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TensorFlow
PyTorch
Scikit-learn
TFlearn
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Cert Decoder
Cert Decoder is a free online tool that helps you decode X.509 SSL/TLS certificates in PEM format. It instantly shows important information like the issuer, expiry date, SAN entries, and fingerprint. All data is processed locally in your browser, so nothing is ever sent or stored elsewhere.
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Cert Decoder's answer:
I built certdecoder.com over the weekend for my own needs. Sometimes in my work, I need to verify and check certificate details.
Cert Decoder's answer:
certdecoder.com was built using just JavaScript and HTML—simple, fast, and with all processing happening locally in your browser, so no certificate data is sent to any server
Cert Decoder's answer:
certdecoder.com is primarily built for developers, sysadmins, cybersecurity enthusiasts, and DevOps engineers.
Cert Decoder's answer:
Simple, fast, and reliable. Some similar tools can’t even decode basic certificates. I rigorously tested my tool with many real-world certificates and covered several edge cases where competitors fall short.
Cert Decoder's answer:
certdecoder.com is primarily built for developers, sysadmins, cybersecurity enthusiasts, and DevOps engineers.
Based on our record, Keras seems to be a lot more popular than Cert Decoder. While we know about 35 links to Keras, we've tracked only 1 mention of Cert Decoder. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The unchallenged leader in AI development is still Python. And Keras, and robust community support. - Source: dev.to / over 1 year ago
If you need simplicity, Keras is a great high-level API built on top of TensorFlow. It lets you quickly prototype neural networks without worrying about low-level implementations. Keras is perfect for getting those first models up and running—an essential part of the startup hustle. - Source: dev.to / almost 2 years ago
At its heart is TensorFlow Core, which provides low-level APIs for building custom models and performing computations using tensors (multi-dimensional arrays). It has a high-level API, Keras, which simplifies the process of building machine learning models. It also has a large community, where you can share ideas, contribute, and get help if you are stuck. - Source: dev.to / almost 2 years ago
The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / about 2 years ago
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / over 2 years ago
Why? Because I built certdecoder.com and couldn’t find a decent place to submit it. So I said screw it — I’ll build my own. With blackjack and hookers. - Source: dev.to / over 1 year ago
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
TFlearn - TFlearn is a modular and transparent deep learning library built on top of Tensorflow.
Clarifai - The World's AI
MLKit - MLKit is a simple machine learning framework written in Swift.