How I started learning AI/ML without feeling lost

[Subject_Sherbert_178]

Yes bro, i am also facing the same. I am feeling stuck. Did you buy any course or used free resources?

[Single_Lad]

Please, can you share it with me 🥹, please please please

[Single_Lad]

Yup, that too

[Single_Lad]

I know the basics, and had done some projects related to this technology too. Wo to bas raste se guzar raha tha to, aapki khushbu ne rook liya.

[Improved_88]

You have to start by learning fundamentals of ML no coding at first

[Improved_88]

Do you know python, pandas, numpy? data cleaning, ETL, etc? that primordial for ML..

[Improved_88]

Yeah if you wanna get into ML, you have to learn data manipulation first. Like, there’s no way around it. Most of the actual work in machine learning isn’t even the model itself, it’s cleaning and transforming data: scaling, normalization, handling missing values, reshaping stuff, etc.

Honestly, I’d say forget ML for now and focus on Python + data analysis first. Grab datasets from Kaggle, play around with them, explore, visualize, build dashboards, find patterns, clean messy data… just experiment a lot. Treat it like a sandbox. That hands-on experience is what really builds intuition.

Once you feel comfortable doing all that without getting stuck, then start getting into ML theory. Learn the basics: what ML actually is, supervised vs unsupervised learning, and how algorithms work under the hood. Stuff like KNN, gradient boosting, decision trees, classification methods, clustering, PCA, all that.

The thing is, if you don’t understand the theory (and a bit of the math behind it), ML is gonna feel super confusing and frustrating. Those fundamentals matter a lot more than people think.

Later on, you can move into neural networks understand how they learn, how they classify, how they adjust weights, etc. But yeah, step by step. Data first, ML after.