Here is a nice summary of traditional machine learning methods, from Mathworks. I also decided to add the following picture below, as it illustrates a method that was very popular 30 years ago but that seems to have been forgotten recently: mixture of Gaussian. In the example below, it is used to separate the data set… Read More »Machine Learning Summarized in One Picture

A personal account from Machine Learning enthusiast Avik Jain on his experiences of #100DaysOfMLCode, a challenge that encourages beginners to code and study machine learning for at least an hour, every day for 100 days.

Learning data science may seem intimidating but it doesn’t have to be that way. Let’s make learning data science fun and easy. So the challenge is how do we exactly make learning data science both…

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Machine learning is complex. For newbies, starting to learn machine learning can be painful if they don’t have right resources to learn from. Most of the machine learning libraries are difficult to…

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Scalable and efficient data pipelines are as important for the success of analytics and ML as reliable supply lines are for winning a war.

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The machine learning process involves a series of steps and activities designed to develop and deploy machine learning models to solve specific problems or make predictions. To simplify, we create programs that take in data and produce desired results in machine learning. There are several stages in the machine-learning process that we briefly describe in this post.

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Machine learning will drive unimagined solutions by augmenting human capabilities. In this article, we will discuss 14 of the most impactful current uses of machine learning.

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The terms Data Science, Machine Learning, and AI fall in the same domain and are connected to each other, they have their specific applications and meaning.