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1
Intro
2
Building blocks of ML pipelines
3
Predicting arm movements
4
Preprocessing
5
Prediction
6
Raw data
7
Neural network
8
Network structure
9
Example
10
Wrapup
11
Questions
Description:
Explore how machine learning is revolutionizing research in this 30-minute EuroPython Conference talk. Discover the impact of ML on daily life and its growing role as a powerful research tool. Learn about Python libraries like keras and scikit-learn that have simplified ML implementation across various fields. Examine real-world applications, including automatic neuron recognition in histological images and predicting arm movements from EEG signals. Gain insights into Python-based techniques for data preparation and analysis, covering standard ML methods and cutting-edge deep neural network implementations. Follow the talk's structure from introduction to building ML pipelines, preprocessing, prediction, and network structures, concluding with a wrap-up and Q&A session.

Boosting Research with Machine Learning

EuroPython Conference
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