GoDataAnalytics @GoDataAnalytic

#DataScientist #Machine_Learning #AI #Robotics #BigData #NLP #Data_Mining #Dtata_Analytics #blockchain #Artificial_Intelligence #Neural_Networks #Deep_Learning Stanford, CA Joined March 2018

Tweets

3K
Followers

464
Following

4K
Likes

1K

elvis @omarsar0

2 days ago

Another impressive paper by Google DeepMind. It takes a closer look at the limits of embedding-based retrieval. If you work with vector embeddings, bookmark this one. Let's break down the technical details:

29 222 2K 193K 3K

Download Image

ℏεsam @Hesamation

22 hours ago

NVIDIA says SLMs are the future of agents and it makes sense: agents mostly do a small set of repetitive tasks that small language models are already good at. using heavy LLMs for these tasks is like buying a supercomputer for high-school math. you can have 10-30x cost…

21 155 1K 77K 928

Download Image

Julian Goldie SEO @JulianGoldieSEO

3 days ago

I compiled 200+ n8n automation templates you can copy & paste into your business or sell to other companies. Just straight plug-and-play systems for: – Lead gen -Content creation – Email outreach – CRM updates – AI workflows – Slack/Discord bots … and more. How to get these…

175 133 271 25K 163

Download Image

Julian Goldie SEO @JulianGoldieSEO

a day ago

This guy literally explains how to MASTER N8N in 5 hours, for FREE. This is crazy: P.S. Want the full guide? DM me.

3 14 84 4K 107

Download Video

elvis @omarsar0

a week ago

A Survey of Frontiers in LLM Reasoning This is a really good overview of the key regimes and architectures advancing reasoning in LLMs.

19 135 627 78K 739

Download Image

Rohan Paul @rohanpaul_ai

a week ago

This Github has a very wide collection of High-quality datasets, tools, and concepts for LLM fine-tuning. All the datasets listed here should be under permissive licensing (Apache 2.0, MIT, cc-by-4.0, etc.). Categorized into segments like Math & Logic, Code, Conversation &…

18 206 1K 66K 1K

Download Image

elvis @omarsar0

2 weeks ago

RAG is not dead! However, we are in an interesting phase of exploring unique ways to index and retrieve information. This vectorless RAG framework uses a tree structure index in place of vectors. Reasoning models will enable methods that mimic human-like search. Early days!

30 161 1K 92K 1K

Download Image

Avi Chawla @_avichawla

2 weeks ago

5 levels of evolution of AI Agents. Over the last few years, we’ve gone from simple LLMs → to fully-fledged Agentic systems with reasoning, memory, and tool use. Here’s a step-by-step breakdown. 1) Small context window LLMs - Input: Text → LLM → Output: Text - Early…

18 74 369 36K 440

Download Image

Sebastian Raschka @rasbt

2 weeks ago

I’ve been working on something new: 📚 Build a Reasoning Model (From Scratch). The first chapters just went live! (The book will cover topics from inference-time scaling to reinforcement learning)

109 364 3K 152K 2K

Download Image

🔥 Matt Dancho (Business Science) 🔥 @mdancho84

3 weeks ago

This 277-page PDF unlocks the secrets of Large Language Models. Here's what's inside: 🧵

13 223 1K 98K 2K

Download Image

Sumanth @Sumanth_077

3 weeks ago

Microsoft launched the best course on AI Agents! AI Agents for Beginners This Free 11 lesson course is available on Github and will teach you everything you need to get started with building AI agents.

11 112 530 38K 788

Download Image

LangChain @LangChainAI

2 weeks ago

📚🔍 Academic Deep Search Assistant A powerful research assistant that automatically discovers and analyzes academic papers, generating comprehensive reports. Built with LangGraph to transform literature review workflows. Check out this game-changing research tool 📖…

10 76 407 29K 383

Download Image

Akshay 🚀 @akshay_pachaar

3 weeks ago

First Principles Approach to MLOps! MadeWithML is the best place to learn how to combine AI/ML with software engineering to build production-grade solutions. These fundamentals are directly applicable to LLMOps as well. 100% free and open-source.

5 147 709 61K 991

Download Image

elvis @omarsar0

3 weeks ago

Anthropic continues to crush it with these guides. This is a good example of what context engineering involves.

33 174 2K 388K 5K

Download Image

ℏεsam @Hesamation

3 weeks ago

Tonight’s reading material. A team at DeepMind wrote this piece on how you must think about GPUs. Essential for AI engineers and researchers.

16 349 3K 156K 3K

Download Image

Rohit Kumar Tiwari @_rohit_tiwari_

3 weeks ago

Want to ace your next LLM interview? Find Top 50 LLM Interview Questions Covers the topics you can’t skip 1. Core LLM Concepts ↳ Tokenization and embeddings ↳ Attention mechanism and multi-head attention ↳ Context window and positional encodings ↳ Autoregressive vs. masked…

99 81 409 45K 825

Download Image

Rohan Paul @rohanpaul_ai

3 weeks ago

BRILLIANT Paper. 💡 A small Qwen2.5 model is fine-tuned to think over retrieved documents, so a single lean setup can answer domain questions on resource-constrained local hardware. Using summarised NHS pages, retrieval hits the right condition among top‑5 in 76% of queries,…

10 103 567 42K 772

Download Image

Avi Chawla @_avichawla

3 weeks ago

3 prompting techniques for reasoning in LLMs:

9 75 484 45K 457

Download Image

Sumanth @Sumanth_077

3 weeks ago

Web scraping will never be the same! Firecrawl just released the new v2 endpoint with 10x faster scraping and semantic crawling. Firecrawl lets you input a URL, crawl it, and convert it into clean LLM-ready data.

20 301 2K 148K 3K

Download Image

Aurimas Griciūnas @Aurimas_Gr

3 weeks ago

Adding 𝗠𝗖𝗣 to 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 Systems. If you are building RAG systems and packing many data sources for retrieval, most likely there is some agency present at least at the data source selection for retrieval stage. This is how MCP enriches the evolution of your…