Using WebR + Pyodide To Fill In The (Temporary) Package Gaps
I won’t wax long and poetic here since I’ve already posted the experiment that has all the details. TL;DR: there are still only ~90-ish 📦 in the WebR WASM “CRAN”,...continue reading.
Category: Python
The State of Shiny Survey: An Essential Tool for Data Scientists
The adoption of Shiny, the R package for building interactive web applications, is growing. As a leader in R Shiny development for enterprises, we’re asking you, fellow users of R...continue reading.
Working with Time Zones & Daylight Saving Time in pandas 🕑
Are you working with datetime data in pandas? Learn how to become “timezone-aware” so that your dataset cooperates with Daylight Saving Time!continue reading.
The Effect [book review]
While it sounds like the title of a science-fiction catastrophe novel or of a (of course) convoluted nouveau roman, this book by Nick Huntington-Klein is a massive initiation to econometrics...continue reading.
When R is Better
Recently, I wrote a blog post stating that I’m starting to use Python for most of my data science work. And I’m starting to recommend Python as the data science...continue reading.
When R is Better
Recently, I wrote a blog post stating that I’m starting to use Python for most of my data science work. And I’m starting to recommend Python as the data science...continue reading.
Why You Should Learn ONE Data Science Language
There are multiple data science languages to choose from. The most popular being R and Python. Many people will tell you to learn both. Learn R AND Python. I think...continue reading.
How to use Python’s f-strings with pandas
Learn how to use Python’s f-strings for substitution and formatting, and then combine those features to solve a real-world pandas problem!continue reading.
Why Python is the Best Data Science Language (in 2023)
The first question that aspiring data scientists ask me is “what is the best data science language … which should I learn.” And almost always, this is framed as a...continue reading.
Numpy Transpose, Explained
In this tutorial, I’ll show you how to use the Numpy transpose function. I’ll explain what the function does, how the syntax works, and I’ll show you step-by-step examples of...continue reading.
Numpy Copy, Explained
In this tutorial, I’ll explain the Numpy copy function. I’ll explain the syntax of np.copy and show you a clear example of how to use it. If you need something...continue reading.
Advent of 2022, Day 16 – MLflow in action with xgboost
In the series of Azure Machine Learning posts: Yesterday we have looked into how to start the MLflow configurations and today, let’s put this to the test. We will create...continue reading.
Advent of 2022, Day 15 – Getting to know MLflow
In the series of Azure Machine Learning posts: MLFlow is an open-source framework for registering, managing and tracking machine learning models. It is multiplatform, bringing consistent model training and model...continue reading.
Advent of 2022, Day 14 – Registering the models
In the series of Azure Machine Learning posts: Important asset is the “Models” in navigation bar. This feature allows you to work with different model types -> custom, MLflow, and...continue reading.
Advent of 2022, Day 13 – Automated ML
In the series of Azure Machine Learning posts: Automated ML is a no-code automated machine learning task. It iterates over many combinations of algorithms and hyperparameters in order to find...continue reading.
Advent of 2022, Day 12 – Creating jobs
In the series of Azure Machine Learning posts: An Azure ML job executes a task against a specified compute target. This is also how the job is created. By configuring...continue reading.
Advent of 2022, Day 11 – Creating Pipelines with Python SDK
In the series of Azure Machine Learning posts: A pipeline is set of instructions (or a workflow) for executing particular work of a machine learning task. The idea behind pipelines...continue reading.
Advent of 2022, Day 10 – Connecting to client using Python SDK namespaces
In the series of Azure Machine Learning posts: Let’s continue to explore the power of SDK and the namespaces. And we will look into namespace that will help you connect...continue reading.
Advent of 2022, Day 9 – Python SDK namespaces for environment, and pipelines
In the series of Azure Machine Learning posts: Let’s continue to explore the power of SDK and the namespaces. Environment Python SDK namespace is azureml.core.environment. Environments specify the set of...continue reading.
Advent of 2022, Day 8 – Python SDK namespaces for workspace, experiments and models
In the series of Azure Machine Learning posts: Looking briefly into Azure CLI and Python SDK, let’s explore the power of SDK and the most important namespaces. Create a new...continue reading.
