This is the code repository for Hands-on Artificial Intelligence with TensorFlow, published by Packt.
Useful techniques in machine learning and deep learning for building intelligent applications
Artificial Intelligence (AI) is a popular area with an emphasis on creating intelligent machines that can reason, evaluate, and understand the same way as humans. It is used extensively across many fields, such as image recognition, robotics, language processing, healthcare, finance, and more.
This book covers the following exciting features: Explore the core concepts of AI and its different approaches Use the TensorFlow framework for smart applications Implement various machine and deep learning algorithms with TensorFlow Design self-learning RL systems and implement generative models Perform GPU computing efficiently using best practices Build enterprise-grade apps for computer vision, NLP, and healthcare
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
# We will use sklearn to create training and testing data
# and for normalization of the data set
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
Following is what you need for this book: Hands-On Artificial Intelligence with TensorFlow is for you if you are a machine learning developer, data scientist, AI researcher, or anyone who wants to build artificial intelligence applications using TensorFlow. You need to have some working knowledge of machine learning to get the most out of this book.
With the following software and hardware list you can run all code files present in the book (Chapter 1-1).
| Chapter | Software required | OS required |
|---|---|---|
| 1-12 | Jupyter Notebook | Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Amir Ziai Amir Ziai is a senior data scientist at Netflix, where he works on streaming security involving petabyte-scale machine learning platforms and applications. He has worked as a data scientist in AdTech, HealthTech, and FinTech companies. He holds a master's degree in data science from UC Berkeley.
Ankit Dixit Ankit Dixit is a deep learning expert at AIRA Matrix in Mumbai, India and having an experience of 7 years in the field of computer vision and machine learning. He is currently working on the development of full slide medical image analysis solutions in his organization. His work involves designing and implementation of various customized deep neural networks for image segmentation as well as classification tasks. He has worked with different deep neural network architectures such as VGG, ResNet, Inception, Recurrent Neural Nets (RNN) and FRCNN. He holds a masters degree in computer vision specialization. He has also authored an AI/ML book.
Click here if you have any feedback or suggestions.