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    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 such as remote functions...

    Data Science

    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...
    Data Science Data Science Featured Homepage Featured Main Practical Techniques Python Pandas D-Tale Profiler EDA

    Explaining black-box models using attribute importance, PDPs, and LIME

    In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights...
    Data Science Code Homepage Featured Main Machine Learning Python Explainability Deep Learning

    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
    Code

    Building a Named Entity Recognition model using a BiLSTM-CRF network

    In this blog post we present the Named Entity Recognition problem and show how a BiLSTM-CRF model can be fitted using a freely available annotated...
    Data Science Code Homepage Featured Main Machine Learning Machine Learning Featured Python NLP

    Accelerating model velocity through Snowflake Java UDF integration

    Over the next decade, the companies that will beat competitors will be “model-driven” businesses. These companies often undertake large data...
    Code Engineering Domino Product Domino Practical Techniques Data Engineering Datasets snowflake Practical Techniques Featured
    Machine Learning

    Fitting Support Vector Machines via Quadratic Programming

    In this blog post we take a deep dive into the internals of Support Vector Machines. We derive a Linear SVM classifier, explain its advantages, and...
    Data Science Code Data Science Featured Machine Learning SVM Python

    ML internals: Synthetic Minority Oversampling (SMOTE) Technique

    In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. We present the...
    Data Science Code Homepage Featured Main Machine Learning Practical Techniques

    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...
    Data Science Domino Users Code Data Science Teams Domino Product Domino Practical Techniques Data Engineering Datasets Data Scientists snowflake Homepage Featured Secondary Managing Data Science Featured

    Why models fail to deliver value and what you can do about it.

    Building models requires a lot of time and effort. Data scientists can spend weeks just trying to find, capture and transform data into decent...
    Data Science Leaders At Work Model Management Data Science Teams Practical Techniques Data Science Leaders Data Scientists Homepage Featured Secondary data Managing Data Science Featured
    Practical Techniques

    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...
    Data Science Practical Techniques signal processing

    Enterprise-class NLP with spaCy v3

    spaCy is a python library that provides capabilities to conduct advanced natural language processing analysis and build models that can underpin...
    Data Science Data Science Featured Practical Techniques spaCy Python NLP
    Leaders at Work

    Defining clear metrics to drive model adoption and value creation

    One of the biggest ironies of enterprise data science is that although data science teams are masters at using probabilistic models and diagnostic...
    Data Science Leaders At Work Advice for Aspiring Chief Data Scientists Leaders At Work Featured Model Evaluation Model Deployment value

    Announcement: Domino is fully Kubernetes native

    Last week we announced that Domino is now fully Kubernetes native. This is great news for data science teams and IT organizations building modern DS...
    Data Science Leaders At Work Engineering Engineering Featured Announcement Data Science Teams Domino Product Domino IT and Data Science Alignment Data Scientists IT Kubernetes
    Model Management

    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,...
    AWS Model Management modelops Models Featured Model Production Containers Model Development

    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...
    Data Science Domino Users Homepage Featured Main Announcement Model Management Data Science Teams Domino Product Domino Data Science Leaders Data Scientists Data Science Platform model

    Towards Predictive Accuracy: Tuning Hyperparameters and Pipelines

    This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E....
    Addison-Wesley Professional Data Science Code Model Management Machine Learning sklearn Models Featured Practical Techniques Model Evaluation Python KNeighborsClassifier Hyperparameters Model Context RandomizedSearch Tuning Hyperparameters Model Development K-NN GridSearch model

    Manual Feature Engineering

    Many thanks to AWP Pearson for the permission to excerpt "Manual Feature Engineering: Manipulating Data for Fun and Profit" from the book, Machine...
    Addison-Wesley Professional Data Science Code Engineering Model Management Machine Learning Practical Techniques Feature Engineering data model
    Engineering

    Announcing Domino 3.4: Furthering Collaboration with Activity Feed

    Our last release, Domino 3.3 saw the addition of two major capabilities: Datasets and Experiment Manager. “Datasets”, a high-performance, revisioned...
    Data Science Engineering Collaboration Activity Feed Model Management Domino Product Domino Data Scientists data Model Development

    Machine Learning in Production: Software Architecture

    Special thanks to Addison-Wesley Professional for permission to excerpt the following "Software Architecture" chapter from the book, Machine Learning...
    Addison-Wesley Professional Engineering Model Management Machine Learning Software Architecture Data Science and Data Engineering Alignment Practical Techniques Model Production Data Engineering Data Infrastructure Data Scientists