When to Use Machine Learning - Tips, Tricks and Warnings

Explore the world of machine learning through this insightful 39-minute conference talk from EuroPython 2018. Gain valuable tips, tricks, and warnings on when to effectively implement machine learning solutions. Discover the core concepts of artificial intelligence and learn how to critically evaluate proposed machine learning projects. Delve into real-world applications, including open-source Python projects and cryptocurrency trading, as the speaker shares challenges and findings from practical experiences. Understand decision trees, spam prediction, and the significance of machine learning in various domains such as image recognition, insurance, and academic data. Explore topics like transfer learning, neural networks, and data preprocessing while gaining insights into the practical implementation of machine learning using Python.

Intro
Who am I
Open source projects
Machine learning
Decision trees
Predicting spam
Bait logic
significance of machine learning
how I came to this idea
example data
main takeaway
another example
x2y problems
ImageNet
Insurance
Academic Data
Localisation
Transfer Learning
Image Data
Compliance
Neural Network
Cryptocurrency
Connecting to ML
Python for ML
X2Y
Reading the data
Bundle Preprocessing
In the end
Questions