This is the code repository for Hands-On Artificial Intelligence for IoT, published by Packt.
Expert machine learning and deep learning techniques for developing smarter IoT systems
There are many applications that use data science and analytics to gain insights from terabytes of data. These apps, however, do not address the challenge of continually discovering patterns for IoT data. In Hands-On Artificial Intelligence for IoT, we cover various aspects of artificial intelligence (AI) and its implementation to make your IoT solutions smarter. This book covers the following exciting features:
- Apply different AI techniques including machine learning and deep learning using TensorFlow and Keras
- Access and process data from various distributed sources
- Perform supervised and unsupervised machine learning for IoT data
- Implement distributed processing of IoT data over Apache Spark using the MLLib and H2O.ai platforms
- Forecast time-series data using deep learning methods
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All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
A = tf.placeholder(tf.float32, None, name='A')
B = tf.placeholder(tf.float32, None, name='B')
Following is what you need for this book:
If you are a data science professional or a machine learning developer looking to build smart systems for IoT, Hands-On Artificial Intelligence for IoT is for you. If you want to learn how popular artificial intelligence (AI) techniques can be used in the Internet of Things domain, this book will also be of benefit. A basic understanding of machine learning concepts will be required to get the best out of this book.
With the following software and hardware list you can run all code files present in the book (Chapter 1-12).
| Chapter | Software required | OS required |
|---|---|---|
| 1 | TensorFlow1.x Python 3.5> Numpy 1.14> | Windows10 MacOS 10.x Ubuntu 16.04+ |
| 2 | TensorFlow1.x Python 3.5> Numpy 1.14> | Windows10 MacOS 10.x Ubuntu 16.04+ |
| Keras OpenpyXL SQL | ||
| HDFS H5py | ||
| 3-5,7,9-11 | TensorFlow1.x Python 3.5> Numpy 1.14> | Windows10 MacOS 10.x Ubuntu 16.04+ |
| Keras Scikit Learn Matplotlib | ||
| Pandas Scipy | ||
| 6 | TensorFlow1.x Python 3.5> Numpy 1.14> | MacOS 10.x Ubuntu 16.04+ |
| Keras Scikit Learn Matplotlib | ||
| Pandas Open AI Gym Random | ||
| 8 | TensorFlow1.x Python 3.5> Numpy 1.14> | Ubuntu 16.04 |
| Keras Scikit Learn Matplotlib | ||
| Scipy Pandas Kafka | ||
| TensorFrames SparkDL PySpark | ||
| TensorFlowOnSpark |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Amita Kapoor is an associate professor in the Department of Electronics, SRCASW, University of Delhi, and has been actively teaching neural networks and artificial intelligence for the last 20 years. She completed her master's in electronics in 1996 and her PhD in 2011. During her PhD she was awarded the prestigious DAAD fellowship to pursue part of her research at the Karlsruhe Institute of Technology, Karlsruhe, Germany. She was awarded the Best Presentation Award at the Photonics 2008 international conference. She is an active member of ACM, AAAI, IEEE, and INNS. She has co-authored two books. She has more than 40 publications in international journals and conferences. Her present research areas include machine learning, artificial intelligence, deep reinforcement learning, and robotics.
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