BeginnerPythonPandas
Introduction to Pandas: DataFrames, Indexing and GroupBy
A practical guide to Pandas — the most important library in any data scientist's toolkit.
Tutorials
Learn by doing
Step-by-step tutorials covering the full ML pipeline — from data cleaning to model deployment. Every tutorial includes working Python code and real datasets.
AllBeginnerIntermediateAdvanced
IntermediateNumPyML Fundamentals
Linear Regression from Scratch with NumPy
Build linear regression step by step using only NumPy. Understand gradient descent and the loss surface.
BeginnerEDAStatistics
Exploratory Data Analysis: A Systematic Approach
A reproducible EDA workflow covering distributions, correlations, outliers and business context.
IntermediateMLTree Models
Decision Trees and Random Forests Explained
From information gain to ensemble methods — a thorough explanation with implementation from scratch.
AdvancedDeep LearningNumPy
Neural Networks: Forward and Backward Propagation
Derive and implement backpropagation from first principles. Build a neural network in pure NumPy.
IntermediateTime SeriesStatistics
Time Series Forecasting with ARIMA and Prophet
A complete guide to forecasting time series data for business and economic applications.