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Top 17 trending interview questions for AI Scientists

Data Science Dojo

Let’s dig into some of the most asked interview questions from AI Scientists with best possible answers Core AI Concepts Explain the difference between supervised, unsupervised, and reinforcement learning. The model learns to map input features to output labels.

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Journey to AI blog

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements. But what is an anomaly and why is detecting it important?

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Are AI technologies ready for the real world?

Dataconomy

AI practitioners choose an appropriate machine learning model or algorithm that aligns with the problem at hand. Common choices include neural networks (used in deep learning), decision trees, support vector machines, and more. With the model selected, the initialization of parameters takes place.

AI 136
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Discover the Role of Entropy in Machine Learning

Pickl AI

Summary: Entropy in Machine Learning quantifies uncertainty, driving better decision-making in algorithms. It optimises decision trees, probabilistic models, clustering, and reinforcement learning. log2P(xi) measures the information content of each event in bits.

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Scikit-Learn For Machine Learning Application Development In Python

Smart Data Collective

There are two essential classifiers for developing machine learning applications with this library: a supervised learning model known as an SVM and a Random Forest (RF). There are numerous reasons that scikit-learn is one of the preferred libraries for developing machine learning solutions.

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Regression in Machine Learning: Types & Examples

Pickl AI

Machine Learning has become a fundamental part of people’s lives and it typically holds two segments. It includes supervised and unsupervised learning. Supervised Learning deals with labels data and unsupervised learning deals with unlabelled data. It is commonly used in medical research.

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Exploring the dynamic fusion of AI and the IoT

Dataconomy

Real-time decision-making With AI, IoT devices can make decisions in real-time based on the data they collect and analyze. This enables them to respond quickly to changing conditions or events.