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Posts tagged “Ml-Fundamentals”

5 posts

Regression and Decision Boundaries

· 17 min read

Part 5 of the ML Fundamentals series. Linear and polynomial regression, Ridge and Lasso regularisation, logistic regression, the Perceptron, and visualising …

data-engineering
ml-fundamentals machine-learning python scikit-learn regression

Classification — KNN, Naive Bayes, Decision Trees

· 15 min read

Part 4 of the ML Fundamentals series. Three foundational classification algorithms — how they work, when to use each, and hands-on implementation with …

data-engineering
ml-fundamentals machine-learning python scikit-learn classification

Python ML Toolkit

· 14 min read

Part 3 of the ML Fundamentals series. Setting up a Python ML environment, and practical workflow patterns with Pandas, NumPy, Matplotlib, Scikit-learn, and …

data-engineering
ml-fundamentals machine-learning python scikit-learn tensorflow pandas

Data Pre-processing and Evaluation

· 10 min read

Part 2 of the ML Fundamentals series. Cleaning messy data, selecting features, splitting datasets, and measuring whether your model is actually any good.

data-engineering
ml-fundamentals machine-learning python data-engineering infrastructure

What Is Machine Learning?

· 6 min read

Part 1 of the ML Fundamentals series. What machine learning actually is, the three main learning paradigms, and why it matters for infrastructure, automation, …

data-engineering
ml-fundamentals machine-learning python automation infrastructure