- Improving model performance through human participation - Apr 23, 2021.
Certain industries, such as medicine and finance, are sensitive to false positives. Using human input in the model inference loop can increase the final precision and recall. Here, we describe how to incorporate human feedback at inference time, so that Machines + Humans = Higher Precision & Recall.
Data Science Platform, Humans, Machine Learning, Model Performance, Precision, Recall
- Data Observability, Part II: How to Build Your Own Data Quality Monitors Using SQL - Feb 23, 2021.
Using schema and lineage to understand the root cause of your data anomalies.
Data Engineering, Data Quality, Data Science, Data Science Platform, SQL
- Data Observability: Building Data Quality Monitors Using SQL - Feb 16, 2021.
To trigger an alert when data breaks, data teams can leverage a tried and true tactic from our friends in software engineering: monitoring and observability. In this article, we walk through how you can create your own data quality monitors for freshness and distribution from scratch using SQL.
Data Engineering, Data Quality, Data Science, Data Science Platform, SQL
- Data Catalogs Are Dead; Long Live Data Discovery - Dec 28, 2020.
Why data catalogs aren’t meeting the needs of the modern data stack, and how a new approach – data discovery – is needed to better facilitate metadata management and data reliability.
Data Catalog, Data Discovery, Data Science, Data Science Platform
- A Tour of End-to-End Machine Learning Platforms - Jul 29, 2020.
An end-to-end machine learning platform needs a holistic approach. If you’re interested in learning more about a few well-known ML platforms, you’ve come to the right place!
AirBnB, Data Science Platform, Google, Machine Learning, MLOps, Netflix, Pipeline, Uber, Workflow
- What I learned from looking at 200 machine learning tools - Jul 21, 2020.
While hundreds of machine learning tools are available today, the ML software landscape may still be underdeveloped with more room to mature. This review considers the state of ML tools, existing challenges, and which frameworks are addressing the future of machine learning software.
Data Science Platform, Data Science Tools, Machine Learning, MLOps, Open Source, Tools
- Data Science Tools Popularity, animated - Jun 25, 2020.
Watch the evolution of the top 10 most popular data science tools based on KDnuggets software polls from 2000 to 2019.
About KDnuggets, Data Science Platform, Poll, Python, R
- Lynx Analytics is open-sourcing LynxKite, its Complete Graph Data Science Platform - Jun 25, 2020.
Check out this article for a brief summary on what LynxKite is, where it is coming from and how it can help with your data science projects.
Data Science Platform, Graph Analytics, Open Source
- Count, the data notebook everyone can use - Jun 9, 2020.
Dashboards have been the primary weapon of choice for distributing data over the last few decades, but they have brought with them a new set of problems. To increasingly democratise access to data we need to think again.
Dashboard, Data Science Platform, Jupyter
- State of the Machine Learning and AI Industry - Apr 16, 2020.
Enterprises are struggling to launch machine learning models that encapsulate the optimization of business processes. These are now the essential components of data-driven applications and AI services that can improve legacy rule-based business processes, increase productivity, and deliver results. In the current state of the industry, many companies are turning to off-the-shelf platforms to increase expectations for success in applying machine learning.
AI, AutoML, Data Science Platform, Industry, Machine Learning
Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms - Feb 24, 2020.
The Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms has the largest number of leaders ever. We examine the leaders and changes and trends vs previous years.
Alteryx, Data Science Platform, Databricks, Dataiku, DataRobot, Domino, Gartner, Google, H2O, IBM, Knime, Machine Learning, Magic Quadrant, MathWorks, Microsoft Azure, RapidMiner, SAS, TIBCO
- Manual Coding or Automated Data Integration – What’s the Best Way to Integrate Your Enterprise Data? - Aug 19, 2019.
What’s the best way to execute your data integration tasks: writing manual code or using ETL tool? Find out the approach that best fits your organization’s needs and the factors that influence it.
Advice, Data Integration, Data Management, Data Science, Data Science Platform, ETL
- KDnuggets™ News 19:n21, Jun 5: Transitioning your Career to Data Science; 11 top Data Science, Machine Learning platforms; 7 Steps to Mastering Intermediate ML w. Python - Jun 5, 2019.
The results of KDnuggets 20th Annual Software Poll; How to transition to a Data Science career; Mastering Intermediate Machine Learning with Python ; Understanding Natural Language Processing (NLP); Backprop as applied to LSTM, and much more.
Backpropagation, Data Science Platform, LSTM, Machine Learning, NLP, Python
Gainers, Losers, and Trends in Gartner 2019 Magic Quadrant for Data Science and Machine Learning Platforms - Feb 11, 2019.
We compare Gartner 2019 MQ for Data Science, Machine Learning Platforms to its previous versions and identify notable changes for leaders and challengers, including RapidMiner, KNIME, TIBCO, Alteryx, Dataiku, SAS, and MathWorks.
Alteryx, Data Science Platform, Dataiku, DataRobot, Gartner, Google, H2O, IBM, Knime, Machine Learning, Magic Quadrant, MathWorks, Microsoft, RapidMiner, SAS, TIBCO
- The 2018 Data Scientist Report is Here - Aug 23, 2018.
Learn about the data and tools that data scientists are working with in 2018, Ethical issues around AI, Algorithmic bias, Job satisfaction, and more.
Bias, Career, Data Science Platform, Data Science Tools, Data Scientist, Ethics, Figure Eight
Python eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018: Trends and Analysis - May 22, 2018.
Python continues to eat away at R, RapidMiner gains, SQL is steady, Tensorflow advances pulling along Keras, Hadoop drops, Data Science platforms consolidate, and more.
Pages: 1 2
Anaconda, Data Mining Software, Data Science Platform, Hadoop, Keras, Poll, Python, R, RapidMiner, SQL, TensorFlow, Trends
Gainers and Losers in Gartner 2018 Magic Quadrant for Data Science and Machine Learning Platforms - Feb 27, 2018.
We compare Gartner 2018 Magic Quadrant for Data Science, Machine Learning Platforms vs its 2017 version and identify notable changes for leaders and challengers, including IBM, SAS, RapidMiner, KNIME, Alteryx, H2O.ai, and Domino.
Alteryx, Anaconda, Angoss, Data Science Platform, Domino, Gartner, H2O, IBM, Knime, Machine Learning, Magic Quadrant, RapidMiner, SAS
- Introducing R-Brain: A New Data Science Platform - Oct 11, 2017.
R-Brain is a next generation platform for data science built on top of Jupyterlab with Docker, which supports not only R, but also Python, SQL, has integrated intellisense, debugging, packaging, and publishing capabilities.
Data Science Platform, Docker, Jen Underwood, Jupyter, R, R-Brain
- An opinionated Data Science Toolbox in R from Hadley Wickham, tidyverse - Oct 10, 2017.
Get your productivity boosted with Hadley Wickham's powerful R package, tidyverse. It has all you need to start developing your own data science workflows.
Data Analysis, Data Science, Data Science Platform, Data Science Tools, Hadley Wickham, R, Tidyverse
Python overtakes R, becomes the leader in Data Science, Machine Learning platforms - Aug 28, 2017.
While Python did not "swallow" R, in 2017 Python ecosystem overtook R as the leading platform for Analytics, Data Science, and Machine Learning and is pulling users from other platforms.
Data Science Platform, Poll, Python, Python vs R, R
- Data science platforms are on the rise and IBM is leading the way - May 25, 2017.
Download the 2017 Gartner Magic Quadrant for Data Science Platforms today to learn why IBM is named a leader in data science and to find out why data science, analytics, and machine learning are the engines of the future.
Data Science Platform, Gartner, IBM, IBM SPSS Modeler
- Data Science & Machine Learning Platforms for the Enterprise - May 8, 2017.
A resilient Data Science Platform is a necessity to every centralized data science team within a large corporation. It helps them centralize, reuse, and productionize their models at peta scale.
Algorithmia, Data Science Platform, Enterprise, Machine Learning
New Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months? - May 5, 2017.
Vote in KDnuggets 18th Annual Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months? We will clean, analyze, visualize, and publish the results.
Data Mining Software, Data Science Platform, Deep Learning, Poll
- Dataiku: The Complete Data Sheet - Apr 20, 2017.
Whether your every day tool is Scala, Python, R, or Excel, you can now use one tool - Dataiku - to transform raw data to predictions without the hassle. Discover the platform!
Automated Data Science, Data Science Platform, Data Workflow, Dataiku
Forrester vs Gartner on Data Science Platforms and Machine Learning Solutions - Apr 14, 2017.
Who leads in Data Science, Machine Learning, and Predictive Analytics? We compare the latest Forrester and Gartner reports for this industry for 2017 Q1, identify gainers and losers, and strong leaders vs contenders.
Data Science Platform, Forrester, Gartner, IBM, Knime, Machine Learning, Mike Gualtieri, Predictive Analytics, RapidMiner, SAS
- Gartner Data Science Platforms – A Deeper Look - Mar 3, 2017.
Thomas Dinsmore critical examination of Gartner 2017 MQ of Data Science Platforms, including vendors who out, in, have big changes, Hadoop and Spark integration, open source software, and what Data Scientists actually use.
Apache Spark, Data Science Platform, Gartner, IBM, Python, R, SAS, Thomas Dinsmore
Gartner 2017 Magic Quadrant for Data Science Platforms: gainers and losers - Feb 23, 2017.
We compare Gartner 2017 Magic Quadrant for Data Science Platforms vs its 2016 version and identify notable changes for leaders and challengers, including IBM, SAS, RapidMiner, KNIME, MathWorks, Microsoft, and Quest.
Data Science Platform, Gartner, IBM, Knime, Magic Quadrant, MathWorks, Microsoft, Quest, RapidMiner, SAS
- R, Python Duel As Top Analytics, Data Science software – KDnuggets 2016 Software Poll Results - Jun 6, 2016.
R remains the leading tool, with 49% share, but Python grows faster and almost catches up to R. RapidMiner remains the most popular general Data Science platform. Big Data tools used by almost 40%, and Deep Learning usage doubles.
Pages: 1 2
Data Mining Software, Data Science Platform, Poll, Python, Python vs R, R, RapidMiner, SQL
- Angoss 9.6 Data Science Software Suite - Apr 29, 2016.
Angoss software provides users with comprehensive scorecard building functionality that is fast, reliable, accurate, and business centric.
Angoss, Data Science Platform, Optimization, Tableau
- Salford Predictive Modeler 8: Faster. More Machine Learning. Better results - Apr 4, 2016.
Take a giant step forward with SPM 8: Download and try it for yourself just released version 8 and get better results.
Classification, Data Science Platform, Decision Trees, Regression, Salford Systems, TreeNet
- New Salford Predictive Modeler 8 - Mar 1, 2016.
Salford Predictive Modeler software suite: Faster. More Comprehensive Machine Learning. More Automation. Better results. Take a giant step forward in your data science productivity with SPM 8. Download and try it today!
Data Science Platform, Decision Trees, Gradient Boosting, Predictive Modeler, Regression, Salford Systems
- Dataiku Data Science Studio – intuitive solution for data professionals - Jul 8, 2015.
Data Science Studio (DSS) from Dataiku is an intuitive software solution that let data professionals harness the power of big data. The latest version DSS 2.0 brings predictive analytics to a whole new level in terms of collaboration and usability.
Data Science Platform, Dataiku
- Domino – A Platform For Modern Data Analysis - Jun 26, 2014.
Tools that facilitate data science best practices have not yet matured to match their counterparts in the world of software engineering. Domino is a platform built from the ground up to fill in these gaps and accelerate modern analytical workflows.
Business Analytics, Data Analysis, Data Science Platform, Domino, Tools
- Data Lakes vs Data Warehouses - Jun 7, 2014.
Data Warehouses, traditionally popular for business intelligence tasks, are being replaced by less-structured Data Lakes which allow more flexibility.
Business Intelligence, Data Lakes, Data Science Platform, Data Visualization, Data Warehouse, DataRPM
