How do I start learning machine learning with a weak math background?
Dropped math after high school. Every ML course opens with linear algebra and I bounce off immediately. Is there a practical way in?
AI & ML Questions & Answers
21 questions · 1 followers
Ask and answer questions about artificial intelligence and machine learning — how models actually work, which tools to learn, and where AI is genuinely useful.
Discussions
What is a large language model and how is it different from a search engine?
People use ChatGPT the way they used Google. Are they doing the same thing differently, or are they fundamentally different tools?
Is data science still a good career in 2026 or is the field saturated?
Seeing conflicting takes — 'data science is dead, it's all AI engineers now' vs 'demand higher than ever'. What's the honest read for someone starting today?
What is the difference between machine learning and statistics?
A statistician told me machine learning is just applied statistics with better marketing. Is that fair?
How do I evaluate whether an AI feature is actually working?
We shipped an AI feature and everyone has opinions about whether it's good. How do you measure quality of something with no single correct answer?
What is a neural network and how does it learn?
I want an intuition for what's happening inside a neural network without the calculus. How does adjusting numbers turn into learning?
What is the difference between generative AI and traditional AI?
Generative AI seems to be treated as a new thing entirely. What changed compared to the AI that already existed in products?
What is the difference between AI, machine learning and deep learning?
These three terms are used interchangeably in every article. Are they the same thing or is there a real hierarchy?
What is fine-tuning and when should I fine-tune a model instead of prompting?
I'm building something with an LLM and people keep suggesting fine-tuning. When is it actually worth it versus just writing a better prompt?
What is the difference between narrow AI and general AI?
AGI comes up constantly in AI discussion. What separates what we have now from what people mean by general intelligence?
What are LLMs and how do they actually work, explained simply?
I use ChatGPT daily but couldn't explain what's happening under the hood to save my life. What's the honest simple version — not the 'it's magic' one and not the PhD one?
How do I start learning machine learning as a complete beginner?
I know some Python and want to get into ML but every roadmap starts with three semesters of maths and I lose motivation. Where do I actually begin?
What's the difference between AI, machine learning and deep learning?
These get used interchangeably everywhere and I want to actually understand the hierarchy before my interview. Simple explanation?
What is bias in AI and how does it get into a model?
AI bias comes up constantly but I don't understand the mechanism. Where does bias actually enter and can it be removed?
Python or R for machine learning — does the choice still matter?
My stats professor swears by R, every job posting says Python. Starting my first ML project — which do I invest in?
How do recommendation algorithms decide what to show me?
My feed knows me uncomfortably well. What's actually happening behind the scenes on YouTube, Instagram or Netflix?
What are AI agents and how are they different from chatbots?
Everyone's talking about agents now. Is it just a chatbot with extra steps or something genuinely different?
How do I get a job in AI without a PhD?
Every AI job listing seems to want a research background. Is there a realistic route in from ordinary software or data work?
What is the best way to learn Python for data science and AI?
I know Python basics. What specifically should I learn next to be useful for data and ML work rather than general programming?
How much math do I actually need for machine learning jobs?
Not research — applied ML jobs at normal companies. What level of math do interviewers and daily work genuinely require?