Review of Python Courses (Part 29)

In Part 28, I summarized my Datacamp courses 83-85. Today I will continue with the next three.

As a reminder, I introduced you to my recent work learning Python here.

My course #86 was Hyperparameter Tuning in Python. This course covers:

• Introduction (visualize Random Forest)
• Hyperparameters overview
• Hyperparameters values
• Introducing grid search
• Grid search with Scikit Learn (from sklearn import metrics)
• Understanding grid search output
• Introducing random search (from itertools import product)
• Random search in Scikit Learn (from sklearn.model_selection import RandomizedSearchCV)
• Comparing grid and random search
• Informed search: coarse to fine
• Informed methods: Bayesian statistics
• Informed methods: genetic algorithms (from tpot import TPOTClassifier)

My course #87 was Case Studies in Statistical Thinking. Topics covered in this course include:

• Activity of zebrafish and melatonin
• Bootstrap confidence intervals
• Hypothesis tests (permutation test)
• Linear regression and pairs bootstrap
• Introduction to swimming data
• Do swimmers go faster in the finals (how to do permutation test exercise)?
• How does the performance of swimmers decline over long events?
• Introduction to the current controversy
• The zigzag effect
• Recap of swimming analysis
• Introduction to statistical seismology
• Timing of major earthquakes
• How are the Parkfield interearthquake times distributed?
• Variations in earthquake frequency and seismicity
• Earthquake magnitudes in Oklahoma

My course #88 was Analyzing Police Activity with Pandas. This course covers:

• Stanford Open Policing Project dataset (count missing values in each column)
• Using proper data types
• Creating a Datetime index
• Do the genders commit different violations?
• Does gender affect who gets a ticket for speeding?
• Does gender affect whose vehicle is searched?
• Does gender affect who is frisked during a search?
• Does time of day affect arrest rate?
• Are drug-related stops on the rise?
• What violations are caught in each district?
• How long might you be stopped for a violation?
• Exploring the weather dataset
• Categorizing the weather
• Merging datasets
• Does weather affect the arrest rate?

I will review more courses next time.