After winning 5 hackathons during college, I finally wrote down the workflow my team naturally converged to over the years. No generic tips, just a practical engineering playbook that has consistently worked for us. Hope it helps you win your next one. https://t.co/7bdLtlj8nR
Built an end-to-end Network Intrusion Detection System and deployed it on AWS.
Debugged real infrastructure failures during deployment. That is where the actual learning happens.
GitHub: https://t.co/YquLmDAi5U
#MLOps#MachineLearning#DataScience#OpenToWork
Built an end-to-end Network Intrusion Detection System and deployed it on AWS.
Debugged real infrastructure failures during deployment. That is where the actual learning happens.
GitHub: https://t.co/YquLmDAi5U
#MLOps#MachineLearning#DataScience#OpenToWork
@Njuchi_ hey when you are going to launch video on mlops on YouTube?? as I have seen something about your post like "mlops video on making" if I am not wrong .
Missed yesterday’s post (college rush @ NIT Hamirpur ), but back today!
Learning never stops — exploring the Iris dataset: visualization, hue, and evaluation metrics
today's notebook:https://t.co/QLfKxwjpmP
Continuing my ML journey! 📚
Practiced Linear Regression with L1 & L2 Regularization (Ridge & Lasso) — explored how regularization keeps models simple yet powerful.
Small tweaks in alpha → big impact on model performance!
Here is my notebook:https://t.co/GwUm1vgkvu
Starting small, learning big! 🌟
Worked on a basic Polynomial Regression model to predict students’ scores from their study hours.
Loving how even simple problems reveal the beauty of ML.
here is the notebook:https://t.co/KidG0fwXlu
🎓 Just completed Mathematics and Statistics for AI and Data Science!
Covered probability, hypothesis testing, A/B testing, and data visualization — all the core building blocks for AI & ML.
Now I am learning Machine Learning!