Hands-On Problem Solving for Machine Learning [Video]

By Rudy Lai

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Working with Machine Learning
- The Course Overview
- Goals and Variations in Machine Learning
- Installing WinPython and Using Jupyter Notebooks
- Exploring Your Data Using Pandas
Data Wrangling
- Types of Messy Data and How to Clean Them
- Parsing Timestamps and Splitting Columns
- Loading Data from Excel, CSVs, and SQL
Linear Regression — Predict Median Living Costs
- Understanding Linear Regression
- Implementing Linear Regression with Scikit-learn
- Troubleshooting Linear Regression
Logistic Regression â€” Classify Flowers
- Exploring and Cleaning the Plants Dataset
- Understanding Logistic Regression
- Implementing Train-Test-Splits and Logistic Regression
Predicting the Future
- Build a Robust Model with Cross Validation
- Create Complex Models with Scikit-learn Pipelines
- Find the Best Model with Hyperparameter Search
Diagnosing Issues with Models
- Understanding Our Accuracy in Predicting Numbers
- Assessing Our Correctness in Predicting Labels
- Dealing with Overfitting Using Regularization