A Gentle Introduction to Data Science

Explore the fundamentals of data science in this EuroPython 2017 conference talk. Delve into the influence of artificial intelligence and the quest to replicate the human mind. Discover how artificial intelligence draws inspiration from our understanding of the human brain, including visual perception, neuron synapses, and the Hebel and Torsten cat experiment. Learn about key concepts such as Hebbian theory, McCulloch Pitts neurons, and various types of neural networks. Understand essential machine learning principles like loss functions, stochastic gradient descent, and backpropagation. Examine practical applications of data science in classification, regression, robotics, recommender systems, clustering, network analysis, image recognition, and self-driving cars. Conclude with a hands-on demonstration of building a "hello world" machine learning model using Python, providing a solid foundation for those new to the field of data science.

Intro
About me
Visual perception example
Neuron synapse
Hubel and Torsten cat experiment
Hebbian theory
McCulloch Pitts neuron
Activate function
Hopfield networks
Boltzman machines
Restricted Boltaman machines
Deep belief networks
Loss function
Stochastic gradient descent
Backpropagation
Internal representation of the world
Classification
Regression
Robotics
Recommender systems
Clustering
Network analysis
Image recognition
Self driving cars
Projects
Questions?