Important dates in history of Machine Learning
Discover the groundbreaking machine learning models that changed the game: from the classic Perceptron to the mind-blowing GPT-3, these models have reshaped AI and taken technology to new heights. Dive into the history of ML innovation:
1957 — Perceptron:
The perceptron, developed by Frank Rosenblatt, is one of the earliest neural network models. It laid the foundation for artificial neural networks and supervised learning, influencing future advancements in deep learning.
1960s — Decision Trees:
Decision trees, introduced by several researchers in the 1960s and popularized by Breiman et al. in the 1980s, are fundamental for classification and regression tasks. They are interpretable and form the basis for more complex tree-based models like Random Forests and Gradient Boosting.
1960s-1970s — Hidden Markov Models (HMM):
HMMs are probabilistic models widely used in speech recognition, natural language processing, and bioinformatics. They model sequential data and have been instrumental in developing applications like speech-to-text and gene prediction.