A.I, Data and Software Engineering

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Metrics for regression and classification – quick note

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...

Predict coronavirus deaths by days

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. 123 death_toll =...

Common Loss functions and their uses – quick note

losses

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 \(optimization\) function, parameters are modified accordingly to reduce the error in prediction. In this article, we will quickly review some common loss functions and...

Generate data on the fly – Keras data generator

keras data generator

Previously, we train our model using the pre-generated dataset, for example, in the recommender system or recurrent neural network. In this article, we will demonstrate using a generator to produce data on the fly for training a model. Keras Data Generator with Sequence There are a couple of ways to create a data generator. However, Tensorflow Keras provides a base class to fit dataset as a...

One-hot encoding matrices demonstration

movie lens automation

This post will demonstrate onehot encoding for a rating matrix, such as movie lens dataset. One-hot encoding Previously, we introduced a quick note for one-hot encoding. It is a representation of categorical variables as binary vectors. It is a group of bits among which the legal combinations of values are only those with a single high (1) bit and all the others low (0) Rating matrix If you are...

A.I, Data and Software Engineering

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