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).
JSNation 2022JSNation 2022
25 min
JavaScript Beats Cancer
Skin cancer is a serious problem worldwide but luckily treatment in the early stage can lead to recovery. JavaScript together with a machine learning model can help Medical Doctors increase the accuracy in melanoma detection. During the presentation, we show how to use Tensorflow.js, Keras and React Native to build a solution that can recognize skin moles and detect if they are a melanoma or a benign mole. We also show issues that we have faced during development. As a summary, we present the pros and cons of JavaScript used for machine learning projects.
ML conf EU 2020ML conf EU 2020
30 min
Boost Productivity with Keras Ecosystem
TensorFlow has built a solid foundation for various machine learning applications, on top of which the Keras ecosystem can really boost the productivity of the developers in building machine learning solutions. Keras has a simple and arbitrarily flexible API for building and training models. However, we still need a lot of manual work to tune the hyperparameters. Fortunately, with Keras Tuner, we can automate the hyperparameter tuning process with minor modifications to the code for building and training the models. To further boost the productivity, we introduce AutoKeras, which fully automates the model building, training, and hyperparameter tuning process. It dramatically reduces the amount of prior knowledge needed of using machine learning for some common tasks. All you need is to define the task and to provide the training data.