AI/ML Tutorials

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AI / ML

AI and ML for Data Engineers

From linear regression to transformers — every algorithm explained with analogies, code, and real-world use cases.

9 in-depth tutorials

01AI/ML Introduction

AI and ML introduction: classification, regression, algorithms, and real-world use cases.

02Linear & Logistic Regression

In-depth tutorial covering linear & logistic regression.

03Decision Trees & Random Forests

In-depth tutorial covering decision trees & random forests.

04XGBoost & Gradient Boosting

In-depth tutorial covering xgboost & gradient boosting.

05Model Evaluation Deep Dive

In-depth tutorial covering model evaluation deep dive.

06Feature Engineering

In-depth tutorial covering feature engineering.

07Fine-Tuning LLMs

In-depth tutorial covering fine-tuning llms.

08Clustering Algorithms

In-depth tutorial covering clustering algorithms.

09Hyperparameter Tuning

Hyperparameter tuning: GridSearchCV, RandomizedSearch, Optuna, and cross-validation.

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