Essential ML library

 

. Sweetviz — Automated EDA That Makes Your Boss Think You Didn’t Sleep

Yes, pandas profiling exists.
But Sweetviz? It generates story-quality EDA reports that look like you paid a designer.

Here’s the shocker: it’s not widely used, and most devs have never heard of it.

import sweetviz as sv
import pandas as pd

df = pd.read_csv("data.csv")
report = sv.analyze(df)
report.show_html("eda_report.html")

Why it’s wizard-level:

• Auto-detects target feature relationships
• Produces visual comparisons between datasets
• Creates reports faster than you can say “data cleaning”

I’ve used this to analyze a dataset in 90 seconds and impress a senior scientist who thought I spent “hours.”
Nope. Just Sweetviz.

2. River — Machine Learning That Learns Continuously

If scikit-learn is the classic calculator, River is the solar-powered one that never stops learning.
You can feed it data one row at a time — perfect for real-time dashboards, IoT streams, or stock tick updates.

from river import linear_model, optim, metrics

model = linear_model.LogisticRegression(optimizer=optim.SGD(0.01))
metric = metrics.Accuracy()

for x, y in stream:  # stream yields…