更新时间：2021-07-02 14:02:40
coverpage
Title Page
Copyright and Credits
Hands-On Artificial Intelligence for IoT
Dedication
About Packt
Why subscribe?
Packt.com
Contributors
About the author
About the reviewers
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
Download the color images
Conventions used
Get in touch
Reviews
Principles and Foundations of IoT and AI
What is IoT 101?
IoT reference model
IoT platforms
IoT verticals
Big data and IoT
Infusion of AI – data science in IoT
Cross-industry standard process for data mining
AI platforms and IoT platforms
Tools used in this book
TensorFlow
Keras
Datasets
The combined cycle power plant dataset
Wine quality dataset
Air quality data
Summary
Data Access and Distributed Processing for IoT
TXT format
Using TXT files in Python
CSV format
Working with CSV files with the csv module
Working with CSV files with the pandas module
Working with CSV files with the NumPy module
XLSX format
Using OpenPyXl for XLSX files
Using pandas with XLSX files
Working with the JSON format
Using JSON files with the JSON module
JSON files with the pandas module
HDF5 format
Using HDF5 with PyTables
Using HDF5 with pandas
Using HDF5 with h5py
SQL data
The SQLite database engine
The MySQL database engine
NoSQL data
HDFS
Using hdfs3 with HDFS
Using PyArrow's filesystem interface for HDFS
Machine Learning for IoT
ML and IoT
Learning paradigms
Prediction using linear regression
Electrical power output prediction using regression
Logistic regression for classification
Cross-entropy loss function
Classifying wine using logistic regressor
Classification using support vector machines
Maximum margin hyperplane
Kernel trick
Classifying wine using SVM
Naive Bayes
Gaussian Naive Bayes for wine quality
Decision trees
Decision trees in scikit
Decision trees in action
Ensemble learning
Voting classifier
Bagging and pasting
Improving your model – tips and tricks
Feature scaling to resolve uneven data scale
Overfitting
Regularization
Cross-validation
No Free Lunch theorem
Hyperparameter tuning and grid search
Deep Learning for IoT
Deep learning 101
Deep learning—why now?
Artificial neuron
Modelling single neuron in TensorFlow
Multilayered perceptrons for regression and classification
The backpropagation algorithm
Energy output prediction using MLPs in TensorFlow
Wine quality classification using MLPs in TensorFlow
