Welcome to the Age of AI
Unless you’ve been living in a secluded hut on the side of a remote mountain in Nepal, you’ve probably heard major chatter about AI in the last few months. First,...continue reading.
Category: Machine learning
Upside down, a cat’s still a cat: Evolving image recognition with Geometric Deep Learning
In this first in a series of posts on group-equivariant convolutional neural networks (GCNNs), meet the main actors — groups — and concepts (equivariance). With GCNNs, we finally revisit the...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.
AO, NAO, ENSO: A wavelet analysis example
El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO) are atmospheric phenomena of global impact that strongly affect people’s lives. ENSO, first and foremost, brings with it...continue reading.
Imputation in R: Top 3 Ways for Imputing Missing Data
Real-world data is often messy and full of missing values. As a result, data scientists spend the majority of their time cleaning and preparing the data, and have less time...continue reading.
Having some fun with Stable Diffusion Inpainting in Python on New Year’s Day
It is New Year’s Day 2023 :sweat_smile:. Happy New Year!!! :fireworks: I am currently driving with my family coast-to-coast on a road trip through the United States, but for New...continue reading.
Advent of 2022, Day 23 – Working with R
In the series of Azure Machine Learning posts: This post is super short 😦 R language and Azure Machine Learning SDK for R was deprecated a year ago (end of...continue reading.
Advent of 2022, Day 22 – Batch endpoints for batch scoring
In the series of Azure Machine Learning posts: Batch endpoints are a great and simple way to run inference over large volumes of data. They simplify the process of hosting...continue reading.
Advent of 2022, Day 21 – Using Azure Machine Learning terminal
In the series of Azure Machine Learning posts: Using Azure CLI can help you progress faster, make repetitve tasks automated and even use the GIT integration, for faster and better...continue reading.
Advent of 2022, Day 20 – Handling kernels, python packages, YAML files in notebooks and keeping structure and good practices
In the series of Azure Machine Learning posts: When creating notebooks, it is always a good way to have the dependencies included. Whether it is a particular version of a...continue reading.
Advent of 2022, Day 19 – Statistical analysis and ML comparison of prediction models
In the series of Azure Machine Learning posts: Yesterday we have shown, that statistical analysis and all bolts and whistles can be done super simple in Azure machine learning. Today...continue reading.
Advent of 2022, Day 18 – Statistical analysis, plotting graphs and feature engineering
In the series of Azure Machine Learning posts: Azure Machine Learning is also a great tool to do ordinary statistical analysis, graph plotting and everything that goes along. Let’s get...continue reading.
Advent of 2022, Day 17 – Building responsible AI dashboard with Python SDK
In the series of Azure Machine Learning posts: Responsible AI is an approach to assessing, developing, and deploying AI systems in a safe, trustworthy, and ethical manner, and take responsible...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.
