M&R SERVICES

Even with almost 4+ years in Data, these 3 mistakes slowed down my AI Engineer transition… (& here’s how I fixed them before it got too late!) Mistake #1 Thinking that ML knowledge was enough. → Because I could build models & tune them well. But AI roles aren’t just about training models, they’re about building systems around them. ✅ So I started learning the full lifecycle, pipelines, deployment, monitoring. Mistake #2 Underestimating the engineering skills. → I treated Python like scripting, not engineering. Didn’t focus enough on APIs, clean code, or scalability. ✅ So I worked on writing production-grade code & understanding backend fundamentals. Mistake #3 Stayed in learning mode for too long. → I kept doing courses and notebook projects. But nothing showed I could build real-world AI systems. ✅ So I started building end-to-end projects and sharing them publicly. I’ve learned that real growth as an AI engineer doesn’t come from doing everything alone, it comes from balance, collaboration & clarity. And if you’re a working professional aiming to grow faster or switch to top PBCs for Gen AI/ML roles, structured guidance from industry experts at Bosscoder Academy can help. 🔗 Explore their Gen AI/ ML Engineer Course: bcalinks.com/qWKOIW3 They’ve helped 2200+ professionals transition successfully through: 💡 Structured curriculum covering Python, Maths & Stats for ML, Deep Learning, Transformers & GenAI (LLMs, Prompting, RAG Systems, Agentic AI). 💡 Industry projects with real-world datasets focused on building end-to-end AI systems. 💡 1:1 mentorship from AI/ML engineers & data scientists at top product companies. 💡 100% placement support to help you land your dream AI/ML role. #genai #machinelearning #jobswitch #tech #collab #tech

Mastering AI Agents — A Complete Guide to Building Intelligent Agentic AI Systems This book covers the complete lifecycle of AI agents, from understanding agent architectures to evaluating, scaling and deploying production-ready agentic workflows.

Thrilled to share that I’m joining Tamara as a Senior Data Scientist! Over the past few years, I’ve had the opportunity to work across the US and India lending markets — building solutions around credit risk, underwriting, and lending strategy. Now excited to begin chapter three — the MENA region 🌍 Looking forward to learning, building, and creating impact with the amazing team at Tamara. #DataScience #Fintech #MerchantLending #CreditRisk #MENA #Tamara

Some memorable moments with National Head Fawad sir, Karan sir and RH Abhideep sir…

One thing becoming increasingly clear with AI is that value is shifting from model capability to adoption. Most AI tools already perform well in specific use cases. The difference in outcomes now comes from whether they are embedded into how organizations actually operate. That puts the focus on how AI gets deployed into workflows, how it is operationalized across teams, and whether usage becomes consistent enough to drive measurable impact. This is where much of the business value will be created over the next few years. Curious how others are seeing this play out.

OpenDataLoader PDF — A Powerful Open-Source PDF Parser for LLM & RAG Pipelines OpenDataLoader PDF converts PDFs into structured Markdown, JSON (with bounding boxes) and HTML, making it ideal for RAG pipelines, LLM applications and document intelligence systems — all while running locally (no GPU required). Key Features: • High Accuracy Parsing — #1 benchmark score (0.907 overall) across real-world PDFs • Structured Outputs — Markdown for LLMs, JSON with bounding boxes for source citation • Hybrid AI Mode — Combines fast local parsing with AI for complex layouts • Advanced Table Extraction — Handles borderless and nested tables with high accuracy • OCR Support — Works with scanned PDFs (80+ languages supported) • Formula & Chart Extraction — Outputs LaTeX + AI-generated descriptions • RAG-Ready — Clean chunking + precise source mapping for better retrieval • AI Safety — Built-in prompt injection filtering • LangChain Integration — Easy integration into modern LLM stacks • Runs Locally — No data leaves your environment Github Link : https://lnkd.in/gCsSvQYW Follow the AI Bulletin channel on WhatsApp & Telegram for the latest AI insights and updates: Whatsapp: https://lnkd.in/gZ4cAPxn Telegram: https://t.me/aibulletin56 Explore latest AI updates here: https://lnkd.in/gTw_CxWH

Amazing experience building, learning, and winning together. Proud to be part of a team that secured runner-up at the hackathon.

An important update: