Gabriele

Identifying the sARIMA model that fits our data consist of a series of steps, which we will perform on the AirPassenger dataset (available here).Each step roughly corresponds to a “page” of the Dash web app.2.1 Plot your dataCreate a line chart of your raw data: some of the features described above can be seen by the naked eye, especially stationarity, and seasonality.Raw line chart | Image by authorIn the above chart, we see a positive linear trend and a recurrent seasonality pattern; considering that we have monthly…

A step-by-step guide to performing a customer churn analysis, using a simulated datasetPhoto by JESHOOTS.COM on Unsplash“Churn” has become a common business word that refers to the concept of churn rate, defined by Wikipedia as the:“proportion of contractual customers or subscribers who leave a supplier during a given time period”When analyzing churn from a data perspective, we usually mean to use the available tools to extract information about the existing customer base, specifically: quantify the current churn rate and…

A guided approach to assign new songs to Spotify playlists, using word2vec and logistic regressionPhoto by israel palacio on UnsplashThis article will present a NLP project aimed at assigning songs to playlists.Two playlists have been selected from Spotify and, via the Spotify API, information such as: artist, song titles, popularity, etc. was downloaded. The song lyrics data, not available through the API, was obtained using webscraping.Next, some data pre-processing steps were performed on the raw lyrics in order to…

Assortativity helps analysing pattern of connections in networks. Let’s use it to confirm if people tend to connect to similar people.Photo by fabio on UnsplashIn this article we will use some Facebook data to explore the concept of network assortativity (also called as homophily), which we define as the tendency of nodes to connect to their similar.Networks or Graphs are data representation consisting in nodes (vertices) and edges (links): in this article we will consider only undirected and unweighted edges. We will…

Testing the ability of Dall-E to deal with abstract topics“A painting representing emotions”. Image by the author, created with DALL-E.Text-to-image generation is one of the hottest topics in the AI world. It has recently delivered groundbreaking advancements that are defying what was thought to be possible only a couple of years ago. DALL-E 2, Imagen, and Parti have recently shown incredible capabilities in generating high-quality images with good fidelity to the input text prompt. While Google has not yet released its…

A few words on the hottest models in the fieldPhoto by Wim van 't Einde on UnsplashMachine Learning is a notoriously intricate field practised by academics and industries alike, constantly improving on its benchmarks and spawning interesting ideas and problem-solving approaches.It has been deployed successfully in countless practical applications in many different fields before even a proper theory has been developed explaining why it works.For this reason, it can sometimes be a bit hard to keep up with the latest…

Building blocks for state-of-the-art modelsPhoto by Mourizal Zativa on UnsplashWhen talking about Time Series, people often tend to do it in a very practical data-oriented way: if you try and look up some definition, you may find expressions such as “a series of data points indexed (or listed or graphed) in time order” (Wikipedia), “a set of data collected at successive points in time or over successive periods of time” (Encyclopædia Britannica), “a sequence of data points that occur in successive order over some period…