Machine learning Interview Questions (Part-4)

This is one among the series of frequently asked interview questions in machine learning. Concepts are demonstrated with schematics wherever necessary Differentiate between local optimization and global optimization Optimization is a process of assigning a set of inputs to an objective function that can extract the best possible output from the objective function. Local optimization

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Machine Learning Interview Questions (Part- 3)

The article discusses interview questions asked in many machine learning job roles Explain label encoding and one hot encoding, Explain how the dimensionality of a dataset is affected with these methods in machine learning Machine learning algorithms can understand only numbers. Often, the dataset consists of categorical and numerical features. We need to convert the

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Summary of the book “The Five Elements of Effective Thinking”

In this blog post, I am going to summarize the key ideas from the book titled “The Five Elements of Effective Thinking” written by Edward Burger and Michael Starbird along with my thoughts on the topic. The preface starts with arguing that thinking is the skill which forms all other skills like decision making, creativity,

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Machine Learning Interview Questions (Part- 2)

This article is one among the series of discussions on interview questions frequently asked in machine learning job roles Explain the concept confusion matrix in machine learning? Confusion matrix is a table displaying a summary of prediction results of a classification problem. Measuring accuracy of a model alone can be misleading in cases where the

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Machine Learning Interview Questions (Part- 1)

This is one among a series of frequently asked interview questions in machine learning published in this website Explain the terms Artificial Intelligence, Machine Learning, Deep Learning, and Reinforcement Learning? Artificial Intelligence (AI) is the domain of intelligent machines which can think rationally and act rationally. It uses algorithms to enable problem solving with robust

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