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There are thousands of online courses which teach you how to build and train a machine learning model or deep neural network, many of these tutorials end with you just training and building the model alone. This, however, ends you having a model file on your local computer, which isn’t the end of the story: the model needs to be deployed in order to be used by the clients or end-users.

As a Web developer and data scientist, I have a desire to build web apps to showcase my work. As much as I like to design the front-end, it…

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A big part of machine learning is classification — we want to know what class or group an observation belongs to. The ability to precisely classify observations is extremely valuable for various business applications like predicting whether a particular user will buy a product or forecasting whether a given loan will default or not.

Data science provides a plethora of classification algorithms such as logistic regression, support vector machine, naive Bayes classifier, and decision trees. But near the top of the classifier hierarchy is the random forest classifier.

In this post, we will examine how Random Forests algorithm works, and…

Photo by 🇨🇭 Claudio Schwarz | @purzlbaum on Unsplash

What is Sentiment Analysis?

A process of computationally identifying and categorizing emotions and opinions expressed in a piece of text, especially in order to determine whether the writer’s attitude towards a particular topic, product, etc. is positive, negative, or neutral. In layman’s terms, we can think of sentiment analysis as using machines to interpret the underlying meaning of a body of the text.

Some of the real-world applications of sentiment analysis are Social Media monitoring (how are people reacting to certain things on social media), Marketing (if people are liking your product or not by analysing product reviews), Political analysis (which politician is more…

Emmanuel Oludare

Full stack web developer and experience machine learning engineer.

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