Data Science Content

• Machine Learning
  • Pyspark Content
  • Style Guides
  • Reinforcement Learning
  • Principal Component Analysis (PCA)
  • Deep Learning
  • Data Engineering Resources
  • NLP
  • Docker
    • Github Roadmaps
  • APIs
  • Startups
  • Content
  • Explainable Machine Learning
  • Mapping with Python
  • Organization
  • Economics and Data Science
• Statistics

Machine Learning

Pyspark Content

• Pyspark Style Guide

• Spark Joins

Style Guides

• Python Style Guide

Reinforcement Learning

• Reinforcement Learning Project

Principal Component Analysis (PCA)

Principal Component Analysis (PCA) with Scikit-learn

Deep Learning

https://www.fast.ai/ https://udemy.com/course/deeplearning/ https://udemy.com/course/complete-tensorflow-2-and-keras-deep-learning-bootcamp https://github.com/jeffheaton/t81_558_deep_learning

Data Engineering Resources

• Data Engineering Resources

NLP

• BERT
  • Using BERT for Unlabeled Data

Docker

• Using Docker for Data Science

Github Roadmaps

• VS Code Roadmap

APIs

• News API

Startups

• Startup Financial Modeling

Content

Explainable Machine Learning

• LIME explanations for classification results

Mapping with Python

• Hex Maps for Spatial Data

• Choropleth using the Plot.ly

Organization

Organizing Folders with Python

Economics and Data Science

An Economist’s Value in Data Science Covers Econometrics. Economists ‘have a unique set of skills that allows them to apply statistics in a very similar fashion to data scientists, while also being able to evaluate bias, externalities, and comprehend the math behind algorithms. Additionally, their experience analyzing businesses provide an ability to question and discuss the value of models relative to business goals.’

Statistics