9.5 TensorFlow and PyTorch

TensorFlow (Google) and PyTorch (Meta) are the two big frameworks for building and training deep learning models.

Chapter 9: Tools and Technologies for AI

TensorFlow was released by Google in 2015, and Keras - now part of it - makes building networks beginner-friendly. PyTorch came out of Meta (Facebook) in 2016 and became a favourite in research for being flexible and feeling very "Pythonic".

Both let you define neural network layers, train them on GPUs and deploy them. Many of today's big AI models are built with PyTorch.

Which should you learn? Either is fine - concepts transfer. Many beginners start with Keras for its simplicity, or PyTorch because so many tutorials and research projects use it.

Key takeaways

TensorFlow/Keras (Google) and PyTorch (Meta)

Both build and train deep neural networks

PyTorch is very popular in research

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1.1 What Is Artificial Intelligence (AI)?
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1.3 History and Evolution of AI
1.4 Goals and Objectives of AI
1.5 Importance of AI in Today's World
1.6 Real-World Applications of AI
1.7 Advantages and Limitations of AI
2.1 Narrow AI (Weak AI)
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3.1 How AI Works
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5.1 What Is Deep Learning?
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6.1 What Is Generative AI?
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8.2 Structured and Unstructured Data
8.3 Data Collection and Preparation
8.4 Introduction to Algorithms
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9.1 Introduction to Python for AI
9.2 NumPy and Pandas
9.3 Matplotlib for Data Visualization
9.4 Scikit-learn
9.5 TensorFlow and PyTorch
9.6 AI APIs and Online Platforms
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10.1 AI in Education
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12.1 Emerging AI Trends
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12.3 Human–AI Collaboration
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