Akshay 🚀 Profile picture
Simplifying LLMs, AI Agents, RAGs and Machine Learning for you! • Co-founder @dailydoseofds_• BITS Pilani • 3 Patents • ex-AI Engineer @ LightningAI
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Aug 1 14 tweets 5 min read
Let's build a (Text2SQL + RAG), hybrid agentic workflow: Before we dive in, here's a quick demo of what we're building!

Tech stack:

- @Llama_Index for orchestration
- @Milvusio to self-host a vectorDB
- @CleanlabAI to validate the response
- @OpenRouterAI to access the latest Qwen3

Let's go! 🚀
Jul 31 17 tweets 6 min read
"Attention is all you need" implemented from scratch using PyTorch: This is the paper that revolutionized AI!

Today, we'll implement:

- The complete Transformer architecture
- Multi-Head Attention mechanism
- Encoder-Decoder structure
- Positional Encoding

Everything in clean, educational Python code!

Let's go! 🚀 Image
Jul 27 11 tweets 4 min read
I have been fine-tuning LLMs for more that 2 years now!

Here are the top 5 LLM fine-tuning techniques, explained with visuals: Traditional fine‑tuning is impractical for LLMs (billions of params; 100s GB).

Since this kind of computing isn't accessible to everyone, parameter-efficient finetuning (PEFT) came into existence.

Today, we’ll cover the top 5 PEFT techniques, step by step. Image
Jul 25 10 tweets 3 min read
How LLMs train LLMs, clearly explained (with visuals): LLMs learn not only from raw text but also from other models.

Google’s Gemma 2 and 3, for example, were distilled from the larger Gemini model.

Today we cover, the three most common knowledge‑distillation methods.

Let's dive in! 🚀
Jul 24 13 tweets 4 min read
Let's build a "Chat with your Code" RAG app using Qwen3-Coder: Before we begin, take a look at what we're about to create!

Tech stack:

- @Llama_Index for orchestration
- @Milvusio to self-host a vectorDB
- @CleanlabAI codex to validate the response
- @OpenRouterAI to access @Alibaba_Qwen 3 Coder.

Let's go! 🚀
Jul 23 15 tweets 5 min read
I just built the ultimate MCP server for Multimodal AI.

It lets you do RAG over audio, video, images and text!

100% open-source, here's the full breakdown...👇 Before we dive in, here's a quick demo of what we're building!

Tech stack:

- @pixeltablehq to build the multi-modal AI infrastructure
- @crewAIInc to orchestrate the agentic workflow

Quickly check the thread, then return here for a detailed overview. 🚀
Jul 21 10 tweets 4 min read
Transformer vs. Mixture of Experts in LLMs, clearly explained (with visuals): Mixture of Experts (MoE) is a popular architecture that uses different "experts" to improve Transformer models.

The visual below explains how they differ from Transformers.

Let's dive in to learn more about MoE!
Jul 20 13 tweets 4 min read
MCP security is completely broken!

Let's understand tool poisoning attacks and how to defend against them: MCP allows AI agents to connect with external tools and data sources through a plugin-like architecture.

It's rapidly taking over the AI agent landscape with millions of requests processed daily.

But there's a serious problem... 👇
Jul 17 13 tweets 7 min read
10 GitHub repos that will set you up for a career in AI engineering (100% free): 1️⃣ ML for Beginners by Microsoft

A 12-week project-based curriculum that teaches classical ML using real-world datasets using Scikit-learn.

Includes quizzes, R/Python lessons, and hands-on projects. Some of the lessons are available as short-form videos.

Check this👇 Image
Jul 16 14 tweets 5 min read
Let's build a multi-agent content creation system (100% local): Before we dive in, here's a quick demo of what we're building!

Tech stack:

- @motiadev as the unified backend framework
- @firecrawl_dev to scrape web content
- @ollama to locally serve Deepseek-R1 LLM

The only AI framework you'll ever need to learn! 🚀
Jul 14 8 tweets 3 min read
ML researchers just built a new ensemble technique.

It even outperforms XGBoost, CatBoost, and LightGBM.

Here's a complete breakdown (explained visually): For years, gradient boosting has been the go-to for tabular learning.

TabM is a parameter-efficient ensemble that provides:
- The speed of an MLP.
- The accuracy of GBDT.

The visual below explains how it works.

Let's dive in!
Jul 12 5 tweets 2 min read
A Crash Course on Building AI Agents!

Here's what it covers:

- What is an AI agent
- Connecting agents to tools
- Overview of MCP
- Replacing tools with MCP servers
- Setting up observability and tracing

All with 100% open-source tools! This course builds agents based on the following definition:

An AI agent uses an LLM as its brain, has memory to retain context, and can take real-world actions through tools, like browsing web, running code, etc.

In short, it thinks, remembers, and acts.
Jul 11 12 tweets 4 min read
MCP is on fire.

AI agents can now talk to real world tools, apps and actually get stuff done.

This changes everything.

Here are 10 amazing examples: 1️⃣ WhatsApp MCP

Exchange images, videos, and voice notes on WhatsApp!

Pair it with the ElevenLabs MCP server for AI-powered transcription & audio messages with 3,000+ voices.

Check this out👇
Jul 10 15 tweets 5 min read
90% of Python programmers don't know these 11 ways to declare type hints: Type hints are incredibly valuable for improving code quality and maintainability.

Today, I'll walk you through 11 must-know principles to declare type hints in just two minutes.

Let's begin! 🚀 Image
Jul 7 9 tweets 3 min read
Temperature in LLMs, clearly explained (with code): Let's prompt OpenAI GPT-3.5 with a low temperature value twice.

It produces identical responses from the LLM.

Check the response below👇 Image
Jul 3 10 tweets 4 min read
7 MCP projects for AI Engineers (with video tutorials): 1️⃣ MCP meets Ollama

An MCP client is a component in an AI app (like Cursor) that establishes connections to external tools.

Learn how to build it 100% locally.

Full walkthrough:
Jun 28 9 tweets 5 min read
I have tested 100+ MCP servers in the last 3 months!

Here are 6 must-use MCP servers for all developers (open-source): 1️⃣ Graphiti MCP server

Agents forget everything after each task.

Graphiti MCP server lets Agents build and query temporally-aware knowledge graphs, which act as an Agent's memory!

Check this👇
Jun 25 12 tweets 4 min read
Let's generate our own LLM fine-tuning dataset (100% local): Before we begin, here's what we're doing today!

We'll cover:
- What is instruction fine-tuning?
- Why is it important for LLMs?

Finally, we'll create our own instruction fine-tuning dataset.

Let's dive in!
Jun 22 11 tweets 4 min read
Let's build a real-time Voice RAG Agent, step-by-step: Before we begin, here's a quick demo of what we're building

Tech stack:

- @Cartesia_AI for SOTA text-to-speech
- @AssemblyAI for speech-to-text
- @LlamaIndex to power RAG
- @livekit for orchestration

Let's go! 🚀
Jun 21 11 tweets 4 min read
Let's build an MCP-powered audio analysis toolkit: Before we dive in, here's a demo of what we're building!

Tech stack:
- @AssemblyAI for transcription and audio analysis.
- Claude Desktop as the MCP host.
- @streamlit for the UI

Let's build it!
Jun 19 4 tweets 2 min read
AI agents can finally talk to your frontend!

The AG-UI Protocol bridges the critical gap between AI agents and frontend apps, making human-agent collaboration seamless.

MCP: Agents to tools
A2A: Agents to agents
AG-UI: Agents to users

100% open-source. Here's the official GitHub repo for @CopilotKit's AG-UI:

(don't forget to star 🌟)github.com/ag-ui-protocol…