Posts in tag

Keras


TF Dev Summit ’19 | Introducing TensorFlow 2.0 and its high-level APIs At TensorFlow Dev Summit 2019, the TensorFlow team introduced the Alpha version of TensorFlow 2.0! With TensorFlow 2.0, we are consolidating our APIs and integrating Keras across the TensorFlow ecosystem. In this talk, we give an overview of what to expect with TensorFlow …

TF Dev Summit ’19 | TensorFlow Probability: Learning with confidence TensorFlow Probability (TFP) is a Python library built on TensorFlow that makes it easy to combine probabilistic models and deep learning on modern hardware (TPU, GPU). It’s for data scientists, statisticians, and ML researchers/practitioners who want to encode domain knowledge to understand data and make …

Overview This guide shows how to install Keras. Keras is a high-level neural networks API written and for Python. It is also capable of running on top of TensorFlow.   Prerequisites Python has been installed Installation on Ubuntu Installation on Windows Optional but recommended. Setup a VirtualEnvironment and Pip has been installed. VirtualEnvironment for Ubuntu …

Google I/O 2019 | Cutting Edge TensorFlow: New Techniques There’s lots of great new things available in TensorFlow since last year’s IO. This session will take you through 4 of the hottest from Hyperparameter Tuning with Keras Tuner to Probabilistic Programming to being able to rank your data with learned ranking techniques and TF-Ranking. Finally, …

PyCon 2019 | Getting Started With Deep Learning: Using Keras & Numpy To Detect Voice Disorders Speaker: Deborah Hanus, Sebastian Hanus   Deep learning is a useful tool for problems in computer vision, natural language processing, and medicine. While it might seem difficult to get started in deep learning, Python libraries, such as Keras make …

Google I/O 2019 | Live Coding A Machine Learning Model from Scratch Do you want to build a machine learning model, but not sure where to start? In this session, learn how to start with an empty Colab notebook, code a model using TensorFlow and Keras, train the model live, deploy it to Cloud AI …