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requirements_lock_3_12.txt
# via # -r requirements.in # keras-nightly idna==3.7 \ --hash=sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc \ --hash=sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0 # via requests jax==0.4.7 \ --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8 # via -r requirements.in keras-nightly==3.0.4.dev2024021403 \
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requirements_lock_3_9.txt
--hash=sha256:f47619d978ab1ae7dfdc4052ea97c636c6263e1f19bd1be0e42c346b98d15ff4 # via # jax # keras-nightly namex==0.0.7 \ --hash=sha256:84ba65bc4d22bd909e3d26bf2ffb4b9529b608cb3f9a4336f776b04204ced69b \ --hash=sha256:8a4f062945f405d77cb66b907f16aa2fd83681945e998be840eb6c4154d40108 # via keras-nightly numpy==1.23.5 ; python_version <= "3.11" \
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requirements_lock_3_10.txt
# via # -r requirements.in # keras-nightly idna==3.7 \ --hash=sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc \ --hash=sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0 # via requests jax==0.4.7 \ --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8 # via -r requirements.in keras-nightly==3.0.4.dev2024021403 \
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requirements_lock_3_11.txt
# via # -r requirements.in # keras-nightly idna==3.7 \ --hash=sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc \ --hash=sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0 # via requests jax==0.4.7 \ --hash=sha256:5e7002d74db25f97c99b979d4ba1233b1ef26e1597e5fc468ad11d1c8a9dc4f8 # via -r requirements.in keras-nightly==3.0.4.dev2024021403 \
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docs/en/data/external_links.yml
- author: Shane Soh author_link: https://medium.com/@shane.soh link: https://medium.com/analytics-vidhya/deploy-machine-learning-models-with-keras-fastapi-redis-and-docker-4940df614ece title: Deploy Machine Learning Models with Keras, FastAPI, Redis and Docker - author: Mandy Gu author_link: https://towardsdatascience.com/@mandygu
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