Kicked off my AI engineer roadmap with Week 1! From Python setup to NLP, here’s my journey: 👇 #AI . #BuildInPublic.

Day 13 of my AI engineer journey: Built an ML pipeline with scikit-learn for Iris! .Resources :Scikit-learn Pipeline: youtube video : Machine Learning Pipeline Explained by StatQuest with Josh Starmer. #AI #MachineLearning.

What’s your go-to ML preprocessing step? Just tried StandardScaler on Iris and loved it! .Share yours below. 👇 . #AI #MachineLearning #LearnInPublic #buildinpublic.

Day 12 of my AI engineer journey: Mastered feature scaling with StandardScaler on Iris dataset! .Resources :. Scikit-learn StandardScaler: youtube video : . #AI #MachineLearning #LearnInPublic #buildinpublic

Youtube videos for easy explanation ,you can watch this .

Day 11 of my AI engineer journey: Optimized my Iris classifier with grid search in scikit-learn!. Resources :.Scikit-learn Hyperparameter Tuning: #AI #MachineLearning #buildinpublic #LearnInPublic.

Cross-validation = robust ML evaluation! Used scikit-learn’s `cross_val_score` for stable Iris metrics in <20 lines. Learn it: #AI #BuildInPublic #LearnInPublic.

YouTube Videos: .“Cross Validation in Scikit-learn” by Data School (12min, beginner-friendly): Cross-Validation Explained by StatQuest (10min, clear visuals):

Official Documentation:.Scikit-learn Cross-Validation: Cross_val_score: Iris Dataset:

Day 10 of my AI engineer journey: Mastered 5-fold cross-validation with scikit-learn on Iris dataset!. Resources that i used are :-. #AI #MachineLearning #buildinpublic #LearnInPublic.

Ever mixed up precision and recall? Just nailed ML evaluation metrics with scikit-learn! What’s your favorite metric for ML models? 👇 #AI #MachineLearning.

Precision, recall, F1-score: key for ML evaluation! Used scikit-learn to assess my Iris model in <30 lines. Learn more: #AI #BuildInPublic.

Day 9 of my AI engineer journey: Evaluated my Iris classifier with scikit-learn! Got 0.9667 accuracy, precision, recall, F1. #AI #MachineLearning.

Day 7: Organized my repo for MLOps. Check it out: Follow along! #AI.

Day 5–6: Built an NLP preprocessor (stopword removal) & word frequency analyzer. Code:

Day 3–4: Mastered pandas (DataFrames) & API calls. Code:

Day 1–2: Set up Python & learned NumPy basics (arrays, matrices). Code: #MachineLearning.

Learning journey: Trained a logistic regression classifier with scikit-learn on the Iris dataset! 🌸 Repo Link: #AI #MachineLearning #AgenticAI

Hello Everyone,.We are pleased to announce new #internship opportunities at Thaluwa! We are committed to empowering local artisans and preserving indigenous cultures. Send your cv at: hiring@thaluwa.com. Requirements .1) UI/UX designer with react experience.

If you agree, give this post a LIKE and SHARE it with your network! 🤝 Let's spark a conversation about the challenges of fundraising and how we can support each other. 💬 #Fundraising #StartupLife #ConnectionsMatter.