How to Build an End-to-End Data Science Workflow with Machine Learning, Interpretability, and Gemini AI Assistance?

How to Build an End-to-End Data Science Workflow with Machine Learning, Interpretability, and Gemini AI Assistance?

In this tutorial, we walk through an advanced end-to-end data science workflow where we combine traditional machine learning with the power of Gemini. We begin by preparing and modeling the diabetes dataset, then we dive into evaluation, feature importance, and partial dependence. Along the way, we bring in Gemini as our AI data scientist to…

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How to build AI scaling laws for efficient LLM training and budget maximization

How to build AI scaling laws for efficient LLM training and budget maximization

When researchers are building large language models (LLMs), they aim to maximize performance under a particular computational and financial budget. Since training a model can amount to millions of dollars, developers need to be judicious with cost-impacting decisions about, for instance, the model architecture, optimizers, and training datasets before committing to a model. To anticipate…

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How to Build a Multilingual OCR AI Agent in Python with EasyOCR and OpenCV

How to Build a Multilingual OCR AI Agent in Python with EasyOCR and OpenCV

class AdvancedOCRAgent: “”” Advanced OCR AI Agent with preprocessing, multi-language support, and intelligent text extraction capabilities. “”” def __init__(self, languages: List[str] = [‘en’], gpu: bool = True): “””Initialize OCR agent with specified languages.””” print(“🤖 Initializing Advanced OCR Agent…”) self.languages = languages self.reader = easyocr.Reader(languages, gpu=gpu) self.confidence_threshold = 0.5 print(f”âś… OCR Agent ready! Languages: {languages}”) def…

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How to Build a Conversational Research AI Agent with LangGraph: Step Replay and Time-Travel Checkpoints

How to Build a Conversational Research AI Agent with LangGraph: Step Replay and Time-Travel Checkpoints

In this tutorial, we aim to understand how LangGraph enables us to manage conversation flows in a structured manner, while also providing the power to “time travel” through checkpoints. By building a chatbot that integrates a free Gemini model and a Wikipedia tool, we can add multiple steps to a dialogue, record each checkpoint, replay…

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Build vs Buy for Enterprise AI (2025): A U.S. Market Decision Framework for VPs of AI Product

Build vs Buy for Enterprise AI (2025): A U.S. Market Decision Framework for VPs of AI Product

Enterprise AI in the U.S. has left the experimentation phase. CFOs expect clear ROI, boards expect evidence of risk oversight, and regulators expect controls consistent with existing risk management obligations. Against this backdrop, every VP of AI faces the enduring question: Should we build this capability in-house, buy it from a vendor, or blend the…

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How We Build AI Apps That Learn From Users in Real Time Without Retaining Their Data

How We Build AI Apps That Learn From Users in Real Time Without Retaining Their Data

“Hey , Ever get the feeling your apps know a little too much about you?”  I had a casual coffee chat the other day, and the conversation drifted to apps and privacy. One friend raised an eyebrow and said, “It’s weird — sometimes these apps remember things I didn’t even realize I told them.” That…

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A Code Implementation to Build a Multi-Agent Research System with OpenAI Agents, Function Tools, Handoffs, and Session Memory

A Code Implementation to Build a Multi-Agent Research System with OpenAI Agents, Function Tools, Handoffs, and Session Memory

In this tutorial, we begin by showcasing the power of OpenAI Agents as the driving force behind our multi-agent research system. We set up our Colab environment with the OpenAI API key, installed the OpenAI Agents SDK, and then defined custom function tools, web_search, analyze_data, and save_research, to harness the agents’ capabilities. We instantiate three…

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“Rather Than Investing  Billion Into A Mega Fab In One City, We Could Build Smaller, Decentralised Fabs Across The Country” – Raja Manickam, iVP Semiconductor

“Rather Than Investing $10 Billion Into A Mega Fab In One City, We Could Build Smaller, Decentralised Fabs Across The Country” – Raja Manickam, iVP Semiconductor

– Advertisement – Amid a global reset in semiconductor strategy, India’s clean-slate advantage lies in frugal innovation, chiplet architecture, and agile microfabs. With no legacy constraints, we havethe freedom to shape the future rather than imitate the past. Raja Manickam, Founder and CEO iVP Semiconductor “There is an Indian in every chip,” I often say,…

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A Coding Guide to Build an Intelligent Conversational AI Agent with Agent Memory Using Cognee and Free Hugging Face Models

A Coding Guide to Build an Intelligent Conversational AI Agent with Agent Memory Using Cognee and Free Hugging Face Models

In this tutorial, we delve into building an advanced AI agent with agent memory using Cognee and Hugging Face models, utilizing entirely free, open-source tools that work seamlessly in Google Colab and other notebook. We configure Cognee for memory storage and retrieval, integrate a lightweight conversational model for generating responses, and bring it all together…

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