The DataVolt Project, Diffusion Models Course, Feature Selection in Machine Learning

This week's agenda:

• Open Source of the Week - The DataVolt project
• New learning resources - Diffusion Models full course, forecasting with LSTM, FastAPI course
• Book of the week - Feature Selection in Machine Learning by Soledad Galli

Daily updates on Telegram, WhatsApp, or Viber.

VScode Extensions

During the past few weeks, I shared a weekend edition with VScode extension recommendations by theme every Saturday. From extensions for working with Git to extensions for code generation with AI. Here are the links for those editions:

• Five VScode Extensions for Git
• Five VScode Utility Extensions
• Five VScode Extensions for Working with Data
• Five VScode Extensions for Working with Python
• Five VScode Extensions for Working with Containers
• Five VScode Extensions for AI Applications

Open Source of the Week

This week's focus is on a new open-source project, DataVolt by Allan Wandia . The DataVolt is a Python library that provides a set of tools for building and maintaining data engineering pipelines.

The library has the following core functionality:

• Pipeline standardization - unified interfaces for ETL operation
• Workflow automation - automated orchestration and preprocessing capabilities
• Integration - supports cloud storage, SQL databases, and machine learning frameworks

Installation:

pip install datavolt        

In addition, the library tracks the pipeline performance and provides a data visualization of key performance metrics. For example, the below screenshot provides a visual representation of the data load from a CSV file:

License: MIT

New Learning Resources

Here are some new learning resources that I came across this week.

Diffusion Models and their Applications

The Diffusion Models and their Applications course from Korea Advanced Institute of Science & Technology provides an introduction to diffusion models.

Forecasting with LSTM

The following tutorial by Code with Josh, provides an introduction to time series forecasting with LSTM models using Python and Tensorflow.

Fast API Course

This one-hour tutorial by NeuralNine provides an introduction to FastAPI, one of Python main framework to build an API system.

Book of the Week

This week focuses on a new ML book - Feature Selection in Machine Learning (2nd edition), by Soledad Galli . The book, as its name implies, focuses on feature selection methods, which, in my opinion, is one of the foundations of data science. The book provides an introduction to the topic and dives into different feature selection methods, such as:

• Features visualization
• Correlation analysis
• Statistical methods such as ANOVA and Chi-square
• Regularization methods such as Lasso regression
• Tree-based feature selection
• Recursive methods

The book currently has only a PDF version, and it is available for purchase on the following website:

Have any questions? Please comment below!

See you next Tuesday!

Thanks,

Rami