Artificial Intelligence Full Course | Artificial Intelligence Tutorial for Beginners | Edureka
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Introduction
Welcome to the comprehensive satellite session on Artificial Intelligence! This tutorial is designed to take you through the journey of AI, explaining its concepts and providing practical implementations using Python.
Table of Contents
- Introduction to Artificial Intelligence
- History of Artificial Intelligence
- Why Artificial Intelligence Now?
- What is Artificial Intelligence?
- Applications of Artificial Intelligence
- Basics of AI
- Programming Languages for AI
- Machine Learning
- Deep Learning
- Natural Language Processing
- Conclusion
Introduction to Artificial Intelligence
In this course, we will cover the fundamental domains and concepts within the realm of Artificial Intelligence (AI). Expect a thorough examination of the history, usage, and potential of AI, as well as hands-on demonstrations of AI applications utilizing Python.
History of Artificial Intelligence
AI has its roots dating back to classical ideas in Greek mythology. The term "Artificial Intelligence" was coined in 1956 at the Dartmouth Conference, marking the first official acknowledgment of AI as a field. Progress in AI has since been recorded through significant milestones, such as Alan Turing's development of the Turing Test and the introduction of learning algorithms.
Why Artificial Intelligence Now?
AI has recently gained prominence due to advancements in computational power, huge data availability, effective algorithms, and substantial investments from universities and tech giants like Google, Amazon, and Microsoft.
What is Artificial Intelligence?
According to John McCarthy, AI is defined as the science and engineering of creating intelligent machines capable of performing tasks that usually require human intelligence, including perception, reasoning, and decision-making.
Applications of Artificial Intelligence
- Google Predictive Search: Google’s suggestions during searches utilize AI for quick completion.
- Document Analysis in Finance: J.P. Morgan uses machine learning for analyzing legal documents.
- Healthcare: IBM Watson has aided diagnoses using data from oncology records.
- Social Media: Facebook recognizes friends’ faces using AI.
- Virtual Assistants: Siri and Alexa utilize AI to respond to inquiries and perform tasks.
Basics of AI
AI can be categorized into three forms:
- Artificial Narrow Intelligence (ANI): AI focused on specific tasks.
- Artificial General Intelligence (AGI): AI that can perform any intelligent task that a human can.
- Artificial Superintelligence (ASI): AI that surpasses human intelligence.
Programming Languages for AI
Python is the most preferred programming language for AI due to its simplicity, extensive libraries, and community support. Other languages include R, Java, Lisp, Prolog, and C++.
Machine Learning
Machine learning is a subset of AI that provides systems the ability to automatically learn and improve from experience without explicit programming. Major types include supervised learning, unsupervised learning, and reinforcement learning, each serving different algorithmic purposes.
Supervised Learning
Involves learning from labeled training data.
Unsupervised Learning
Involves drawing inferences from unlabeled data and identifying hidden patterns.
Reinforcement Learning
Involves agents that learn optimal actions through trial and error, maximizing cumulative rewards.
Deep Learning
Deep learning is a more advanced subset of machine learning using artificial neural networks, allowing for complex functions to be modeled. It has shown significant success in fields like image and speech recognition.
Natural Language Processing
Natural Language Processing (NLP) is a field that allows computers to understand, interpret, and manipulate human language. Techniques include tokenization, stemming, lemmatization, and sentiment analysis, making it pivotal for applications like chatbots and language translation.
Conclusion
Artificial intelligence encompasses a broad scope of techniques and technologies with far-reaching applications today. Whether through programming in Python or leveraging deep learning models, AI is proving to be a transformative force in technology and business.
Keywords
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Natural Language Processing
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Tokenization
- Sentiment Analysis
- Neural Networks
FAQ
What is Artificial Intelligence? AI is the simulation of human intelligence processes by machines, especially computer systems.
How does Machine Learning relate to AI? Machine Learning is a subset of AI focused on the development of algorithms that enable machines to learn from and make predictions based on data.
What is Deep Learning? Deep Learning is a subset of Machine Learning that uses neural networks with multiple layers to analyze various factors of data.
What programming languages are needed for AI? Python is widely used for AI development, but R, Java, and C++ are also popular options.
What are the main applications of AI? Applications range from predictive search engines, document analysis, virtual assistants, healthcare diagnostics, and social media processing.