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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

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How to become a data scientist

Dataconomy

Machine learning Machine learning is a key part of data science. It involves developing algorithms that can learn from and make predictions or decisions based on data. Familiarity with regression techniques, decision trees, clustering, neural networks, and other data-driven problem-solving methods is vital.

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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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GIS Machine Learning With R-An Overview.

Towards AI

We shall look at various types of machine learning algorithms such as decision trees, random forest, K nearest neighbor, and naïve Bayes and how you can call their libraries in R studios, including executing the code. Decision Tree and R. R Studios and GIS In a previous article, I wrote about GIS and R.,

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

IBM Journey to AI blog

Supervised learning Supervised learning techniques use real-world input and output data to detect anomalies. These types of anomaly detection systems require a data analyst to label data points as either normal or abnormal to be used as training data.

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Exploring 5 Statistical Data Analysis Techniques with Real-World Examples

Pickl AI

Decision Trees Decision trees are a versatile statistical modelling technique used for decision-making in various industries. In marketing, a decision tree can help determine the most effective advertising channels based on customer demographics, improving campaign targeting and ROI.

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Data Analysis vs. Data Visualization – More Than Just Pretty Charts

Pickl AI

to understand the data’s main characteristics, distributions, and relationships. Modeling & Algorithms: Applying statistical models (like regression, classification, clustering) or Machine Learning algorithms to identify deeper patterns, make predictions, or classify data points. This helps formulate hypotheses.