Pickl AI

APRIL 3, 2025

Objective Evaluation: Allows for the assessment of performance, the effectiveness of interventions, or the testing of hypotheses. Key Processes and Techniques in Data Analysis Data Collection: Gathering raw data from various sources (databases, APIs, surveys, sensors, etc.). Recommends actions to achieve desired outcomes (e.g.,

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

Pickl AI

SEPTEMBER 12, 2024

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.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

MAY 30, 2024

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.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Pickl AI

AUGUST 9, 2024

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.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

NOVEMBER 28, 2024

Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. Decision Trees These trees split data into branches based on feature values, providing clear decision rules.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

JULY 23, 2023

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.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

Mlearning.ai

MAY 23, 2023

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.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52