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​Hands-On Artificial Intelligence for IoT

​Hands-On Artificial Intelligence for IoT - Second Edition

By : Dr. Amita Kapoor
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​Hands-On Artificial Intelligence for IoT

​Hands-On Artificial Intelligence for IoT

5 (1)
By: Dr. Amita Kapoor

Overview of this book

Transform IoT devices into intelligent systems with this comprehensive guide by Amita Kapoor, Chief AI Officer at Tipz AI. Drawing on 25 years of expertise in developing intelligent systems across industries, she demonstrates how to harness the combined power of artificial intelligence and IoT technology. A pioneer in making AI and neuroscience education accessible worldwide, Amita guides you through creating smart, efficient systems that leverage the latest advances in both fields. This new edition is updated with various optimization techniques in IoT used for enhancing efficiency and performance. It introduces you to cloud platforms such as Platform as a Service (PaaS) and Infrastructure as a Service (IaaS) for analyzing data generated using IoT devices. You’ll learn about machine learning algorithms, deep learning techniques, and practical applications in real-world IoT scenarios and advance to creating AI models that work with diverse data types, including time series, images, and audio. You’ll also harness the power of widely used Python libraries, TensorFlow and Keras, to build a variety of smart AI models. *Email sign-up and proof of purchase required
Table of Contents (22 chapters)
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Part 1: Foundations and Basic Integrations of IoT and AI
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Part 2: Advanced AI Techniques and Their Application in IoT
10
Part 3: Implementing Intelligent IoT Solutions in Diverse Domains
16
Part 4: Applying AI and IoT in Real-World Scenarios

Summary

This chapter dealt with many different data formats and, in the process, many different datasets. We started with the simplest TXT data and accessed the Shakespeare play data. We learned how to read data from CSV files using the csv, NumPy, and pandas modules. We moved on to the JSON format; we used Python’s JSON and pandas modules to access JSON data. From data formats, we progressed to accessing databases and covered both SQL and NoSQL databases. Then, we learned how to work with HDFS in Python. In our pursuit of understanding modern data storage solutions, we turned our attention to object storage, a crucial component in managing vast amounts of unstructured data. We examined popular object storage solutions such as Amazon S3, Google Cloud Storage, and Azure Blob Storage, along with open source alternatives such as MinIO and Ceph. Finally, we ventured into the cutting-edge territory of edge data storage and processing.

Accessing data is the first step. In the next...

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