Keep Looking, Don't Settle

2019-03-02 Week 9

Shares From Internet

  1. Visualizing gradient descent in action An ineresting project to show how learning rate will affect the converge. If LR is too small, it will converge very slowly. If LR is too big(like 1.01), it will diverge.
  2. How to add new embeddings for unknown words in Tensorflow (training & pre-set for testing)
  3. How to Develop a Word Embedding Model for Predicting Movie Review Sentiment It is possible that the loaded embedding does not contain all of the words in our chosen vocabulary. As such, when creating the Embedding weight matrix, we need to skip words that do not have a corresponding vector in the loaded GloVe data. Or if the testing data has some out of vocabulary words, you may add a "UNKNOWN" word in the vocabulary and give a unique index for this special word, then you should random initialize the weights of this word.
  4. Using pre-trained embeddings for out of vocabulary words
  5. Ask HN: Tools or sites you use to scope out a workplace before taking a job?
  6. AutoML toolkit for neural architecture search and hyper-parameter tuning NNI (Neural Network Intelligence) 是自动机器学习(AutoML)的工具包。 它通过多种调优的算法来搜索最好的神经网络结构和(或)超参,并支持单机、本地多机、云等不同的运行环境。
  7. immersive linear algebra: Linear Algebra with interactive display and graphs.