Machine Learning models are great, they take input data used for a classification or regression task, learn from it, and when encountered by new data, they are able to give a prediction. There are several types of models that range in complexity, from a simple Linear Regression, which is used to estimate real values such as house prices, to a black box Neural Network model, which is used to solve complex tasks such as natural language understanding.

In this post, I will discuss how to achieve the same interpretability of a a simple Linear Regression model from a complex Tree…


As an Industrial Engineer graduate and as a person who currently works in manufacturing, I’ve been compelled to look for a different career path. After working for 4 years in an outdated manufacturing plant, I found myself stuck in the past, trying to optimize outdated machinery and processes which should have been upgraded long ago. A small sign of hope came when a new piece of machinery was purchased by the company’s owners, a fully automated machine filled with state of the art technology such as variable frequency drives, Allen-Bradley PLCs and HDMI, and sensors that can detect all sorts…


Lets say that you are interested in developing original video content and decided to create a new movie studio. The problem is, you don’t know anything about creating movies because you’ve been working as a data scientist your entire life. Fear not my friend, on this post, I will explain the steps required to web scrape movie data from the TMBD website using you data scientist skills so you can draw some insights to help you decide what type of films you should be creating.

What is Web Scraping?

Web Scraping is the extraction of data from a website, and…


Image taken from:https://thumbs.dreamstime.com/z/nlp-natural-language-processing-cognitive-computing-technology-concept-virtual-screen-natural-language-scince-concept-nlp-154696606.jpg

Deep natural language processing (Deep NLP) is a technique used to extract meaning and context from a body of text. That is made possible by using Word Embeddings, which are a type of vectorization strategy that computes word vectors from a body of text and uses those vectors to capture the semantic meaning of words.

In this post, I will create a model that can classify low quality and high quality wines based on their expert reviews and introduce how to implement Word Embeddings using Word2Vec and GloVe, as well as introducing LSTM, Double LSTM, GRU, and Bidirectional layers used…

Gabriel Jarosi

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store