Data Science
Data Scientists
Data Scientists can be experts in multiple disciplines:
- Applied mathematics
- Computational statistics
- Computer Science
- Machine learning
- Deep learning
Data Scientists also have significant big data experience:
- Business Intelligence
- Data Base Design
- Data Warehouse Design
- Data Mining
- SQL Queries
- SQL Reporting
Artificial Intelligence is a scientific discipline embracing several Data Science fields ranging from narrow AI to strong AI, including machine learning, deep learning, big data and data mining.
The Deep Learning Revolution
The deep learning revolution is here!
The deep learning revolution started around 2010. Since then, Deep Learning has been used to solve many "unsolvable" problems.
Examples
Convolutional Neural Networks (CNNs)
Deep CNNs such as ResNeta and Inception have reduced the error rate in the ImageNet classification from 25% in 2011 to 5% in 2017.
ImageNet is an image database organized according to the WordNet hierarchy, in which each node of the hierarchy contains hundreds and thousands of images. ImageNet is a useful resource for researchers, educators, students and everyone else with a passion for pictures.
WordNet is a lexical database of semantic relations between words in 200+ languages. It is organized as a combination of a dictionary and thesaurus, linking words together into semantic relations using synonyms, hyponyms, and meronyms.
Recurrent Neural Networks (RNNs)
RNNs are helping create music scores and novel instrument sounds:
https://magenta.tensorflow.org/demos.
