Selva Prabhakaran

Selva is the Chief Author and Editor of Machine Learning Plus, with 4 Million+ readership. He has authored courses and books with100K+ students, and is the Principal Data Scientist of a global firm.

Train Test Split – How to split data into train and test for validating machine learning models?

The train-test split technique is a way of evaluating the performance of machine learning models. Whenever you build machine learning models, you will be training the model on a specific dataset (X and y). Once trained, you want to ensure the trained model is capable of performing well on the unseen test data as well. …

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What is a Data Scientist? – Roles, Responsibilities, Skillsets, Career Path and Salary

A Data scientist uses Data and AI to solve business problems, is skilled at working with data, extract meaningful insights, using ML to solve business problems, build applications that make predictions and recommendations, deploy and monitor the solutions. The perks of being a Data Scientist Data scientist is a relatively a new profession. By Data …

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Data Science Roadmap – How to become a Data Scientist? (6 month self study plan)

Today, I discuss the Data Science Roadmap, the missing guide to self study machine learning. I’ll discuss what exactly you need to know and do in order to self study Data science / ML / AI / Stats. I will provide you with some of the best resources for each topic, why you need to …

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Why learn the math behind Machine Learning and AI?

Why learn the math behind machine learning algorithms when you can readily implement it using the python libraries like scikit-learn, h2o, statsmodels etc? This is a fair question especially coming from beginners when it is easy to implement ML with few lines of code and get the results fast. Now, you must understand that learning …

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Mistakes programmers make when starting machine learning

Today, I want to discuss some of the common mistakes that programmers make when starting to learn machine learning. But first, let me speak about why software engineers should start looking into ML. First, let’s see why programmers should start ML? Today, from what I’ve seen, people coming with a strong software engineering background, good …

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Machine Learning Use Cases – The Big List of Real World Applications by Vertical and Industry

The use cases of machine learning to real world problems keeps growing as ML/AI sees increased adoption across industries. However, there are certain core use cases that add lot of value for organizations and you’ll often find them being implemented in banks, healthcare, manufacturing, product companies or by consulting organizations as well. Let’s tour of …

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Linear Regression in Machine Learning – Clearly Explained

    In this lesson, I introduce what Linear regression is all about. Linear Regression is a foundational algorithm for machine learning and statistical modeling. Traditionally, Linear Regression is the very first algorithm you’d learn when getting started with predictive modeling. While there are a lot more ML and Deep learning algorithm in use today, …

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Linear Regression in Machine Learning – Clearly Explained

Understanding linear regression. Let’s understand what linear regression is all about from a non-technical perspective, before we get into the details, we will first understand from a layman’s terms what linear regression is. Now, linear regression is a machine learning algorithm ml algorithm that uses data to predict a quantity of interest, typically, we call …

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Machine Learning A-Z™: Hands-On Python & R In Data Science

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Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science

Machine Learning A-Z™: Hands-On Python & R In Data Science