Keras 3: Deep Learning for Humans Keras 3 is a multi-backend deep learning framework, with support for JAX, TensorFlow, and PyTorch. Effortlessly build and train models for computer vision, natural language processing, audio processing, timeseries forecasting, recommender systems, etc. Accelerated mo...
Keras: Deep Learning for humans You have just found Keras. Keras is a high-level neural networks API, written in Python and capable of running on top ofTensorFlow,CNTK, orTheano. It was developed with a focus on enabling fast experimentation.Being able to go from idea to result with the ...
# Keras: Deep Learning for humans You have just found Keras. Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result ...
maketechhuman
《Machine Learning for Humans》 介绍:(文本)机器学习可视化分析工具. 《A Plethora of Tools for Machine Learning》 介绍:机器学习工具包/库的综述/比较. 《The art of visualizing visualizations: a best practice guide》 介绍:数据可视化最佳实践指南. ...
In contrast to prediction tasks, it is not self-obvious how deep networks can help understand a natural process such as a cognitive task performed by humans (e.g., decision making). Here we propose a methodology for using a deep learning model to analyse a cognitive decision making process....
Dive into the science behind deep learning and understand how computers mimic human learning processes. Explore the hierarchical models, learning rates, and approaches that make deep learning a transformative force in artificial intelligence.
For robots to coexist with humans in a social world like ours, it is crucial that they possess human-like social interaction skills. Programming a robot to possess such skills is a challenging task. To addresses this challenge, we present two deep reinforcement learning based self-learning paradi...
Dive into the science behind deep learning and understand how computers mimic human learning processes. Explore the hierarchical models, learning rates, and approaches that make deep learning a transformative force in artificial intelligence.
learning rate, for each snapshot, the model reaches a local minimum having a lower error rate and thus fitting the training data totally (means it has a very high variance). Again, when the model is saved during the rise of the learning rate, it has a comparatively higher error rate ...