🤖 AI Basics Index
This index provides an overview of key topics in Artificial Intelligence (AI). Explore the sections below to learn about the origins, core components, popular tools, essential terminologies, and algorithms that power modern AI systems.
1. Basics of AI
A brief overview of what AI is, its purpose, and the primary concepts that drive its development.
2. Introduction to AI
History & Origins:
- Founders: Key figures and pioneers in AI research.
- Timeline: When the research started and major milestones in the field.
- Market Leaders: Companies and institutions that have shaped and led AI innovation.
3. Basic Core Components of AI
An exploration of the fundamental building blocks in AI, including:
- LLM (Large Language Models): Models designed to understand and generate human-like text.
- Transformer Architecture: The breakthrough model architecture behind many state-of-the-art AI systems.
- Encoder-Decoder Models: Frameworks that translate or generate sequences in tasks such as language translation.
4. Popular AI Tools
A list of widely used AI tools and platforms in the industry:
- TensorFlow
- PyTorch
- scikit-learn
- OpenAI GPT Series
- Hugging Face Transformers
5. Basic Terminologies
Understand the common terms and language used in AI discussions:
- Neural Networks
- Deep Learning
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
6. Algorithms in AI
Explore some of the key algorithms that drive AI processes:
- Linear Regression
- Logistic Regression
- Decision Trees
- Neural Network Algorithms
- Clustering Algorithms (e.g., K-Means)
Each section can be expanded into detailed guides and tutorials to further explore these topics.