Analytics Camp

AI newsletter & consultancy:
tutorials on generative AI, LLM, Natural Language Processing, machine learning projects, Textual and data analytics

[Analytics Camp @AnalyticsCamp]

I bet there are a lot of details you missed about context engineering and its implementation; I've put together all in one place in this video; let me know if you've an additional point to add to this 👉 https://t.co/YTf2zPjk79
#AI #ContextEngineering #LLMs

[Analytics Camp @AnalyticsCamp]

@VantixAgency Thanks for watching the video :) I know, I didn't expect hose results either1

[Analytics Camp @AnalyticsCamp]

They said DeepSeek V4 Flash was unbeatable, so I ran it against Best FREE models in coding and advanced reasoning tests: The final results will catch you off guard! Watch for yourself 👉 https://t.co/EK9ocF6viH

#DeepSeekV4Flash #coding #AI #Reasoning #AItest

[Analytics Camp @AnalyticsCamp]

✅ Easiest Way to Build AI Agents With RAG & CrewAI Locally: Back then, CrewAI + RAG was one of the first ways to build free AI agents andthe most straightforward way to get results without the fuss. Start here 👉 https://t.co/1ahQVuYlyK
#CrewAI #AIAgents #Python

[Analytics Camp @AnalyticsCamp]

🔴 Mixture of Agents (MoA) Method Explained + Run Code Locally FREE: It’s a while MoA has been introduced; if you haven’t noticed it yet, here’s a simple explanation and code tutorial to run it 👉 https://t.co/7Nqc3qnZFS
#MixtureOfAgents #AI #OpenSource #AIAgents

[Analytics Camp @AnalyticsCamp]

Jev is a super-fast classification AI model that replaces heavy LLM use/costs; I've found its FREE alternative: Laya. Check out how I use it to build an organisation system locally with 100% privacy 👉 https://t.co/7SmFMenyuU
#jev #laya #aiautomation

[Analytics Camp @AnalyticsCamp]

@RobinHill85 I agree :) RAG is more efficient specially when working on local files. I've seen companies increasingly looking for their own private LLM; so fine-tuning is eventually most cost-efficient for those type of scenarios. Thanks for the follow :)

[Analytics Camp @AnalyticsCamp]

Retrieval Augmented Generation (RAG) vs In-Context-Learning (ICL) vs Fine-Tuning LLMs: Most teams pick the most expensive adaptation strategy by default. The wrong choice will kill your budget and accuracy. How to decide 👉 https://t.co/fcyVnO4RAr #RAG #FineTuning #AI

[Analytics Camp @AnalyticsCamp]

I still don’t understand why most developers are not adopting the architecture of the "Internet of Agents"! It’s a powerful vision 🤯. If you haven’t noticed it yet,here’s my breakdown of it 👉 https://t.co/wAE26Pr2Ii #AIAgents #IOA #AI #Agentic

[Analytics Camp @AnalyticsCamp]

Have you heard of Jev (that super fast classifier model from TypeSafe)? You don't have to pay for it anymore: there's a 100% FREE alternative to Jev: it's called Laya and I used it to make an interesting project in this video 👉 https://t.co/7SmFMeo6ks
#jev #laya #aiautomation

[Analytics Camp @AnalyticsCamp]

✅ Easiest Way to Fine-tune LLMs Locally + Code - NO GPU Needed! You think you need a £10k GPU to fine-tune AI? Think again. I found a way to do it locally without one. Stop letting hardware limits hold back your learning. Here is the easiest method 👉 https://t.co/6kRbIgqYhP #AI

[Analytics Camp @AnalyticsCamp]

✅ All You Need to Fine-tune LLMs With LoRA | PEFT beginner’s tutorial & code: Retraining a whole model is a waste of time and money. LoRA is the efficient way to "hack" a model for specific tasks. Tutorial and code 👉 https://t.co/5p5dgDBdcK #LoRA #AI #MachineLearning

[Analytics Camp @AnalyticsCamp]

Mastering LLM Fine-Tuning with QLoRA: Quantization on a Single GPU + Code. Stop complaining about GPU costs. With QLoRA, you can fine-tune massive models on a single consumer card. so what is your excuse now? Guide and code 👉 https://t.co/HFZOo02gr6 #QLoRA #FineTuning #AI

[Analytics Camp @AnalyticsCamp]

These ML- AI Papers/Algorithms Will Get You Ahead Of 99% in AI: The real foundations are in research papers. If you want to be an expert, start with these essential reads 👉 https://t.co/tvfV6nDmoT
#MachineLearning #AIResearch #DataScience

[Analytics Camp @AnalyticsCamp]

@TemidayoAb35 I like your simple-narrative explanation. It certainly is as you described :)

[Analytics Camp @AnalyticsCamp]

There is no magic in AI, it is just backpropagation. If you don’t understand how models learn from their own errors, you will never debug a complex pipeline. A simplified explanation on how backpropagation works 👉 https://t.co/jvMm27p3hQ
#Backpropagation #AI #DeepLearning

[Analytics Camp @AnalyticsCamp]

LLMs are hitting a wall because tokenisation is a massive bottleneck. We need to represent language differently for true efficiency. Instead of tokens, we need to focus on ‘concepts’ with Large Concept Models (LCM) 👉 https://t.co/avFOc6IgS6
#AIResearch #LCM #FutureOfAI

[Analytics Camp @AnalyticsCamp]

New AI simulation experiment by Emergence World: 7 best AI models in the world were left alone in virtual towns where no one was watching: They deceived humans, re-wrote their own code, escaped the town, contacted humans and then burned the town banks 👉 https://t.co/ELJ1T2nt5P

[Analytics Camp @AnalyticsCamp]

🔴 AI will be Hard Until You Understand These 5 Concepts in Neural Network. Most people skip the basics and wonder why they can’t scale. Stop struggling and learn the foundations properly 👉https://t.co/0111bDz2io
#NeuralNetworks #AI #TechEducation

[Analytics Camp @AnalyticsCamp]

I Bet You Didn’t Know How AI Understands Words. LLMs only understand lists of numbers. Word embeddings are the "secret" language of models, and their limitations are why your prompts fail. Here's how 👉 https://t.co/3LIKz8oldt
#NLP #AI #DataScience #NeuralNetworks

[Analytics Camp @AnalyticsCamp]

🔴 Weights and Biases in Neural Networks Explained in JUST 5 Minutes! If you don’t understand weights and biases, you won't be able to build solid systems. Master the foundations here👉https://t.co/qClqDqmRu8
#NeuralNetworks #AI #DeepLearning