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Day 5 of my 30-day Agentic AI series. 🔍 3 metrics every research agent needs before you trust it. Answer correctness catches wrong answers. Source grounding catches hallucinations. Task completion
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Day 4 of 30: Plan-and-Execute Agents 🤖 Today we’re building an autonomous research agent that doesn’t answer in one shot. It first plans the research path, breaks the question into smaller steps, t
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Day 3 of my Agentic AI series — Memory in AI Agents 🧠 The biggest shift from “LLMs” → “agents” isn’t just tool calling. It’s continuity. In the Stanford + Google generative agents paper, agents di
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April 🌸✨
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Hi Folks! It’s Day 2 of Agentic AI! Today let’s talk about Tool calling. As Andrew Ng says: Tool use is one of the most reliable agent design patterns you can ship today. Because at the end of the d
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Hello Folks! It’s Day 1 of my new series Agentic AI ✨ Let’s dive into the Anatomy of Agent by understanding the paper that quietly started the agent revolution. ReAct: Synergizing Reasoning and Acti
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Most developers are using AI to write code. Very few are using it the right way. The difference isn’t the tool- it’s how you think, structure, and validate your work. Here are 5 practices that turn
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Hello Folks! It’s Day 23 of Building an LLM from Scratch ✨ From past few weeks I have been diving into Fine tuning. Today I completed my code! It was all about instruction finetuning. Until now, my m
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Hello Folks! Hope you had an amazing long weekend and soaked up some 🌞. I definitely did! Day 22 of building my LLM from scratch. Today I dived deeper into Fine Tuning! The goal is straightforward:
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Hey Folks! Happy Seahawks day 💚💙 Still smiling because the Seahawks won the Super Bowl! 🏈 What a day to be in Seattle! And on a personal note, another exciting win for my Build an LLM from Scratch
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Hi Folks! Happy Saturday 🫶🏻 It’s finally time to implement the code for pretraining the LLM ✨ It’s day 20 for the challenge today! Here’s what I am doing in a nutshell - ✨ I implement the full trai
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Hello Folks! The work week has begun in full force. I managed to spend some cycles on my challenge nevertheless. It’s day 19 of building a LLM from scratch ✨Today I coded evaluation of generative la
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About @awomanindatascience

Chinar Arora is a Instagram micro influencer in the Digital creator category. With 11.4K followers and 12 posts, awomanindatascience's account shows a follower-to-following ratio of 62.5:1. This profile demonstrates strong community engagement within its niche. View all content anonymously on Pictame - no login required.

awomanindatascience's engagement rate sits at 1.22%. For accounts with 10K-100K followers, the average is around 2.5%, so there's some room to grow — though every community is unique.

Out of the last 12 posts, 92% are videos and 8% are photos. Content shows up about every 10 days. Captions lean detailed, averaging 725 characters.

1.22% engagement rate — room to grow compared to average for 10K-100K follower accounts.
Posts about every 10 days.
62.5:1 follower-to-following ratio.

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awomanindatascience
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@awomanindatascience

Chinar Arora

PublicDigital creator
Posts
12
Followers
11.4K
Top Hashtags
#generativeai#deeplearning#largelanguagemodels#womenintech#womenwhocode#agenticai#AgenticAI#AIEngineering

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Engagement
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📈applied scientist @microsoft 👩‍💻documenting my learning 🏋️‍♀️building better habits after my 9-5 📍seattle

#motivation
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