Tips and techniques to decide whether it is time to retrain our model — Training a model is a complex process requiring much effort and analysis. Once a model is ready, we know that it won’t be valid forever and that we’ll need to train it again. How can we decide if a model needs to be retrained? …

A brief overview about models that need pre-processed data — Data pre-processing is an important part of every machine learning project. A very useful transformation to be applied to data is normalization. Some models require it as mandatory to work properly. Let’s see some of them. What is normalization? Normalization is a general term related to the scaling of the variables. Scaling transforms…

A brief overview of some interpretable machine learning models — Model explanation is an essential task in supervised machine learning. Explaining how a model can represent the information is crucial to understanding the dynamics that rule our data. Let’s see some models that are easy to interpret. Why do we need to interpret our models? Data Scientists have the role to extract information from raw data. They aren’t…

A simple guide on how to use statistics to run A/B tests on proportions — Online marketing and startup growth are better if you can continuously test different ideas. The statistic comes into help when we have to perform A/B tests. The results you may achieve with the proper analysis can give your project a great boost. What is an A/B test? Companies often need to compare the results of…

A short guide on how to create comparable training and test datasets — Data scientists usually split a dataset into training and test sets. Their model is trained on the former and then its performance is checked in the latter. But, if these sets are sampled wrongly, model performance may be affected by biases. Should training and test sets be similar? From the beginning of my career, everybody used to…

How to create Node.js or client-side models that aren’t too CPU-expensive—while still making the most of Python’s libraries — Models are very powerful tools to be used in several web applications. The general approach is to make them accessible by using REST APIs. In this article, I’ll talk about a model that can be created in Python and then deployed in pure Javascript. Why Javascript? Machine learning models are often created…

Some advantages of remote work — Remote work is not just a simple idea you can implement into your business with no effort and start making more profit. It is an opportunity that, when brought to life, will allow you to benefit from a number of advantages that you never thought possible. In the following article…

How to visualize the predictive power of a numerical feature — Measuring the predictive power of some feature in a supervised machine learning problem is always a hard task to accomplish. Before using any correlation metrics, it’s important to visualize whether a feature is informative or not. In this article, we’re going to apply data visualization to a classification problem. How does a numerical feature affect a categorical target?

An overview of the two most used tools for remote working — Work from home jobs always has an edge to them when it comes to team meetings and group chats. Because unlike office environment you are unable to communicate with your co-workers in random sittings like moving in an elevator together, over a coffee break, etc. In remote work, the success…