Open your calendar, NumPy 2.0 is going to be out on June 16th 🚀
This is the first major release since 2006. The release includes breaking changes in the library API, and therefore, if you are planing to adopt it, some code refactoring may required.
The release includes new features, performance improvement 🏎️, improvements on the C API, and more.
(1/2) Shiny Apps for demystifying statistical models and methods 🚀
This is a cool website that explains different statistical concepts with the use of interactive Shiny Apps. Ben Prytherch made this website from the Department of Statistics at Colorado State University.
Some of the folks who signed up for my #StickersAndStamps project finally got an email from me, thanking them for letting me know when their letters arrived.
Most of them arrived on, or near, the the day I had my surgery.
My recovery is still going well, and I finally had the mental and physical energy for the correspondence.
I'll be returning to working on the data visualization and art of the project soon!
Building robust data pipelines with dbt, Airflow, and Great Expectations 🚀
I started to dive into great expectations - a Python library for data quality checks, and I found this great talk by Sam Bail about building data pipelines with dbt, Airflow, and great expectations.
The Machine Learning for Beginners by Microsoft Developer is an introductory course for classical machine learning. This crash course mainly focuses on regression analysis with Python 🐍, and it covers topics such as:
✅ General setup
✅ Cleaning data
✅ Data visualization
✅ Regression models
✅ Polynomial regression
✅ Logistic regression
Here is a short e-book with a sequence of tutorials on the scientific Python ecosystem for beginners. This includes topics such as:
✅ Working with numerical data using NumPy
✅ Data visualization with Matplotlib
✅ Scientific computing with SciPy
✅ Statistics with Python
✅ Machine learning with scikit-learn
(1/4) TIL about the plotnine library- the grammar of graphics in Python 🚀
I had never heard about the Plotnine library until I came across the Posit Plotnine contest (see the link below). The plotnine is a Python implementation of a grammar of graphics based on the ggplot2 library.
Learn how to handle rows in R containing specific strings using base R's grep() and dplyr's filter() with str_detect(). Select or drop rows efficiently and enhance your data manipulation skills. Give it a try with your datasets for better data cleaning and organization.
College Precalculus – Full Course with Python Code by Ed Pratowski and freeCodeCamp focus on the foundation of calculus with Python implementation. This 12 hours course covers the following topics:
✅ Core trigonometry
✅ Matrix operation
✅ Working with complex numbers
✅ Probability
FreeCodeCamp released today a new course for fine tuning LLM models. The course, by Krish Naik, focuses on different tuning methods such as QLORA, LORA, and Quantization using different models such as Llama2, Gradient, and Google Gemma model.
Here is a great resource for getting started with Observable Framework by Allison Horst. Observable Framework is an open-source JS library for creating dashboards. The sequence of videos covers how to set up a project and data loader, customize the dashboard, and deploy it.
I've been using Quarto for over a year now and I fully endorse it for technical writing, a game changer that can help get your work out there 🚀 If you're new to this space and want to get involved I highly recommend this as a starting point: https://youtu.be/_f3latmOhew?si=VxcMut5INSgK4pyP#DataScience
The End To End Data Science With R is a new book by Rene Essomba. The book, as the name implies, focuses on the core data science applications using R ❤️. This book covers the following topics:
✅ Exploratory data analysis
✅ Data visualization
✅ Supervised learning
✅ Unsupervised learning
✅ Time series
✅ Natural language processing
✅ Image classification
I'm looking for consulting work in data science/data analysis. I'm based in Christchurch, New Zealand, but I'm happy to work remote.
I have a background in media & communication, so I'm happy working with clients of any technical ability ^_^ I've worked on projects ranging from surveys of social workers to network analysis, so I'm happy to try anything!