Python for Machine Learning
Python for Data Visualization
Libraries |
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Matplotlib |
Seaborn |
ggplot |
GraphX |
Plotly |
Functions |
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Exploratory data analysis |
Data storytelling |
Decision-support dashboard design |
Public education(news, media, and data blogging) |
Python for Machine Learning
Libraries |
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scikit-learn |
Tensor Flow |
PyTorch |
Functions (By Use Case) |
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Regression |
Clustering |
Dimension reduction |
Association rules |
Deep learning |
Instance-based |
Decision trees |
Bayesian |
Ensemble |
Regularization |
Python for Data Engineering
Functions
- Learn to build simple MapReduce jobs (sans Java)
- Write Spark jobs(sans Scala)
- Programming IoT device(Raspberry Pi)
- Building ETL processes(Airflow)
Types of Machine Learning Methods
Supervised Learning | Making predictions straight from labeled data |
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Unsupervised Learning | Making predictions straight from unlabeled data |
Semi-Supervised Learning | Uses both labeled and unlabeled data to make a set of predictions |
Popular Ways to Group ML Algorithms
By Learning | By Function | By Use Case |
---|---|---|
Supervised | Regression | Fraud detection |
Unsupervised | Clustering | Recommendation engines |
Semi-supervised | Dimension reduction | Price forecasting |
Association rules | Inventory demand forecasting | |
Deep learning | Water consumption forecasting | |
Instance-based | Infrastructure demand forecasting | |
Decision trees | And so on | |
Bayesian | ||
Ensemble | ||
Regularization |