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Keras is an open-source library of high-level neural networks written in Python. It allows developers to quickly create and prototype deep learning models, as well as run them on both CPUs and GPUs. Keras is designed to make developing deep learning models fast and easy, while still being powerful and flexible. It supports a range of different architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs).
JavaScript Beats Cancer
JSNation 2022JSNation 2022
25 min
JavaScript Beats Cancer
Karol Przystalski
Karol Przystalski
Codete & Medtransfer, Poland
This Talk discusses using JavaScript to combat skin cancer, with a focus on machine learning integration. The speaker has experience in medical imaging and has partnered with dermatoscopy companies to develop hardware. JavaScript libraries like TensorFlow.js and Pandas.js are used for model deployment and data analysis. The Talk also covers building neural networks, analyzing skin cancer using scoring methods and image processing techniques, and extracting asymmetry in skin images using Python and JavaScript.
kerasreact nativetensorflowinnovation
Boost Productivity with Keras Ecosystem
ML conf EU 2020ML conf EU 2020
30 min
Boost Productivity with Keras Ecosystem
Haifeng Jin
Haifeng Jin
Keras Team at Google
This Talk introduces the TensorFlow in Keras ecosystem and highlights its features, including tensor manipulations, automatic differentiation, and deployment. It also discusses the workflow and automation of hyperparameter tuning with Keras Tuner and AutoKeras. The Talk emphasizes the simplicity and productivity of using AutoKeras, which supports various tasks and advanced scenarios. It also mentions the challenges beginners face and provides resources for learning. Lastly, it touches on the use of TensorFlow and Keras in the research domain and the customization options in AutoKeras, including time series forecasting.
kerastensorflowmachine learning