TensorFlow was developed by the Google Brain team for internal Google use in research and production. The initial version was released under the Apache License 2.0 in 2015. TensorFlow is an open-source machine learning platform that offers a flexible ecosystem of tools, libraries, and community resources. It’s heavily utilized by data scientists for tasks involving machine learning and artificial intelligence. TensorFlow operates by creating a flow of data through a computational graph, where nodes represent mathematical operations and edges represent the data (tensors) flowing between them. This architecture allows for efficient parallel computation and is particularly beneficial for tasks like deep learning. TensorFlow’s versatility makes it suitable for a wide range of applications in the field of machine learning.
Here are some of its key features:
- High-Level APIs
- Open-Source
- Versatile Deployment
- Neural Network Support
- Eager Execution and Graph Mode
- Responsive Construct and Flexibility
- Large Community
- Support for Various Computations
Best suited for:
- Data Scientists
- Deep Learning Enthusiasts
- Those Focused on AI Products
| PROS | CONS |
|---|---|
| Visualizing Data | Limited OS Support |
| Debugging Ease | Rapid Updates |
| Diverse Applications | Training Limitations |
| Flexibility | Inconsistencies |
| Language Limitations |
Pricing:
| Starting Price | Free |
| Free Version | N/A |
| Free Trial | N/A |