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Slides and jupyter notebook tutorial on Machine Learning and Data Science introduction.
devfest-19-gdg-settat's Introduction
Slides and jupyter notebook tutorial on Machine Learning and Data Science introduction.
- Objectives
- Machine Learning
- Types of Learning
- Supervised Learnojg
- Unsupervised Learning
- Reinforcment Learning
- Regression and Classification
- EDA: Exploratory Data Analysis
- Load Data
- Collect general information
- Data Visualisation
- Correlation Matirx
- More on EDA
- On to Modelling
- Split Data
- K-NN Algorithm
- Evaluating Model Performences
- Define Euclidian Distance
- 1NN with Euclidian Distance
- 3NN with Euclidian Distance
- General KNN with Different Distances
- Comparing with Sklearn
- Summary
- Where to Go Next?
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