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							| @@ -8,14 +8,14 @@ This project implemented several neural architecture search (NAS) and hyper-para | ||||
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| ## **Who should consider using AutoDL-Projects** | ||||
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| - Beginner who want to **try different AutoDL algorithms** for study | ||||
| - Engineer who want to **try AutoDL** to investigate whether AutoDL works on your projects | ||||
| - Beginners who want to **try different AutoDL algorithms** | ||||
| - Engineers who want to **try AutoDL** to investigate whether AutoDL works on your projects | ||||
| - Researchers who want to **easily** implement and experiement **new** AutoDL algorithms. | ||||
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| ## **Why should we use AutoDL-Projects** | ||||
| - Simplest library dependencies: each examlpe is purely relied on PyTorch or Tensorflow (except for some basic libraries in Anaconda) | ||||
| - All algorithms are in the same codebase. If you implement new algorithms, it is easy to fairly compare with many other baselines. | ||||
| - I will actively support this project, because all my furture AutoDL research will be built upon this project. | ||||
| - Simple library dependencies | ||||
| - All algorithms are in the same codebase | ||||
| - Active maintenance | ||||
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| ## AutoDL-Projects Capabilities | ||||
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