A.I, Data and Software Engineering
Sometimes, we want to reduce the training time by using a subset of a very large dataset while the negative samples outnumbers the positive ones, e.g. word embedding. Another situation when we deal with implicit data. In this case, we may need to populate new data for negative values. This post demonstrates how to generate data for training using uniform negative sampling. The data Originally...
In this article, we review some common metrics and their uses for two main ML problems, i.e. regression and classification. Regression Metrics Most of the blogs have focussed on classification metrics like precision, recall, AUC etc. For a change, I wanted to explore all kinds of metrics including those used in regression as well. MAE and RMSE are the two most popular metrics for continuous...
This quick note is one solution (may not optimal) to prevent Colab from disconnecting during training your deep learning model. disconnect Problem Recently, my Google Colab notebook often gets disconnected after a while, and the data is lost. I searched and found a solution. So reshare this here. SOLUTION So to prevent this, we add a JS code to the console. Its purpose is to keep on clicking the...
As the pandemic is going on with an increasing number of deaths daily, let create a simple model to predict the deaths caused by 2019-nCoV (Wuhan Coronavirus). The 2019-nCoV death data I grab the death toll data from World Meters website. DateDaily DeathsFeb. 889Feb. 786……Jan. 2416Jan. 238 Plot the data Firstly, we transform the table into a Pandas data frame. death_toll =...
Machines learn by means of a loss function which reflects how well a specific model performs with the given data. If predictions deviate too much from actual results, loss function would yield a very large value. Gradually, with function, parameters are modified accordingly to reduce the error in prediction. In this article, we will quickly review some common loss functions and their usage in the...
A.I, Data and Software Engineering