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Practical guides and research explainers for building with AI.
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Basics of AI/MLBeginner
Build a Neural Network Without PyTorch. What Changes When It Learns?
You run a training script. A number called “loss” gets smaller. A few seconds later, your model makes better predictions. But what happened inside it? Where did the learning get stored? And why does running the same calculation again produce a different answer?
Basics of AI/ML, How-toBeginner
How to Use XGBoost and LightGBM in Python: A Beginner's Guide to Gradient Boosting (Food Delivery ML Series, Part 7)
How to Use XGBoost and LightGBM in Python: A Beginner's Guide to Gradient Boosting (Food Delivery ML Series, Part 7)
Basics of AI/ML, How-toBeginner
How to Explain Machine Learning Predictions in Python: A Beginner's Guide to Feature Importance and SHAP (Delivery ML Series, Part 6)
How to Explain Machine Learning Predictions in Python: A Beginner's Guide to Feature Importance and SHAP (Delivery ML Series, Part 6)
Basics of AI/ML, How-toBeginner
How to Tune a Machine Learning Model in Python: A Beginner's Guide to Hyperparameters and GridSearchCV (Food Delivery ML Series, Part 5)
How to Tune a Machine Learning Model in Python: A Beginner's Guide to Hyperparameters and GridSearchCV (Food Delivery ML Series, Part 5)
Basics of AI/ML, How-toBeginner
How to Clean Messy Data for Machine Learning in Python: A Beginner's Guide (Food Delivery ML Series, Part 3)
How to Clean Messy Data for Machine Learning in Python: A Beginner's Guide (Food Delivery ML Series, Part 3)
Basics of AI/ML, How-toBeginner
How to Predict Numbers with Machine Learning in Python: Regression for Beginners (Food Delivery ML Series, Part 2)
How to Predict Numbers with Machine Learning in Python: Regression for Beginners (Food Delivery ML Series, Part 2)