this goal.
Proximal Policy Optimization with PyTorch and Gymnasium
Learn the first principles of Proximal Policy Optimization, including its implementation in PyTorch with Gymnasium! Arun Nanda Nov 18, 2024 · 15 min read Create Your Free Account Practice and track your progress. Continue with Google By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA. Become an ML Scientist Upskill in Python to become a machine learning scientist.
Reducing the Size of AI Models
Running large AI models on edge devices AI models, particularly Large Language Models (LLMs), need large amounts of GPU memory. For example, in the case of the LLaMA 3.1 model, released in July 2024, the are: The 8 billion parameter model needs 16 GB memory in 16-bit floating point weights The larger 405 billion parameter model needs 810 GB using 16-bit floats In a full-sized machine learning model, the weights are represented as 32-bit floating point numbers.
What Is Fraud Analytics? Techniques, Workflows, and Tools
blog Learn how data science is implemented in the banking sector by exploring one of the most common use cases: fraud detection. blog We explain what business analytics is, why it's important, the different aspects of business analytics, and the tools most commonly used. blog In this article, we discuss what predictive analytics is, explore some examples of how it is used, and look at how it works.
Understanding Superalignment: Aligning AI with Human Values
How to Scale AI in Your Organization: A Guide For Leaders Discover a comprehensive roadmap to scaling AI in your organization. Learn how to align AI with your business goals and create a robust data infrastructure to ensure your AI initiatives deliver lasting value and transformative growth. AI Ethics: An Introduction AI Ethics is the field that studies how to develop and use artificial intelligence in a way that is fair, accountable, transparent, and respects human values.
Quantizing the Weights of AI Models
Reducing high-precision floating-point weights to low-precision integer weights To make AI models more affordable and accessible, many developers and researchers are working towards making the models smaller but equally powerful. Earlier in this series, the article Reducing the Size of AI Models gives a basic introduction to quantization as a successful technique to reduce the size of AI models.
Generative vs Discriminative Models: Differences & Use Cases
Generative models Discriminative models Objective Capture the joint probability and marginal probability. Use Bayes' rule to compute the conditional probability. Capture only the conditional probability. There is no information on joint or marginal probabilities. Data generation Can generate new data points based on the training dataset. For example, a model trained on handwritten digits can generate new, fake digits. Cannot generate new data points.
Confidence vs Prediction Intervals: Understanding the Difference
This article teaches you the meaning, the differences, and the appropriate use cases of prediction intervals and confidence intervals in statistical and regression analyses. It also shows you how to implement these intervals in R. Become a ML Scientist Master Python skills to become a machine learning scientist Become an ML Scientist Upskill in Python to become a machine learning scientist.
Expert Guide: What India Needs To Do To Create More Jobs
India should be able to keep pace with the changing, diverse global trends with new skills and technology By Arun Nanda August 09, 2021 Photograph by Tribhuvan Tiwari Arun Nanda July 29, 2021 00:00 IST Expert Guide: What India Needs To Do To Create More Jobs outlookindia.com 2021-07-31T18:14:08+05:30 There is significant uncertainty regarding an anticipated third wave of Covid-19, and businesses are still reluctant to hire.
A comparative study of regulatory trends of pharmaceuticals in Brazil, Russia, India and China (BRIC) countries
BRIC basically include the emerging markets of Brazil, Russia, India and China. The growth of pharmaceutical market in these countries has been very eye-popping during the last two decades. The growth of pharmaceutical market depends upon the drug regulatory system and drug regulatory laws.
Compulsory licensing of drug products in developing countries
Compulsory licensing of drug products is a very hot issue in today’s pharmaceutical world. Compulsory licensing of a drug product allows the government to issue the license of manufacturing the drug to a third person. The third person has to give some 5–10% royalty to the patent holder (the quantum of royalty is decided by the government and not by the patentee).
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