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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Key Components of Data Science Data Science consists of several key components that work together to extract meaningful insights from data: Data Collection: This involves gathering relevant data from various sources, such as databases, APIs, and web scraping. Data Cleaning: Raw data often contains errors, inconsistencies, and missing values.

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Big Data Syllabus: A Comprehensive Overview

Pickl AI

Businesses need to analyse data as it streams in to make timely decisions. Variety It encompasses the different types of data, including structured data (like databases), semi-structured data (like XML), and unstructured formats (such as text, images, and videos). This diversity requires flexible data processing and storage solutions.

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Understanding Data Science and Data Analysis Life Cycle

Pickl AI

It systematically collects data from diverse sources such as databases, online repositories, sensors, and other digital platforms, ensuring a comprehensive dataset is available for subsequent analysis and insights extraction. These include databases, APIs, web scraping, and public datasets.

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Data Demystified: What Exactly is Data?- 4 Types of Analytics

Pickl AI

Datasets are typically formatted and stored in files, databases, or spreadsheets, allowing for easy access and analysis. Examples of datasets include a spreadsheet containing information about customer demographics, a database of medical records, or a collection of images for training an AI model. Types of Data 1. Key Features: i.

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[Updated] 100+ Top Data Science Interview Questions

Mlearning.ai

Decision trees are more prone to overfitting. Underfitting: Here, the model is so simple that it is not able to identify the correct relationship in the data, and hence it does not perform well even on the test data. Some algorithms that have low bias are Decision Trees, SVM, etc. character) is underlined or not.

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Top 50+ Data Analyst Interview Questions & Answers

Pickl AI

SQL stands for Structured Query Language, essential for querying and manipulating data stored in relational databases. The SELECT statement retrieves data from a database, while SELECT DISTINCT eliminates duplicate rows from the result set. What are the advantages and disadvantages of decision trees ?