Tag

data science

Essential Tools for Deep Learning and Data Science

Learn the most important tools in the repertoire of a data scientist and machine learning practitioner – Principal Component Analysis (PCA), Singular Value Decomposition (SVD), and Latent Semantic Analysis (LSA) – with the help of Krishnendu Chaudhury.

NLP Analysis of Large Text Datasets: conducted by Dr. Leonard Apeltsin

In this video, Dr. Leonard Apelstin demonstrates xClustering Large Text Datasets in Python.

The Practical Guide to Data Leadership

From Become a Leader in Data Science by Jike Chong and Yue Cathy Chang

Achieving Loose Coupling

From Practices of the Python Pro by Dane Hillard

This article covers

•  Recognizing the signs of tightly coupled code

•  Strategies for reducing coupling

Flexible and Scalable Data Analysis

From PySpark in Action by Jonathan Rioux

What Makes Code Extensible and Flexible?

From Practices of the Python Pro by Dane Hillard

This article covers

  • Using inversion of control to make code flexible
  • Using interfaces to make code extensible
  • Adding new features to your existing code

Improve Your Data Science Skills

From Data Science Bookcamp by Leonard Apeltsin

Namespacing with Python

From Practices of the Python Pro by Dane Hillard

The article explores the concept of namespaces and how Python uses them to help make code better.

Zero to AI

From Zero to AI by Nicolo Valigi and Gianluca Mauro

Data Science and Bucatini all’Amatriciana

Six Questions for Jesse C. Daniel, author of Data Science with Python and Dask

Jesse Daniel is a software developer (Python, Scala, JavaScript, C#) who leads a team of data scientists at a media technology company. He has taught Python for Data Science at the University of Denver.

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