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1
Introduction
2
About Pivotal
3
About Andrew Aang
4
What is Machine Learning
5
Supervised Learning
6
Unsupervised Learning
7
Reinforcement Learning
8
Hello World Dataset
9
Visual Neural Net Server
10
Feedforward
11
BackPropagation
12
Measuring Error
13
Theta
14
Two Degrees of Freedom
15
Make Your Own Neural Networks
16
Deep Learning for J
17
Playground
18
Convolutional Networks
Description:
Explore the fundamentals of machine learning in this 50-minute conference talk from Spring I/O 2018 in Barcelona. Gain a gentle introduction to key concepts such as supervised learning, unsupervised learning, reinforcement learning, and deep learning. Discover the potential applications of machine learning and develop an intuition for the underlying mathematics. Starting from the basics, the talk builds up to more advanced techniques in an approachable manner, making it suitable for beginners and those looking to deepen their understanding. Learn about neural networks, backpropagation, error measurement, and convolutional networks through practical examples and visualizations. By the end of the session, acquire the knowledge to embark on your own machine learning projects and experiments.

Machine Learning Exposed - The Fundamentals

Spring I/O
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