90 Data Engineering for Data Scientists
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Summary: It is always good for a data scientist to understand more about data engineering, especially the blueprint of a fully productionized data platform.
Pages: 4
22 Machine Learning with Graph
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Summary: Using Graph representations and graph theories to learn
Pages: 4
21 Monte Carlo
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Summary: Monte Carlo method is a fantastic numerical integration method
Pages: 1
19 Model Selection
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Summary: A good model selection process selects a good model for us. What is a good model? How do we quantify it?
Pages: 5
19 Forecasting
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Summary: Forecasting is a widely used technique in both industry and science
Pages: 7
18 Tools
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Summary: Notes for Tools of Data Science: Git, Command Line, Notebook, AWS etc
Pages: 9
13 Statistical Hypothesis Testing
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Summary: Hypothesis testing in statistics
Pages: 5
8 Machine Learning
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Summary: To make machine learning and understand machine learning
Pages: 53
5 Data Warehouse
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Summary: Take care of your data and your data will show you its power.
Pages: 4