TensorFlow 1.x Deep Learning Recipes for Artificial Intelligence Applications
Real-life use cases to build artificial intelligence algorithms with TensorFlow
Created by Alvaro Fuentes
Explore practical ways to apply deep learning using TensorFlow in areas like computer vision, natural language processing, reinforcement learning, and finance. Gain hands-on experience building models that solve real-world problems and see how advanced techniques come together in actual AI applications.
Packt | Jun 2018 | 185 min
What You Will Learn
You will work through a series of practical recipes that guide you step by step in building and training deep learning models using TensorFlow. Each project focuses on a specific domain, helping you understand both the concepts and the code needed to solve real problems. By experimenting with these examples, you'll develop the confidence to tackle your own AI challenges.
Key Features
- Build and train neural networks for image, text, and sequential data tasks
- Apply reinforcement learning to create intelligent decision-making systems
- Deploy deep learning models for practical use in various domains
Target Audience
Ideal for data analysts, data scientists, engineers, and Python developers who already understand basic machine learning and neural networks. If you want to move beyond theory and start building deep learning solutions with TensorFlow, you'll find these hands-on projects especially useful for advancing your skills and applying them to real-world tasks.
