Exception Handling In Python Applied Ai With Python Batch 1 Class 6 Mohan Sivaraman

Summary

Comparing classification models on a loan-approval dataset, with preprocessing for skewed and numeric columns using pipelines ... Iterating over lists and strings with for loops and range, list comprehension, sorting and reversing a list. Playlist: What web applications are, and how a plain Removing data with pop(), working with JSON, looping with items() and dictionary comprehension. Playlist: Introduction to unsupervised learning: clustering basics, why scaling matters, and a PCA demo. Playlist: Hands-on dictionary practice: keys and values, updating and adding keys, mixed key types, and common pitfalls. Playlist: ... Default and keyword arguments, *args and **kwargs, and when each one is the right choice. Playlist: Ensemble learning with Random Forest, the confusion matrix, and a credit card Converting categorical data to numbers with map() and scikit-learn preprocessing, and filling missing data with SimpleImputer. Training, saving and serving a model as an API, testing it with Postman, pushing it to GitHub and deploying on Render. Playlist: ... What prompt engineering is, open vs closed models, zero-shot and role-based prompting, using Markdown files for better prompts ...