AI vs Machine Learning vs Deep Learning vs LLM: The Difference in 5 Minutes
AI, machine learning, deep learning and LLMs are nested ideas, not rivals. A short, jargon-free explanation with everyday examples of each.
Read article →Machine Learning
Regression, trees and clustering in Python and Excel, from scratch.
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Machine Learning
Regression, trees and clustering in Python and Excel, from scratch.
📄 13 articles⬇️ 12 with practice files🕒 Updated 28 Sep 2026
🎓 Start here: Vibe Coding Course → 🎓 Start here: AI Agents & RAG Course → 🎓 Start here: AI for Office Work Course →Linear Regression in Excel with LINEST, SLOPE and FORECAST — No Add-ins
Linear Regression in Excel with LINEST, SLOPE and FORECAST — No Add-ins
Machine learning starts with a straight line. Fit a regression in Excel with SLOPE, INTERCEPT, RSQ, LINEST and FORECAST.LINEAR, and learn how to read…
Read article →Linear Regression From Scratch in Python: How a Model Actually Learns
Linear Regression From Scratch in Python: How a Model Actually Learns
Code linear regression with gradient descent in plain NumPy, watch the model learn slope and intercept, then check it against NumPy and scikit-learn. The…
Read article →Machine Learning Lesson 8: Project, Predict Late Invoice Payments
Machine Learning Lesson 8: Project, Predict Late Invoice Payments
Build a complete model that predicts which invoices will be paid late, test it, save it, and score new invoices into an Excel file…
Read article →Machine Learning Lesson 7: Pipelines, Cross-Validation and Avoiding Leakage
Machine Learning Lesson 7: Pipelines, Cross-Validation and Avoiding Leakage
Bundle cleaning and the model into one scikit-learn pipeline so nothing leaks from test data, and compare models fairly with 5-fold cross-validation.
Read article →Machine Learning Lesson 6: Clustering Customers with K-Means
Machine Learning Lesson 6: Clustering Customers with K-Means
Group shoppers into segments without any labels using K-Means. Scale features first, choose the number of groups with the elbow method, and describe each…
Read article →Machine Learning Lesson 5: Decision Trees and Random Forests
Machine Learning Lesson 5: Decision Trees and Random Forests
Decision trees learn readable if/then rules; unlimited trees overfit. Random forests combine hundreds of trees and show which features matter most.
Read article →Machine Learning Lesson 4: Classification (Which Customers Will Leave?)
Machine Learning Lesson 4: Classification (Which Customers Will Leave?)
Predict yes/no outcomes with logistic regression. Read accuracy, precision, recall and the confusion matrix, and choose your own probability cut-off.
Read article →Machine Learning Lesson 3: Train/Test Split and Honest Evaluation
Machine Learning Lesson 3: Train/Test Split and Honest Evaluation
Keep part of the data hidden from the model to test it fairly. Measure regression accuracy with MAE and R2 and always compare with…
Read article →Machine Learning Lesson 2: Preparing Data (Missing Values and Text Columns)
Machine Learning Lesson 2: Preparing Data (Missing Values and Text Columns)
Models only accept complete, numeric tables. Find and fill missing values with the median and turn text columns like city into 0/1 columns with…
Read article →Machine Learning Lesson 1: What ML Is and Your First Model
Machine Learning Lesson 1: What ML Is and Your First Model
What machine learning actually is, the words you need (features, target, training), installing scikit-learn, and a first model that predicts flat prices from area.
Read article →Group Customers Automatically with K-Means in Python (From an Excel File)
Group Customers Automatically with K-Means in Python (From an Excel File)
Use k-means clustering to split customers into segments by orders, spend and recency — reading from and writing back to Excel with pandas and…
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