- Facebook Open Sources ReBeL, a New Reinforcement Learning Agent - Dec 14, 2020.
The new model tries to recreate the reinforcement learning and search methods used by AlphaZero in imperfect information scenarios.
- Facebook Open Sourced New Frameworks to Advance Deep Learning Research - Nov 17, 2020.
Polygames, PyTorch3D and HiPlot are the new additions to Facebook’s open source deep learning stack.
- Microsoft and Google Open Sourced These Frameworks Based on Their Work Scaling Deep Learning Training - Nov 2, 2020.
Google and Microsoft have recently released new frameworks for distributed deep learning training.
- Uber Open Sources the Third Release of Ludwig, its Code-Free Machine Learning Platform - Oct 13, 2020.
The new release makes Ludwig one of the most complete open source AutoML stacks in the market.
- Getting Started in AI Research - Oct 5, 2020.
A guide on how to contribute to confirming the reproducibility of some of the most recent papers and join open-search research.
- Netflix’s Polynote is a New Open Source Framework to Build Better Data Science Notebooks - Aug 5, 2020.
The new notebook environment provides substantial improvements to streamline experimentation in machine learning workflows.
- 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.
- 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.
- Uber’s Ludwig is an Open Source Framework for Low-Code Machine Learning - Jun 15, 2020.
The new framework allow developers with minimum experience to create and train machine learning models.
- LinkedIn Open Sources a Small Component to Simplify the TensorFlow-Spark Interoperability - May 25, 2020.
Spark-TFRecord enables the processing of TensorFlow’s TFRecord structures in Apache Spark.
- Build and deploy your first machine learning web app - May 22, 2020.
A beginner’s guide to train and deploy machine learning pipelines in Python using PyCaret.
- Facebook Open Sources Blender, the Largest-Ever Open Domain Chatbot - May 15, 2020.
The new conversational agent exhibit human-like behavior in conversations about almost any topic.
- Google Open Sources SimCLR, A Framework for Self-Supervised and Semi-Supervised Image Training - Apr 27, 2020.
The new framework uses contrastive learning to improve image analysis in unlabeled datasets.
- Announcing PyCaret 1.0.0 - Apr 21, 2020.
An open source low-code machine learning library in Python. PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few words only. This makes experiments exponentially fast and efficient.
- OpenAI Open Sources Microscope and the Lucid Library to Visualize Neurons in Deep Neural Networks - Apr 17, 2020.
The new tools shows the potential of data visualizations for understanding features in a neural network.
- Free Workshop Preview: Data Thinking with Martin Szugat - Apr 13, 2020.
As anticipation grows for Predictive Analytics World’s virtual conferences (PAW for Industry 4.0, PAW for Healthcare and Deep Learning World on 11-12 May 2020) and virtual workshops (13 May 2020), here is a chance to start familiarising yourself with the quality of the content and of the virtual networking. Gain an insight into how to apply design thinking for data science & analytics. Reserve your spot.
- Sharing your machine learning models through a common API - Feb 12, 2020.
DEEPaaS API is a software component developed to expose machine learning models through a REST API. In this article we describe how to do it.
- KDnuggets™ News 19:n46, Dec 4: The Future of Data Science Careers; Which Data Visualization Should I Use? - Dec 4, 2019.
This week: The Future of Careers in Data Science & Analysis; Task-based effectiveness of basic visualizations; Open Source Projects by Google, Uber and Facebook for Data Science and AI; Getting Started with Automated Text Summarization; A Non-Technical Reading List for Data Science; and much more!
- Google Open Sources MobileNetV3 with New Ideas to Improve Mobile Computer Vision Models - Dec 2, 2019.
The latest release of MobileNets incorporates AutoML and other novel ideas in mobile deep learning.
- Open Source Projects by Google, Uber and Facebook for Data Science and AI - Nov 28, 2019.
Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.
- Contributing to PyTorch: By someone who doesn’t know a ton about PyTorch - Oct 9, 2019.
By the end of my week with the team, I managed to proudly cut two PRs on GitHub. I decided that I would write a blog post to knowledge share, not just to show that YES, you can too.
- What’s the Best Data Strategy for Enterprises: Build, buy, partner or acquire? - Jul 22, 2019.
Every large organization is investing heavily in building data solutions and tools. They are building data solutions from scratch when they could be taking advantage of readily available tools and solutions. Many organizations are re-inventing the wheel and wasting resources.
- 2018 Year-in-Review: Machine Learning Open Source Projects & Frameworks - Dec 17, 2018.
This post is a look at the top open source projects and major developments in machine learning frameworks over the past 12 months.
- A comprehensive list of Machine Learning Resources: Open Courses, Textbooks, Tutorials, Cheat Sheets and more - Dec 7, 2018.
A thorough collection of useful resources covering statistics, classic machine learning, deep learning, probability, reinforcement learning, and more.
- Open Source Data Science Adoption: The How & Why - Dec 4, 2018.
Get the report on Enterprise Open Source Data Science Adoption which outlines the most popular open source tools for a host of jobs. Free download.
- The Evolution of Build Engineering in Managing Open Source [Webinar Replay] - Nov 13, 2018.
Explore how the role of build engineering is evolving to reconcile two key trends: massive wide-scale adoption of open source; the most devastating cyber-attacks in recent history tied to unpatched dependencies and other vulnerabilities.
- How to Mitigate Open Source License Risks - Oct 30, 2018.
This whitepaper from ActiveState investigates the various types of OSS licenses, common myths and risks, DIY risk management, the importance of enterprise legal indemnification, and more.
- Implementing Automated Machine Learning Systems with Open Source Tools - Oct 25, 2018.
What if you want to implement an automated machine learning pipeline of your very own, or automate particular aspects of a machine learning pipeline? Rest assured that there is no need to reinvent any wheels.
- Datmo: the Open Source tool for tracking and reproducible Machine Learning experiments - Sep 26, 2018.
As a data scientist, managing environments and experiments is always hard and results in wasted time and effort with all the troubleshooting and lost work. With datmo, you can track your experiments using this common standard and not worry about reproduction of previous work.
- 10 Big Data Trends You Should Know - Sep 17, 2018.
A collection of Big Data trends to familiarize yourself with, covering IoT Networks, Artificial Intelligence, Predictive Analytics, Dark Data and more.
- Analyze, engineer, design: Do it all with Dash - Aug 24, 2018.
Open-source Dash lets you wrap a GUI around that analytical code, without leaving the familiarity of Python. Explore your data with rich, interactive drop-down menus, sliders, and other components, all in the web browser.
- The 6 components of Open-Source Data Science/ Machine Learning Ecosystem; Did Python declare victory over R? - Jun 6, 2018.
We find 6 tools form the modern open source Data Science / Machine Learning ecosystem; examine whether Python declared victory over R; and review which tools are most associated with Deep Learning and Big Data.
- ioModel Machine Learning Research Platform – Open Source - Jun 5, 2018.
This article introduces ioModel, an open source research platform that ingests data and automatically generates descriptive statistics on that data.
- Torus for Docker-First Data Science - May 8, 2018.
To help data science teams adopt Docker and apply DevOps best practices to streamline machine learning delivery pipelines, we open-sourced a toolkit based on the popular cookiecutter project structure.
- Top 16 Open Source Deep Learning Libraries and Platforms - Apr 24, 2018.
We bring to you the top 16 open source deep learning libraries and platforms. TensorFlow is out in front as the undisputed number one, with Keras and Caffe completing the top three.
- How I Unknowingly Contributed To Open Source - Apr 24, 2018.
This article explains what is meant by the term 'open source' and why all data scientists should be a part of it.
- Top KDnuggets tweets, Feb 14-20: Neural Network AI is simple. So… Stop pretending you are a genius - Feb 21, 2018.
#NeuralNetwork #AI is simple. Stop pretending you are a genius; Cartoon: #ValentinesDay or #MachineLearning Problems in 2118; #MachineLearning Top 10 Open Source Projects.
- Top 20 Python AI and Machine Learning Open Source Projects - Feb 20, 2018.
We update the top AI and Machine Learning projects in Python. Tensorflow has moved to the first place with triple-digit growth in contributors. Scikit-learn dropped to 2nd place, but still has a very large base of contributors.
- Supercharging Visualization with Apache Arrow - Jan 5, 2018.
Interactive visualization of large datasets on the web has traditionally been impractical. Apache Arrow provides a new way to exchange and visualize data at unprecedented speed and scale.
- DeepSchool.io: Deep Learning Learning - Dec 22, 2017.
What I truly envision for deep school is that this will build a whole lot of Meetup nodes across the world where people will learn, mentor and network around sharing AI knowledge.
- Choosing an Open Source Machine Learning Library: TensorFlow, Theano, Torch, scikit-learn, Caffe - Nov 8, 2017.
Open Source is the heart of innovation and rapid evolution of technologies, these days. Here we discuss how to choose open source machine learning tools for different use cases.
Pages: 1 2
- Full Stack Data Science at ODSC - Aug 29, 2017.
Improve your skills in every layer of the Data Science stack at ODSC West 2017 and test drive the leading open source tools. Save 60% with code KD60 until Sep 1.
- Data Version Control in Analytics DevOps Paradigm - Aug 14, 2017.
DevOps and DVC tools can help reduce time data scientists spend on mundane data preparation and achieve their dream of focusing on cool machine learning algorithms and interesting data analysis.
- Why Apache Arrow is the future for open source-columnar memory analytics - Aug 7, 2017.
Apache Arrow is a de-facto standard for columnar in-memory analytics. In the coming years we can expect all the big data platforms adopting Apache Arrow as its columnar in-memory layer.
- Visualizing Convolutional Neural Networks with Open-source Picasso - Aug 1, 2017.
Toolkits for standard neural network visualizations exist, along with tools for monitoring the training process, but are often tied to the deep learning framework. Could a general, easy-to-setup tool for generating standard visualizations provide a sanity check on the learning process?
- Data Version Control: iterative machine learning - May 11, 2017.
ML modeling is an iterative process and it is extremely important to keep track of all the steps and dependencies between code and data. New open-source tool helps you do that.
- You Scored 200 Dollars Off Open Source Data Event in Boston - May 2, 2017.
Use code KDPV17 to save on Postgres Vision, June 26-28, 2017, at the Royal Sonesta Boston. Co-hosted by EnterpriseDB and MIT, the event sponsors include Amazon Web Services, Avnet, credativ, EnterpriseDB, IBM, Microsoft, MIT, NEC, Palisade Compliance, Quest, TechData, and The Executive Council.
- Open Source is Central to the Data Management Conversation, Boston, June 26-28 - Apr 18, 2017.
Open source dominates the data management conversation. Postgres Vision, June 26-28, Boston, explores the business value realized from innovative solutions and strategies. Use code KDPV17 to save.
- DataRobot Webinar, May 2: How Automated Machine Learning is Transforming the Predictive Analytics Landscape - Apr 11, 2017.
Learn how DataRobot automates predictive modeling, and how our platform can deliver these same types of insights and a substantial productivity boost to your machine learning endeavors.
- Help Define the Future of Open Source Data Management, Boston, June 26-28 - Apr 10, 2017.
Postgres Vision, June 26-28, Boston, will be a forum for the sharpest minds in open source as organizations strive to harvest greater strategic value and actionable insight from their data. Use code KDPV17 to save.
- Open Source Toolkits for Speech Recognition - Mar 14, 2017.
This article reviews the main options for free speech recognition toolkits that use traditional Hidden Markov Models and n-gram language models.
- Kobielus Predictions for Data Science in 2017 - Dec 5, 2016.
IBM Data Evangelist James Kobielus predictions for 2017, including key role of data scientists in survival of their companies. Join industry experts for a live #MakeDataSimple Crowdchat on Thursday December 8 at 1:00pm EST.
- Top KDnuggets tweets, Nov 16-22: Top 20 #Python #MachineLearning #OpenSource Projects; Shortcomings of #DeepLearning - Nov 23, 2016.
Top 20 #Python #MachineLearning #OpenSource Projects; Shortcomings of #DeepLearning; What is the Difference Between #DeepLearning and Regular #MachineLearning?; Questions To Ask When Moving #MachineLearning From Practice to Production; How to Choose the Right #Database System
- Top 20 Python Machine Learning Open Source Projects, updated - Nov 21, 2016.
Open Source is the heart of innovation and rapid evolution of technologies, these days. This article presents you Top 20 Python Machine Learning Open Source Projects of 2016 along with very interesting insights and trends found during the analysis.
- Webinar: Breaking Data Science Open, Sep 15 - Sep 12, 2016.
Learn how to drive collaboration and data science teamwork; how to mitigate legal risk through open source assurance and appropriate package selection, and how to democratize innovation through broad access to open data science tools.
- Top Machine Learning Projects for Julia - Aug 19, 2016.
Julia is gaining traction as a legitimate alternative programming language for analytics tasks. Learn more about these 5 machine learning related projects.
- 35 Open Source tools for Internet of Things - Jul 25, 2016.
If you have heard about the Internet of Things many times by now, its time to join the conversation. Explore the many open source tools & projects related to Internet of Things.
Pages: 1 2 3
- Webinar, July 28: How Open Data Science Can Help Analytics Leaders Survive & Thrive in an Era of Accelerating Technology Disruption - Jul 22, 2016.
Continuum Analytics CTO Peter Wang will show how you, an analytics leader, and your team can continuously leverage the latest innovations in data, analytics and computation by joining the big data party in the Open Data Science tent.
- Getting Started with Analytics: What’s the Upfront Investment? - Jul 5, 2016.
Everyone wants to leverage analytics, but should everyone dive into the deep end right away? Heed some sensible advice on getting started with analytics, and assessing the true upfront investment.
- IBM: Open Source Data Scientist - Jun 8, 2016.
IBM seeks an Open Source Data Scientist to assist the sales team with solution sales activities to address a client’s specific challenges implementing Big Data solutions; must be entrepreneurial and self-driven.
- Open Source Machine Learning Degree - Jun 6, 2016.
A set of free resources for learning machine learning, inspired by similar open source degree resources. Find links to books and book-length lecture notes for study.
- 5 Machine Learning Projects You Can No Longer Overlook - May 19, 2016.
We all know the big machine learning projects out there: Scikit-learn, TensorFlow, Theano, etc. But what about the smaller niche projects that are actively developed, providing useful services to users? Here are 5 such projects.
- ODSC East 2016: 3 ways to become a better Data Scientist - Apr 7, 2016.
This year’s 2016 ODSC East brings together the most influential data scientists, practitioners, innovators, and thought leaders in data science and big data, including many open source data science pioneers.
- Data Science Tools – Are Proprietary Vendors Still Relevant? - Mar 25, 2016.
We examine and quantify the dramatic impact of open source tools like R and Python on SAS, IBM, Microsoft, and other proprietary Data Science vendors. We also investigate how open source tools were faring against each other, which are growing, which are falling, and look R versus Python debate.
Pages: 1 2
- Top 10 Data Science Resources on Github - Mar 24, 2016.
The top 10 data science projects on Github are chiefly composed of a number of tutorials and educational resources for learning and doing data science. Have a look at the resources others are using and learning from.
- Journey to Open Data Science, March 23 Webinar - Mar 15, 2016.
Learn how to drive collaboration and teamwork through open data science; mitigate legal risk through indemnification and appropriate package selection; bring advanced analytics to Excel-loving analysts with AnacondaXL.
- Top 10 Data Visualization Projects on Github - Feb 22, 2016.
Github provides a number of open source data visualization options for data scientists and application developers integrating quality visuals. This is a list and description of the top project offerings available, based on the number of stars.
- Opening Up Deep Learning For Everyone - Feb 19, 2016.
Opening deep learning up to everyone is a noble goal. But is it achievable? Should non-programmers and even non-technical people be able to implement deep neural models?
- Auto-Scaling scikit-learn with Spark - Feb 11, 2016.
Databricks gives us an overview of the spark-sklearn library, which automatically and seamlessly distributes model tuning on a Spark cluster, without impacting workflow.
- Spark 2015 Year In Review - Jan 15, 2016.
Apache Spark went through a lot in 2015. Get a solid review from Databricks, the steward organization founded by the creators of Spark and the drivers of its innovation.
- Top 10 Deep Learning Projects on Github - Jan 13, 2016.
The top 10 deep learning projects on Github include a number of libraries, frameworks, and education resources. Have a look at the tools others are using, and the resources they are learning from.
- Top 10 Machine Learning Projects on Github - Dec 14, 2015.
The top 10 machine learning projects on Github include a number of libraries, frameworks, and education resources. Have a look at the tools others are using, and the resources they are learning from.
Pages: 1 2
- R Style Ninjas: New Lifestyle Site for R Enthusiasts - Dec 11, 2015.
New R themed apparel site with several designs generated from R data visualizations. A portion of each purchase goes toward supporting R development.
- Topological Data Analysis – Open Source Implementations - Nov 6, 2015.
Topological Data Analysis (TDA) is making waves in the analytics community lately, but are there open source options available?
- H2O World 50% off for 24 hours only – Open Source Machine Learning - Sep 23, 2015.
Join machine learning industry leaders, H2O customers, and community in a day of H2O training and two days of talks. 50% OFF valid for 24 hours only.
- YCML Machine Learning library on Github - Aug 24, 2015.
YCML is a new Machine Learning library available on Github as an Open Source (GPLv3) project. It can be used in iOS and OS X applications, and includes Machine Learning and optimization algorithms.
- Interview: Stefan Groschupf, Datameer on Why Domain Expertise is More Important than Algorithms - Aug 6, 2015.
We discuss large-scale data architectures in 2020, career path, open source involvement, advice, and more.
- Interview: Reiner Kappenberger, HP Security Voltage on How to Secure Data-in-Motion - Jul 9, 2015.
We discuss the security concerns in Big Data, challenges in securing Big Data locally and over cloud, and open source solutions – Knox and Ranger.
- KDnuggets Interview: Amr Awadallah, CTO & Co-founder, Cloudera on the Secret Sauce of Open Source - Jul 2, 2015.
We discuss the critical success factor for open source projects, entrepreneurial lessons, advice, desired qualities in data scientists and more.
- Interview: Joseph Babcock, Netflix on Genie, Lipstick, and Other In-house Developed Tools - Jun 16, 2015.
We discuss role of analytics in content acquisition, data architecture at Netflix, organizational structure, and open-source tools from Netflix.
- Top KDnuggets tweets, Jun 2-8: Starting salaries for #DataScientists have gone north of $200,000 - Jun 9, 2015.
Starting salaries for #DataScientists have gone north of $200K; Top 20 #Python #MachineLearning #OpenSource Projects; Neural Networks and Deep Learning, free online book (draft); #Airbnb announces #Aerosolve, an #OpenSource #MachineLearning #software package.
- Interview: James Taylor, Salesforce on Apache Phoenix – RDBMS for Big Data - Jun 5, 2015.
We discuss the beginning of Phoenix project, decision of making it open source, relational database layer on HBase, and key reasons for the superior performance of Apache Phoenix.
- Top 20 Python Machine Learning Open Source Projects - Jun 1, 2015.
We examine top Python Machine learning open source projects on Github, both in terms of contributors and commits, and identify most popular and most active ones.
- Open drives Boston Open Data Science Conference, May 30-31 - Apr 25, 2015.
Data science is built on transparency, effort, and the exchange of ideas. Join Open Data Science Conference, Boston, May 30-31, 2015.
- Top /r/MachineLearning Posts, Apr 12-18: Andrew Ng AMA, Autoencoders, and Deep Learning Textbooks - Apr 23, 2015.
Andrew Ng's AMA, a probabilistic view of Autoencoders, open source sentiment analysis, deep learning textbooks, and Airbnb's host matching are all discussed this week on /r/MachineLearning.
- Top KDnuggets tweets, Mar 19-22: Tensor methods for Machine Learning; Tibco survey: Big Data top use cases - Mar 23, 2015.
Tensor methods for #MachineLearning: fast, accurate, scalable, need open-source libs; #DataScience and Reproducibility: Explaining when the experiment does not work; Google #DeepLearning FaceNet is the best ever for recognizing faces; Tibco survey #BigData top use cases: Customer & Experience Analytics, Risk/Threat.
- PredictionIO: Machine Learning Engineer (Evangelist) - Feb 26, 2015.
Are you passionate about machine learning and open source? Do you have the ability to engage other developers and data scientists? If yes, read on ...
- PredictionIO: Machine Learning Evangelist - Feb 4, 2015.
Are you passionate about machine learning and open source? Do you have the ability to engage other developers and data scientists? If yes, read on ...
- Top /r/MachineLearning posts, Jan 11-17 - Jan 18, 2015.
SVMs, open source datasets, Bayesian decision theory, game AI, and deep learning visualizations are all featured in the past week's top /r/MachineLearning posts.
- Top KDnuggets tweets, Dec 17-18: Why Amazon Ratings Might Mislead You; Open Source Tools for Machine Learning - Dec 19, 2014.
Why #Amazon Ratings Might Mislead You: The Story of Herding Effects; Open Source Tools for Machine Learning; #DeepLearning Intelligence Platform - Addressing AML #Terrorism #Financing; #NIPS2014 #MachineLearning Trends: Rapid progress in #DeepLearning.
- Open Source Tools for Machine Learning - Dec 17, 2014.
Open source machine learning software makes it easier to implement machine learning solutions on single computers and at scale, and the diversity of packages provide more options for implementers.
- Open Source Big Data Analytics Platform - Dec 14, 2014.
Download IKANOW open source analytics platform for FREE and start analyzing structured and unstructured data sources. Great for cyber, social, and crisis use cases.
- Mode Playbook for Open Source Analytics - Dec 5, 2014.
Mode Analytics is open-sourcing their internal analysis and data visualizations which can be tailored to common data structures in SQL databases.
- SlamData Open Source Analytics Tool for MongoDB - Dec 4, 2014.
SlamData is an open source SQL-based tool designed to make accessing data in MongoDB easy for developers and non-developers alike with the goal of making application intelligence easier.
- KDnuggets Exclusive: Marten Mickos, SVP, HP on the Role of Open Source in Cloud industry - Nov 15, 2014.
In an exclusive interview with KDnuggets, Marten talks about HP’s Open Source strategy, evolution of Open Source production model, learning from the success of Open Source in Web, trends and more.
- H2O World, Open Source Machine Learning Meeting, Nov 18-19, Mountain View - Oct 27, 2014.
H2O World (Nov 18-19, Mountain View) is where the users of the very popular Open Source Machine Learning Engine H2O gather to share their knowledge and know-how to build Smart Applications.
- Book: Modern Optimization with R - Oct 10, 2014.
Learn the most relevant concepts related to modern optimization methods and how to apply them using multi-platform, open source, R tools in this new book on metaheuristics.
- Mirador, a free tool for visual exploration of complex datasets - Oct 1, 2014.
Mirador is an open-source tool for visual exploration of complex datasets, enabling users to discover correlation patterns and derive new hypotheses from the data. Download Windows and Mac OS X versions from Github.
- Rattle package for Data Mining and Data Science in R - Sep 17, 2014.
Try the newly-released version of Rattle, the open source R package for data mining, and enjoy accessing a huge array of data mining algorithms through a convenient interface.
- Interview: Michael Berthold, President and Founder of KNIME, on Data Mining, Startups, and Visual Workflow - Aug 9, 2014.
We discuss KNIME key features and how it compares to competition, KNIME business model, Pharma, planned development, and transition from an academic project to a company.
- Interview: Sujee Maniyam, Elephant Scale on Why Open Source is So Important for Big Data - Aug 8, 2014.
We discuss the importance of contributing to Open Source, Big Data skills for business managers, Big Data predictions, key qualities sought in data engineers, career advice and more.
- Interview: Sujee Maniyam, Elephant Scale on the Best Free Online Resources to Learn Hadoop - Aug 7, 2014.
We discuss the startup - Elephant Scale, DIY Hadoop learning, best free online resources for learning Hadoop, getting a good job in Big Data, and the experience of authoring a book - Hadoop Illuminated (available for free).
- Top KDnuggets tweets, Aug 1-3: Open Source Data Science Masters plan - Aug 4, 2014.
Open Source #DataScience Masters plan, with courses from Coursera, Stanford, edX; Book: Data Classification: Algorithms and Applications; Markov Chains, key #MachineLearning technique, nice visual explanation; Data Science with #Python: Part 1.
- BIDMach machine learning toolkit - Jul 14, 2014.
BIDMach machine learning toolkit offers "rooflined" (optimized to the limit) compute primitives and competitive performance on learning tasks like regression, clustering, classification, and matrix factorization.
- Interview: Ingo Mierswa, RapidMiner CEO on “Predaction” and Key Turning Points - Jun 27, 2014.
RapidMiner CEO Ingo Mierswa talks about "predaction", reasons for RapidMiner popularity, business source model, analytics to investigate fraud, key turning points, and more.
- The R User Conference, June 30 – July 3, Los Angeles - Jun 19, 2014.
The open source R language is a leading tool for data scientists. Attend useR! conference, the main annual event of the R community, June 30 - July 3, in Los Angeles.
- DLib: Library for Machine Learning - Jun 10, 2014.
DLib is an open source C++ library implementing a variety of machine learning algorithms, including classification, regression, clustering, data transformation, and structured prediction.
- OpenNN, An Open Source Library For Neural Networks - Jun 2, 2014.
OpenNN is an open source class library written in C++ which implements neural networks, and runs on Windows, Apple, or Linux.
- Big Data Landscape, v 3.0, analyzed - May 15, 2014.
We analyze the Big Data Landscape and identify the most popular market segments in Analytics, Infrastructure, Applications, Open Source, and Data Sources categories. It is still early - only 4.5% of companies had exits.
- Oracle Academy – Teaching Students Around The World - Apr 15, 2014.
Oracle academy teaches millions on students around the world, supports Oracle and open-source applications, with courses ranging from computer science for kids to Big Data education.
- Prediction.io open source machine learning server - Apr 10, 2014.
Prediction.io is an open source machine learning server for predictive solutions, such as personalization or recommendations, built on top of scalable frameworks such as Hadoop and Cascading - ready to handle Big Data.
- Open Analytics NYC Summit May 8 - Apr 10, 2014.
Open Analytics Summits are a great place for CTOs, Engineers, Developers, Data Scientists, and others to connect, network, and learn about open source technologies and big data analytics. Early reg by Apr 18 + KDnuggets discount.
- Open Analytics Summit – Chicago, March 27 – KDnuggets discount - Mar 18, 2014.
The Open Analytics Summit, Chicago, March 27 is a great place for CTOs, Engineers, Developers, Data Scientists, and others to network and learn about open source technologies and big data analytics. Exclusive KDnuggets discount - register today!
- useR 2014: attend, sponsor R Analytics and Data Science conference - Feb 1, 2014.
Open invitation to attend and sponsor the main annual event of the R community, the useR! conference to be held in Los Angeles on Jul 1-3.
- Top 10 KDnuggets tweets, Jan 20-21: Data scientists who use OS tools earn more; JHU #DataScience Specialization - Jan 22, 2014.
Data scientists who master open source tools R, Python, Hadoop earn more; JHU offers 9-Course #DataScience Specialization via Coursera; The Life of a Data Scientist, Relentless, but in a Lazy Way; MADlib, a solution for #BigData Analytics
- Open Source Data Science Masters Curriculum - Dec 21, 2013.
A good collection of open source resources for Data Science Masters Curriculum, covering Math, Algorithms, Databases, Data Mining, Machine Learning, Natural Language Processing, Data Analysis and Visualization, and Python.