Home Page Icon
Home Page
Table of Contents for
Thank you
Close
Thank you
by Xuanyi Chew
Go Machine Learning Projects
Title Page
Copyright and Credits
Go Machine Learning Projects
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
The project 
Exploratory data analysis 
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
Summary
Decomposing CO2 Trends Using Time Series Analysis
Exploratory data 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
Summary
References
Clean Up Your Personal Twitter Timeline by Clustering Tweets
The project 
K-means 
DBSCAN
Data acquisition
Exploratory data analysis
Data massage
The processor 
Preprocessing a single word 
Normalizing a string
Preprocessing stopwords
Preprocessing Twitter entities 
Processing a single tweet 
Clustering 
Clustering with K-means 
Clustering with DBSCAN 
Clustering with DMMClust 
Real data
The program 
Tweaking the program
Tweaking distances 
Tweaking the preprocessing step 
Summary
Neural Networks - MNIST Handwriting Recognition
A neural network
Emulating a neural network
Linear algebra 101
Exploring activation functions
Learning
The project
Gorgonia
Getting the data
Acceptable format
From images to a matrix
What is a tensor?
From labels to one-hot vectors
Visualization
Preprocessing
Building a neural network
Feed forward
Handling errors with maybe
Explaining the feed forward function
Costs
Backpropagation
Training the neural network
Cross-validation
Summary
Convolutional Neural Networks - MNIST Handwriting Recognition
Everything you know about neurons is wrong 
Neural networks – a redux
Gorgonia
Why?
Programming
What is a tensor? – part 2
All expressions are graphs
Describing a neural network
One-hot vector
The project
Getting the data
Other things from the previous chapter
CNNs
What are convolutions?
How Instagram filters work
Back to neural networks
Max-pooling
Dropout
Describing a CNN
Backpropagation
Running the neural network
Testing
Accuracy
Summary
Basic Facial Detection
What is a face? 
Viola-Jones
PICO 
A note on learning 
GoCV 
API 
Pigo
Face detection program 
Grabbing an image from the webcam 
Displaying the image 
Doodling on images 
Face detection 1 
Face detection 2
Putting it all together
Evaluating algorithms
Summary
Hot Dog or Not Hot Dog - Using External Services
MachineBox
What is MachineBox?
Signing in and up 
Docker installation and setting up
Using MachineBox in Go
The project
Training 
Reading from the Webcam 
Prettifying the results
The results
What does this all mean? 
Why MachineBox?
Summary
What's Next?
What should the reader focus on? 
The practitioner 
The researcher 
The researcher, the practitioner, and their stakeholder
What did this book not cover?
Where can I learn more?
Thank you
Other Books You May Enjoy
Leave a review - let other readers know what you think
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Prev
Previous Chapter
Where can I learn more?
Next
Next Chapter
Other Books You May Enjoy
Thank you
Thank you for reading this book; I hope it has been useful to you.
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset