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Breaking Down Bayes' Theorem
Bayes' Theorem is the foundation of Bayesian Statistics commonly used in Data Science and Machine Learning! Read more about how it works here!
Predicting Tweet Author with Naive Bayes
In this project, we'll use the Twitter API and Naive Bayes to predict whether a newly presented Tweet was authored by Barack Obama or Donald Trump.
Evaluation Metrics: Accuracy, Precision, Recall, and F1 Score
Learn how to increase and understand model performance with Accuracy, Precision, Recall, and F1 Score!
Overfitting and Underfitting Models
Learn what it means to have an overfit and underfit model and how to find the "sweet spot" between the two.
Histograms make visualizing important aspects of our data simple. Discover how to read and interpret the insight they provide!
Handling NaN in Pandas
Almost all data projects involve missing or unknown values. Learn all you need to know about handling these values (NaN) in Pandas.
The Data Mining Process (CRISP-DM)
Learn how to structure your data science project from start to finish using the Cross-Industry Standard Process for Data Mining (CRISP-DM).
Python List Comprehensions Made Simple
A gentle introduction to list comprehensions. Understanding list comprehensions is an important stepping stone for anyone hoping to break into an intermediate understanding of Python.
Introduction to SQL Joins
Your one-stop-shop introduction to SQL Joins. Learn how to connect critical related data by querying data across multiple tables.
Python Crash Course Review
Whether you're an absolute beginner to programming, looking for a quick way to learn the basics of the Python language, or an intermediate Pythonista looking to explore additional applications of Python programming using special libraries and frameworks, this book is perfect for you.
Add, Rename, and Delete Columns in Pandas
The ultimate beginner's guide to adding, renaming, and deleting columns in the popular Python library, Pandas!