Data Science Blog

Polars - A lightning fast DataFrames library

We have previously talked about the challenges that the latest SOTA models present in terms of computational complexity. We've also talked about...

Data Science Python Pandas Parallel Processing

The Importance of Machine Learning Model Validation and How It Works

Model validation is a core component of developing machine learning or artificial intelligence (ML/AI). While it’s separate from training and...

Data Science Model Management Machine Learning Model Development

MATLAB for Data Science and Machine Learning

The opportunities to solve problems with the use of data are greater than ever, and as different industries embrace them, the available data has been...

Data Science Matlab

Data Exploration with Pandas Profiler and D-Tale

We all have heard how data is the new oil. I always say that if that is the case, we need to go through some refinement process before that raw oil...

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Getting Started with OpenCV

In this article we talk about the foundations of Computer vision, the history and capabilities of the OpenCV framework, and how to make your first...

Code Machine Learning Deep Learning Computer Vision

Reinforcement Learning: The K-armed bandit problem

In a previous blog post we talked about the foundations of reinforcement learning. We covered classical and operant conditioning, rewards, states,...

Code Python Reinforcement Learning

N-shot and Zero-shot learning with Python

Introduction In a previous post we talked about how advances in deep learning neural networks have allowed significant improvements in learning...

Machine Learning Python transfer learning

A Hands-on Tutorial for Transfer Learning in Python

Fitting complex neural network models is a computationally heavy process, which requires access to large amounts of data. In this article we...

Machine Learning Python transfer learning

Simplify Data Access and Publish Model Results in Snowflake Using Domino Data Lab

Introduction Arming data science teams with the access and capabilities needed to establish a two-way flow of information is one critical...

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Practical Techniques

Building a Speaker Recognition Model

The ability of a system to recognize a person by their voice is a non-intrusive way to collect their biometric information. Unlike fingerprint...

Data Science Machine Learning Practical Techniques signal processing Python

Fundamentals of Signal Processing

Basics of Digital Signal Processing A signal is defined as any physical quantity that varies with time, space or any other independent variables....

Data Science Practical Techniques signal processing

Leaders at Work

Fireside Chat: Stig Pedersen from Topdanmark

"In having one or two very successful algorithmic deployments, the business then begins coming to you to ask for assistance. It becomes a mutual...

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Defining Metrics to Drive Machine Learning Model Adoption & Value

One of the biggest ironies of enterprise data science is that although data science teams are masters at using probabilistic models and diagnostic...

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Model Management

A Guide to Machine Learning Model Deployment

Machine-learning (ML) deployment involves placing a working ML model into an environment where it can do the work it was designed to do. The process...

Model Management Model Monitoring Model Deployment

Machine Learning Modeling: How It Works and Why It’s Important

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of...

Model Management Model Technology Model Production Model Monitoring Model Evaluation Model Deployment Model Myth Model Delivery Model Context Model Governance Model Productivity

The Role of Containers on MLOps and Model Production

Container technology has changed the way data science gets done. The original container use case for data science focused on what I call,...

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Domino Paves the Way for the Future of Enterprise Data Science with Latest Release

Today, we announced the latest release of Domino’s data science platform which represents a big step forward for enterprise data science teams. We’re...

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Engineering

Tensorflow, PyTorch or Keras for Deep Learning

Machine learning provides us with ways to create data-powered systems that learn and enhance themselves, without being specifically programmed for...

Engineering Python Deep Learning Neural Networks

Getting Started with Ray

In this blog post we give a quick introduction to Ray. We talk about the architecture and execution model, and present some of Ray's core paradigms...

Code Engineering High-Performance Computing Ray Python

Transformers - Self-Attention to the rescue

Data Science