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Roshak, Michael. Artificial Intelligence for IoT Cookbook: Over 70 Recipes for Building AI Solutions for Smart Homes, Industrial IoT, and Smart Cities. — Birmingham: Packt Publishing, Limited, 2021. — 1 online resource (252 pages) — <URL:http://elib.fa.ru/ebsco/2747794.pdf>.Дата создания записи: 27.03.2021 Тематика: Artificial intelligence — Computer programs.; Internet of things.; Artificial intelligence — Industrial applications.; Intelligence artificielle — Logiciels.; Internet des objets.; Intelligence artificielle — Applications industrielles.; Artificial intelligence — Computer programs.; Artificial intelligence — Industrial applications.; Internet of things. Коллекции: EBSCO Разрешенные действия: –
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Оглавление
- Cover
- Title Page
- Copyright and Credits
- Contributors
- Table of Contents
- Preface
- Chapter 1: Setting Up the IoT and AI Environment
- Choosing a device
- Dev kits
- Manifold 2-C with NVIDIA TX2
- The i.MX series
- LattePanda
- Raspberry Pi Class
- Arduino
- ESP8266
- Dev kits
- Setting up Databricks
- Storing data
- Parquet
- Avro
- Delta Lake
- Storing data
- Setting up IoT Hub
- Getting ready
- How to do it...
- How it works...
- Setting up an IoT Edge device
- Getting ready
- How to do it...
- Configuring an IoT Edge device (cloud side)
- Configuring an IoT Edge device (device side)
- How it works...
- Deploying ML modules to Edge devices
- Getting ready
- How to do it...
- How it works...
- There's more...
- Setting up Kafka
- Getting ready
- How to do it...
- How it works...
- There's more...
- Installing ML libraries on Databricks
- Getting ready
- How to do it...
- Importing TensorFlow
- Installing PyTorch
- Installing GraphX and GraphFrames
- How it works...
- Choosing a device
- Chapter 2: Handling Data
- Storing data for analysis using Delta Lake
- Getting ready
- How to do it...
- How it works...
- Data collection design
- Getting ready
- How to do it...
- Variance
- Z-Spikes
- Min/max
- Windowing
- Getting ready
- How to do it...
- Tumbling
- Hopping
- Sliding
- How it works...
- Exploratory factor analysis
- Getting ready
- How to do it...
- Visual exploration
- Chart types
- Redundant sensors
- Sample co-variance and correlation
- Visual exploration
- How it works...
- There's more...
- Implementing analytic queries in Mongo/hot path storage
- Getting ready
- How to do it...
- How it works...
- Ingesting IoT data into Spark
- Getting ready
- How to do it...
- How it works...
- Storing data for analysis using Delta Lake
- Chapter 3: Machine Learning for IoT
- Analyzing chemical sensors with anomaly detection
- Getting ready
- How to do it...
- How it works...
- There's more...
- Logistic regression with the IoMT
- Getting ready
- How to do it...
- How it works...
- There's more...
- Classifying chemical sensors with decision trees
- How to do it...
- How it works...
- There's more...
- Simple predictive maintenance with XGBoost
- Getting ready
- How to do it...
- How it works...
- Detecting unsafe drivers
- Getting ready
- How to do it...
- How it works...
- There's more...
- Face detection on constrained devices
- Getting ready
- How to do it...
- How it works...
- Analyzing chemical sensors with anomaly detection
- Chapter 4: Deep Learning for Predictive Maintenance
- Enhancing data using feature engineering
- Getting ready
- How to do it...
- How it works...
- There's more...
- Using keras for fall detection
- Getting ready
- How to do it...
- How it works...
- There's more...
- Implementing LSTM to predict device failure
- Getting ready
- How to do it...
- How it works...
- Deploying models to web services
- Getting ready
- How to do it...
- How it works...
- There's more...
- Enhancing data using feature engineering
- Chapter 5: Anomaly Detection
- Using Z-Spikes on a Raspberry Pi and Sense HAT
- Getting ready
- How to do it...
- How it works...
- Using autoencoders to detect anomalies in labeled data
- Getting ready
- How to do it...
- How it works...
- There's more...
- Using isolated forest for unlabeled datasets
- Getting ready
- How to do it...
- How it works...
- There's more...
- Detecting time series anomalies with Luminol
- Getting ready
- How to do it...
- How it works...
- There's more...
- Detecting seasonality-adjusted anomalies
- Getting ready
- How to do it...
- How it works...
- Detecting spikes with streaming analytics
- Getting ready
- How to do it...
- How it works...
- Detecting anomalies on the edge
- Getting ready
- How to do it...
- How it works...
- Using Z-Spikes on a Raspberry Pi and Sense HAT
- Chapter 6: Computer Vision
- Connecting cameras through OpenCV
- Getting ready
- How to do it...
- How it works...
- There's more...
- Using Microsoft's custom vision to train and label your images
- Getting ready
- How to do it...
- How it works...
- Detecting faces with deep neural nets and Caffe
- Getting ready
- How to do it...
- How it works...
- Detecting objects using YOLO on Raspberry Pi 4
- Getting ready
- How to do it...
- How it works...
- Detecting objects using GPUs on NVIDIA Jetson Nano
- Getting ready
- How to do it...
- How it works...
- There's more...
- Training vision with PyTorch on GPUs
- Getting ready
- How to do it...
- How it works...
- There's more...
- Connecting cameras through OpenCV
- Chapter 7: NLP and Bots for Self-Ordering Kiosks
- Wake word detection
- Getting ready
- How to do it...
- How it works...
- There's more...
- Speech-to-text using the Microsoft Speech API
- Getting ready
- How to do it...
- How it works...
- Getting started with LUIS
- Getting ready
- How to do it...
- How it works...
- There's more...
- Implementing smart bots
- Getting ready
- How to do it...
- How it works...
- There's more...
- Creating a custom voice
- Getting ready
- How to do it...
- How it works...
- Enhancing bots with QnA Maker
- Getting ready
- How to do it...
- How it works...
- There's more...
- Wake word detection
- Chapter 8: Optimizing with Microcontrollers and Pipelines
- Introduction to ESP32 with IoT
- Getting ready
- How to do it...
- How it works...
- There's more...
- Implementing an ESP32 environment monitor
- Getting ready
- How to do it...
- How it works...
- There's more...
- Optimizing hyperparameters
- Getting ready
- How to do it...
- How it works...
- Dealing with BOM changes
- Getting ready
- How to do it...
- How it works...
- There's more...
- Building machine learning pipelines with sklearn
- Getting ready
- How to do it...
- How it works...
- There's more...
- Streaming machine learning with Spark and Kafka
- Getting ready
- How to do it...
- How it works...
- There's more...
- Enriching data using Kafka's KStreams and KTables
- Getting ready
- How to do it...
- How it works...
- There's more...
- Introduction to ESP32 with IoT
- Chapter 9: Deploying to the Edge
- OTA updating MCUs
- Getting ready
- How to do it...
- How it works...
- There's more...
- Deploying modules with IoT Edge
- Getting ready
- Setting up our Raspberry Pi
- Coding setup
- How to do it...
- How it works...
- There's more...
- Getting ready
- Offloading to the web with TensorFlow.js
- Getting ready
- How to do it...
- How it works...
- There's more...
- Deploying mobile models
- Getting ready
- How to do it...
- How it works...
- Maintaining your fleet with device twins
- Getting ready
- How to do it...
- How it works...
- There's more...
- Enabling distributed ML with fog computing
- Getting ready
- How to do it...
- How it works...
- There's more...
- OTA updating MCUs
- About PACKT
- Index
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