How to Rename a File in Linux Terminal
“Renaming files in Linux is easy with the ‘mv’ command. It allows renaming single/multiple files, handling special characters, and prevents overwrites.”
How to Deploy Machine Learning Models Using Fast API
Deploying machine learning models in production is easy with FastAPI. Here’s how to deploy scikit learn models.
Data challenges in Production ML Systems.
Data is the main challenge in production ML systems. Here are four different aspects of data ML engineers should be aware when serving models.
Machine Learning Systems in Real-Life Production vs. Research/Academic Settings.
Real-life machine learning is far from what we encounter in an academic setting. Here are the challenges of production ML.
How to Train Deep Learning Models With Small Datasets
Training a deep learning model requires a lot of data. When we can also build a successful model with small datasets with these techniques.
Scalable, No-Code, AutoML Solution on Your Amazon Cloud
Build end-to-end machine learning pipeline, train, test and deploy ML models without depending on data scientists and worrying about scalability.
How to Embed Serverless Jupyter Notebooks on Any Website
Let your website visitors try out Python code snippets then and there.
This Tiny Python Package Creates Huge Augmented Datasets
How to create an image data augmentation pipeline to generate tons of synthetic data points?
Python | MLOps | Programming
How to Run Python Tests on Every Commit Using GitHub Actions
Running Python unit tests every time before publishing changes is difficult. Automating it through a CI pipeline help save a lot of effort. GitHub Actions does it well.
In the 8 Key MLOps Roles, Where Do You Fit In?
Large-scale data science teams can have several distinct roles & responsibilities to manage machine learning operations.