Master Machine Learning
The Unified Way!

Build Real Projects.
Get Hired.

Step-by-step courses, intermediate and advanced projects.


# An ML pipeline in Python (scikit-learn)
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline import make_pipeline
from sklearn.metrics import accuracy_score

# 1) Load data
X, y = load_breast_cancer(return_X_y=True)

# 2) Train/test split
X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=0.2, random_state=42, stratify=y
)

# 3) Build pipeline: scale -> logistic regression
clf = make_pipeline(StandardScaler(), LogisticRegression(max_iter=1000))

# 4) Train
clf.fit(X_train, y_train)

# 5) Evaluate
y_pred = clf.predict(X_test)
acc = accuracy_score(y_test, y_pred)
print(f"Accuracy: {acc:.3f}")

Hello, I'm Ardavan

A Physicist & Data Scientist. I have over 14 years of experience in data roles — including serving as a Data Science Fellow at the National Library of Medicine and as an author with the CMS experiment, where I analyzed terabyte-scale data.

I'm here to help you understand the core concepts of machine learning, think like a professional scientist, and build the skills, experience, and online presence you need to advance your data science career.