更新时间：2021-06-10 18:47:12
coverpage
Title Page
About Packt
Why subscribe?
Packt.com
Contributors
About the author
About the reviewer
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Conventions used
Get in touch
Reviews
How to Solve All Machine Learning Problems
What is a problem?
What is an algorithm?
What is machine learning?
Do you need machine learning?
The general problem solving process
What is a model?
What is a good model?
On writing and chapter organization
Why Go?
Quick start
Functions
Variables
Values
Types
Methods
Interfaces
Packages and imports
Let's Go!
Linear Regression - House Price Prediction
The project
Exploratory data analysis
Ingestion and indexing
Janitorial work
Encoding categorical data
Handling bad numbers
Final requirement
Writing the code
Further exploratory work
The conditional expectation functions
Skews
Multicollinearity
Standardization
Linear regression
The regression
Cross-validation
Running the regression
Discussion and further work
Summary
Classification - Spam Email Detection
Tokenization
Normalizing and lemmatizing
Stopwords
Ingesting the data
Handling errors
The classifier
Naive Bayes
TF-IDF
Conditional probability
Features
Bayes' theorem
Implementating the classifier
Class
Alternative class design
Classifier part II
Putting it all together
Decomposing CO2 Trends Using Time Series Analysis
Downloading from non-HTTP sources
Handling non-standard data
Dealing with decimal dates
Plotting
Styling
Decomposition
STL
LOESS
The algorithm
Using STL
How to lie with statistics
More plotting
A primer on Gonum plots
The residuals plotter
Combining plots
Forecasting
Holt-Winters
References
Clean Up Your Personal Twitter Timeline by Clustering Tweets
K-means
