Contributors: F M Nurul Huda Pathan, Soumya Ranjan Mishra

This article aims to make you understand the System Design of the Uber application. We hope you will enjoy the blog. Let’s Start!

Uber is an American technology company that provides ride-hailing, food delivery (Uber Eats), package delivery, couriers, freight transportation…

Let’s first talk about time series before discussing about the different aspects of feature engineering in time series.

Time Series refers to a series of data points indexed in time order. In other words, a time series is a sequence taken at successive equally spaced points in time. …

For any machine learning model we built, we need to validate the stability of our model. We may face a situation in deciding the right choices about predictive variables to use, what types of models to use, what arguments to supply those models, etc. We make these choices in a…

With the advancement of AI, many challenging tasks can be accomplished with the help of technology in a short span of time. People who speak different languages can text each other using translation apps like Google Translator. There are many apps which can recognize human voice and performs a particular…

When we talk about unsupervised machine learning algorithms, we have an intuition that the machine learning model will be fed with unlabeled data to predict the underlying patterns in the data. Clustering is one of the important unsupervised machine learning algorithm.

Now, let’s discuss in detail how clustering works. Suppose…

When we talk about supervised machine learning, Linear regression is the most basic algorithm every one learns in data science. Let’s try to understand the term Regression.

Regression is a technique from statistics that is used to predict values of a desired target quantity when the target quantity is continuous…

We might have heard that some product companies claim that their product is 95% efficient in controlling a particular disease or an unwanted a phenomenon. For example, a company claims that, its product X kills 99.9% of germs. So how can they say so? …

Having a great knowledge on Calculus, Linear Algebra, Probability Theory and Statistics is an essential trait every great data scientists posses. A solid understanding on these topics will eventually help an aspiring data scientist a lot in learning Machine Learning models. It will give them an edge among their peers.

F M Nurul Huda Pathan

Aspiring Data Scientist

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