Ever wondered what makes AI so smart? The secret lies in its training Data! This tutorial dives deep into the various methods used to collect data that trains AI models.
Understanding data collection is essential to appreciating how AI models learn and function.This tutorial explores various methods for gathering data to train AI, including:
Web Scraping: Automated data extraction from websites.
Crowdsourcing: Gathering contributions from platforms like Amazon Mechanical Turk.
Sensor Data: Collecting information from IoT devices, smartphones, and wearables.
Public Datasets: Utilizing data from governments, research institutions, and companies.
Synthetic Data Generation: Creating artificial data to supplement real-world data.
APIs: Accessing data through various online services.
User Interactions: Gathering data from user interactions with AI systems.
Surveys and Questionnaires: Collecting structured data directly from participants.
Social Media Mining: Extracting data from platforms like Twitter and Facebook
Database Integration: Combining data from various organizational databases.
Experimental methods, Environment interaction, Transfer learning etc.
We'll also discuss challenges such as data quality, privacy, and availability. Learn about privacy concerns, bias pitfalls, and ethical considerations that shape the future of AI development. This video also shares few important research paper on data collection.
Whether you're an AI Enthusiast or AI Wizard, this guide to smart data collection is a must-watch!
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