I'm a passionate writer and practitioner in the field of machine learning in production. With a strong background in both machine learning and software engineering, I bring a unique perspective to the challenges and intricacies of deploying machine learning models in real-world environments.
Freelance ML, Data analysis, and Technical writing
Mar 24, 2024 · 2 min read · Machine learning models are prepared in two steps: training and tuning. We can distinguish these processes by what they're affecting. Let's take a look at what a machine-learning algorithm is. A machine learning algorithm tries to capture what happen...
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Aug 25, 2023 · 5 min read · Photo by Boitumelo on Unsplash In the world of machine learning and deep learning, two popular techniques often used to leverage pre-trained models are fine-tuning and transfer learning. These approaches allow us to benefit from the knowledge and exp...
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Aug 4, 2023 · 4 min read · Airflow is an open-source platform for creating, scheduling, and monitoring workflows. In this tutorial, we'll use Airflow to extract weather data from an API, transform the data, and load it into a CSV file in an S3 bucket. We'll start by creating a...
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Jul 27, 2023 · 3 min read · To bring any machine learning model to fruition, an abundance of experimentation cycles is required to ascertain the optimal ML model that will effectively achieve the desired business objective. This phase of experimentation introduces a heightened ...
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Jul 20, 2023 · 7 min read · This article is a part of my 'Practical Model Evaluation' series that I started a few months ago. You can find the links to the first and second parts below. Part 1: The first approach Part 2: Training models with automated machine learning In t...
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