Amazing progress has been made in deep learning. I have been Tensorflow for a while now. I started out with tf0.6 then upgraded to tf0.12 then to tf1.0. The latest version is tf1.10 which is supposed to provide a stable API. I have a lot of code which has now become incompatible. The tf0.6's saver … Continue reading Organizing my Neural Network Codes
Tag: machine learning
Deep Learning Overview
View my Deep Learning Overview : [Google Slides] Deep Learning Research Projects: [Google Slides] Beware, these things get out of date very quick. This presentation is from Oct 2016. The outline of the talk: Toy Neural Network Loss Function Stochastic Gradient Descent Forward-pass (Neural Function Evaluation) Backward-pass (Gradient of Neural function wrt to params) Recent … Continue reading Deep Learning Overview
Toy Neural Network
In my last post on neural network [HERE], I talked on how one can think of neural network as universal approximators. In this post I am trying to help understand a toy neural network implementation. In particular one can have a clearer and intuitive understanding of what a forward_pass is and what back_propagation means. Most … Continue reading Toy Neural Network
Machine Learning : Handling Imbalanced Datasets
When dealing with real datasets in machine learning or data mining, we quite frequently encounter a 2 category classification task. However, to add to our agony the dataset is skewed. This means samples from one class are more in number than the other. There are a few well know techniques to get around the problem. … Continue reading Machine Learning : Handling Imbalanced Datasets
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