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Search results for mllib

    Found 100 documents, 12389 searched:

  • MLlib: Apache Spark component for machine learning

    ...its codebase. MLlib has features for classification, regression, collaborative filtering, clustering, and decomposition (SVD and PCA). What’s New in MLlib With the release of Spark 1.0, there are some exciting new features in MLlib. Here is a run-down of all the available machine learning...

    https://www.kdnuggets.com/2014/07/mllib-apache-spark-component-machine-learning.html

  • Machine Learning Model Metrics

    ...bversion of the type system. But MLlib is still being rapidly developed, so this cast operation is just a sign of an incomplete implementation within MLlib. Development on MLlib is very active, but machine learning is an enormous domain for any one library to support. New functionality is being...

    https://www.kdnuggets.com/2018/01/machine-learning-model-metrics.html

  • Top KDnuggets tweets, Apr 9-10: MLlib: Scalable Machine Learning on Spark; Ensemble methods overview

    Most popular @KDnuggets tweets for Apr 9-10 were Top 10 Tweets MLlib: Scalable Machine Learning on Spark (free ebook, 43 pages) #BigData buff.ly/1eluNBP Ensemble methods usually give best results in Machine Learning - An overview of Ensemble Packages in R #rstats buff.ly/1eluEOO Prediction.io open...

    https://www.kdnuggets.com/2014/04/top-tweets-apr9-10.html

  • KDnuggets 14:n19, Big Data Gap; Boundary of Effectiveness; Great interviews; MLlib machine learning

    Date: Jul 30, 2014 Latest KDnuggets News 14:n19, (Jul 30, 2014) Features: Poll Results: Largest Dataset Analyzed surprisingly stable MLlib: Apache Spark component for machine learning MIT CDOIQ Symposium: Where is the Big Data Boundary of Effectiveness? KDnuggets Free Pass to Strata Conference +...

    https://www.kdnuggets.com/2014/07/pub-kdnuggets-14-n19-big-data-gap-boundary-effectiveness-great-interviews-mllib.html

  • Apache Spark Key Terms, Explained

    ...n (email: String, iq: Long, name: String) // Read JSON file and convert to Dataset using the case class val ds = spark.read.json(“...”).as[Person] 5. MLlib Apache Spark provides a general machine learning library -- MLlib -- that is designed for simplicity, scalability, and easy integration with...

    https://www.kdnuggets.com/2016/06/spark-key-terms-explained.html

  • Yahoo! CaffeOnSpark: Distributed Deep Learning on Big Data Clusters

    ...Feature”) val lr_model = lr.fit(lr_input_df) lr_model.write.overwrite( ) .save(conf.outputPath) } Figure 4: Scala application using CaffeOnSpark both MLlib Scala program in Figure 4 illustrates how CaffeOnSpark and MLlib work together: L1-L4 … You initialize a Spark context, and use it to create...

    https://www.kdnuggets.com/2016/02/yahoo-caffe-spark-distributed-deep-learning.html

  • Exclusive Interview: Matei Zaharia, creator of Apache Spark, on Spark, Hadoop, Flink, and Big Data in 2020

    ...ones include DataFrames, machine learning pipelines, R support, and a huge range of new algorithms that we're getting parallel implementations for in MLlib (Apache Spark's scalable machine learning library). GP: Q2. What are the key things to know about Apache Spark? MZ: Here are some lesser-known...

    https://www.kdnuggets.com/2015/05/interview-matei-zaharia-creator-apache-spark.html

  • Top stories in July: Cartoon: Facebook data science experiment and Cats; Data Mining/Data Science “Nobel Prize”

    ...e than “Data Analyst” ? - Jul 1, 2014. When Watson Meets Machine Learning - Jul 2, 2014. Spotting Bad Data Visualizations - Jul 22, 2014. MLlib: Apache Spark component for machine learning - Jul 24, 2014. GraphLab Create: large-scale machine learning platform for graph, structured, and...

    https://www.kdnuggets.com/2014/08/top-news-2014-jul.html

  • Machine Learning with Optimus on Apache Spark

    ...achine Learning is one of the last steps, and the goal for most Data Science WorkFlows. Some years ago the Apache Spark team created a library called MLlib where they coded great algorithms for Machine Learning. Now with the ML library we can take advantage of the Dataframe API and its optimization...

    https://www.kdnuggets.com/2017/11/machine-learning-with-optimus.html

  • Top 15 Scala Libraries for Data Science in 2018

    ...provides highly functional API for Java, Python, and R, but opportunities for Scala are more flexible. The library consists of two separate packages: MLlib and ML. Let’s look at them in more detail one by one. MLlib is an RDD-based library that contains core machine learning algorithms for...

    https://www.kdnuggets.com/2018/02/top-15-scala-libraries-data-science-2018.html

  • R, Python Duel As Top Analytics, Data Science software – KDnuggets 2016 Software Poll Results

    ...oop/Big Data Tools The usage of Hadoop/Big Data tools grew to 39%, up from 29% in 2015 and 17% in 2014), driven mainly by big growth in Apache Spark, MLlib (Spark Machine Learning Library) and H2O, which we included among Big Data tools. Here are the Big Data tools and their share in 2016, 2015,...

    https://www.kdnuggets.com/2016/06/r-python-top-analytics-data-mining-data-science-software.html

  • Top stories for Jul 20-26

    ...s tweets, Jul 18-20: Baby steps in Learning Python; 7 Steps for Learning Data Mining - Jul 21, 2014. Spotting Bad Data Visualizations - Jul 22, 2014. MLlib: Apache Spark component for machine learning - Jul 24, 2014. Interview: Leo Meyerovich, Graphistry on Browser-based Interactive Big Data...

    https://www.kdnuggets.com/2014/07/top-news-week-jul-20.html

  • Top 15 Frameworks for Machine Learning Experts

    …nd recommender systems) and tools for evaluation. Related to the WEKA project, MOA is also written in Java, while scaling to more demanding problems. MLlib (Spark) is Apache Spark’s machine learning library. Its goal is to make practical machine learning scalable and easy. It consists of common…

    https://www.kdnuggets.com/2016/04/top-15-frameworks-machine-learning-experts.html

  • Top KDnuggets tweets, Jul 23-24: 81% of retail firms gather #BigData, only 34% use analytics

    ...t.co/lZK36A6BCe The Journal of Big Data has published its first articles - Hadoop, Mahout, Data Mining, Health Informatics, and more t.co/s08NZbPml2 MLlib: Apache Spark component for machine learning http://t.co/QUaKlLlrld Course: Tools for Discovering Patterns in Data, Sep 8-9 t.co/vEkyJMaPjT...

    https://www.kdnuggets.com/2014/07/top-tweets-jul23-24.html

  • How Big Data Pieces, Technology, and Animals fit together

    ...ing interface, it has higher level libraries to make it more accessible to data scientists. The Machine Learning library built on top of it is called MLlib and there's a distributed graph library called GraphX. Pregel and it's open source twin Giraph is a way to do graph algorithms on billions of...

    https://www.kdnuggets.com/2015/02/how-big-data-pieces-technology-fit-together.html

  • Mastering Advanced Analytics with Apache Spark

    ...lar technical blog posts that provide an introduction to machine learning on Apache Spark, and highlights many of the major developments around Spark MLlib and GraphX. Whether you are just getting started with Spark or are already a Spark power user, it will arm you with the knowledge to be...

    https://www.kdnuggets.com/2018/05/databricks-advanced-analytics-apache-spark.html

  • Open Source Tools for Machine Learning

    ...ithms and useful data types, designed to run at speed and scale. As you’d expect with any Hadoop project, Java is the primary language for working in MLlib, but Python users can connect MLlib with the NumPy library (also used in scikit-learn), and Scala users can write code against MLlib....

    https://www.kdnuggets.com/2014/12/open-source-tools-machine-learning.html

  • A Community Event for Innovative Spark Apps: A Datapalooza Dispatch

    ...htag through a sentiment meter. It enable real-time identification of trends evident in the data. It leverages Spark (Spark Streaming, Spark SQL, and MLLib) to run K-means, DecisionTree, and linear regression machine-learning algorithms against live data to create dynamic visualizations....

    https://www.kdnuggets.com/2015/11/datapalooza-dispatch-kobielus.html

  • 7 Steps to Mastering Apache Spark 2.0">Silver Blog7 Steps to Mastering Apache Spark 2.0

    ...isted and reloaded again, across languages Spark supports (see the blog link below). Fig 11. Machine Learning pipeline In the webinar on Apache Spark MLlib, you will get a quick primer on machine learning, Spark MLlib, and an overview of some Spark machine learning use cases, along with how other...

    https://www.kdnuggets.com/2016/09/7-steps-mastering-apache-spark.html

  • KDnuggets™ News 14:n19, Jul 30

    ...GB range, and confirm the gap between the internet-scale data miners and the rest. MLlib: Apache Spark component for machine learning - Jul 24, 2014. MLlib, the machine learning component of Apache Spark, has developed into a tool that supports many common machine learning algorithms and now comes...

    https://www.kdnuggets.com/2014/n19.html

  • Apache Spark Introduction for Beginners">Silver BlogApache Spark Introduction for Beginners

    ...ted Machine Learning structure above Spark in view of the distributed memory-based Spark architecture. It is, as indicated by benchmarks, done by the MLlib engineers against the Alternating Least Squares (ALS) executions. Spark MLlib is nine times as rapid as the Hadoop disk version of Apache...

    https://www.kdnuggets.com/2018/10/apache-spark-introduction-beginners.html

  • Introduction to Apache Spark

    ...ing status updates posted by users of a web service. MLlib : Spark comes with a library containing common machine learning (ML) functionality, called MLlib. MLlib provides multiple types of machine learning algorithms, including classification, regression, clustering, and collaborative filtering,...

    https://www.kdnuggets.com/2018/07/introduction-apache-spark.html

  • R leads RapidMiner, Python catches up, Big Data tools grow, Spark ignites

    ..., to 2.0% share (55 votes) from 0.2% in 2014 Actian, 345% up, to 2.0% (56 votes), from 0.5% in 2014 Spark, 326% up, to 11.3% (311), from 2.6% in 2014 MLlib, 228% up, to 3.3% (91), from 1.0% in 2014 Alteryx, 79% up, to 5.6% (155), from 3.1% in 2014 Python, 56% up, to 30.3% (837), from 19.5% in 2014...

    https://www.kdnuggets.com/2015/05/poll-r-rapidminer-python-big-data-spark.html

  • Practical Apache Spark in 10 Minutes

    ...lar ML tasks, such as classification and regression, is mainly based on supervised learning algorithms. Among the variety of existing ML tools, Spark MLlib is a popular and easy-to-start library which enables training neural networks for solving the problems mentioned above. In this post, we would...

    https://www.kdnuggets.com/2019/01/practical-apache-spark-10-minutes.html

  • BigData TechCon San Francisco Report: Focus on Spark

    ...n Python using Spark" were well prepared and delivered. The class conveyed a lot of information that allowed people to see how they could using Spark MLLib to perform common machine learning tasks including data wrangling. Here are his slides. There were exhibits from a number of vendors including...

    https://www.kdnuggets.com/2014/11/bigdata-techcon-san-francisco-report-focus-spark.html

  • Top Data Science Courses on Udemy

    ...aborative Filtering Decision Trees & Random Forests Ensemble Learning Tools you will learn Python machine learning libraries Apache Spark and its MLLib package Overview Data Science and Machine Learning with Python is a comprehensive walk-through of how to use Python to analyzing large data...

    https://www.kdnuggets.com/2016/04/top-data-science-courses-udemy.html

  • Dataiku Data Science Studio, now also runs on Apache Spark

    ...4) Machine Learning at Scale Another important element that DSS brings to the table is the ability to train models using both MLlib and Scikit-Learn. MLlib is a Spark library constituted of highly scalable algorithms that can be trained across distributed data. By adding MLlib to the mix, users are...

    https://www.kdnuggets.com/2015/09/dataiku-data-science-studio-now-also-apache-spark.html

  • New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Software Poll">Gold Blog, May 2017New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Software Poll

    ...2017% usage 2016% usage Turi (former Dato/GraphLab) -93% 0.2% 2.4% RapidInsight/Veera -92% 0.2% 3.0% Salford SPM/CART/RF/MARS/TreeNet -89% 0.4% 3.5% MLlib -61% 4.5% 11.6% C4.5/C5.0/See5 -38% 1.2% 2.0% Hadoop: Open Source Tools -32% 15.0% 22.1% Other free analytics/data mining tools -29% 4.8% 6.8%...

    https://www.kdnuggets.com/2017/05/poll-analytics-data-science-machine-learning-software-leaders.html

  • Using Apache SystemML(tm) with Hortonworks Data Platform

    ...l ml = new MLContext(spark) ml.info For this example, Apache Spark MLlib is first used to generate small sample data: %spark2 import org.apache.spark.mllib.util.LinearDataGenerator import org.apache.spark.mllib.linalg.Vector import org.apache.spark.sql._ import...

    https://www.kdnuggets.com/2017/09/ibm-apache-systemml-hortonworks-data-platform.html

  • Scaling Big Data and AI – Spark + AI Summit 2019

    ...e Merrier - Scaling Model Building Infrastructure at Zendesk – Wai Chee Kuo of Zendesk talks about the importance of close collaboration. Using Spark MLlib Models in a Production Training and Serving Platform: Experiences and Extensions – Uber’s Anne Holler talks about how Michelangelo supports...

    https://www.kdnuggets.com/2019/03/databricks-scaling-big-data-ai-spark-ai-summit-2019.html

  • The 3 Biggest Mistakes on Learning Data Science">Gold BlogThe 3 Biggest Mistakes on Learning Data Science

    ...achine learning is a technique with a growing importance, as the size of the datasets experimental sciences are facing…scikit-learn.org Apache Spark: MLlib: Main Guide - Spark 2.4.1 Documentation Due to licensing issues with runtime proprietary binaries, we do not include netlib-java's native...

    https://www.kdnuggets.com/2019/05/biggest-mistakes-learning-data-science.html

  • The Benefits & Examples of Using Apache Spark with PySpark

    ...r notebook, you can learn all these concepts without spending anything on AWS or Databricks platform. You can also easily interface with SparkSQL and MLlib for database manipulation and machine learning. It will be much easier to start working with real-life large clusters if you have internalized...

    https://www.kdnuggets.com/2020/04/benefits-apache-spark-pyspark.html

  • Project Hydrogen, new initiative based on Apache Spark to support AI and Data Science

    ...unifies data processing with machine learning and specifically distributed training on Spark. We want to make every other framework as easy to run as MLlib directly on Spark, whether it is TensorFlow or Horovod, or future popular ML frameworks. It significantly expands the ecosystem of ML...

    https://www.kdnuggets.com/2018/08/databricks-project-hydrogen-apache-spark.html

  • Glimpses & Impressions: Strata Silicon Valley AI + ML Review – Part One

    ...nd H2O are all examples of this kind of approach. Even though H2O does offer its own algorithm library, its platform is still compatible with Spark’s MLlib. Data Robots is compatible with H2O, Spark MLlib, Python and R. Domino Data Lab does integration best because aside from many open source...

    https://www.kdnuggets.com/2016/07/silicon-valley-strata-ai-machine-learning-part-1.html

  • KDnuggets 15th Annual Analytics, Data Mining, Data Science Software Poll: RapidMiner Continues To Lead

    ...nting languages like Perl or SQL) that received at least 1% share in 2014 were Pig 3.5% Alpine Data Labs, 2.7% Pentaho, 2.6% Spark, 2.6% Mahout, 2.5% MLlib, 1.0%   Among tools with at least 2% share, the largest decline in 2014 was for StatSoft Statistica (now part of Dell), down 81%, to 1.7%...

    https://www.kdnuggets.com/2014/06/kdnuggets-annual-software-poll-rapidminer-continues-lead.html

  • XGBoost: Implementing the Winningest Kaggle Algorithm in Spark and Flink

    ...del, you can either predict in local side or in a distributed fashion // testSet is an RDD containing testset data represented as // org.apache.spark.mllib.regression.LabeledPoint val testSet = MLUtils.loadLibSVMFile(sc, inputTestPath) // local prediction // import methods in DataUtils to convert...

    https://www.kdnuggets.com/2016/03/xgboost-implementing-winningest-kaggle-algorithm-spark-flink.html

  • Natural Language Processing Library for Apache Spark – free to use

    ...is collaboration is that the library is a seamless extension of Spark ML, so that for example you can build this kind of pipeline: val pipeline = new mllib.Pipeline().setStages( Array(docAssembler,tokenizer,stemmer,stopWordRemover,hasher,idf,dtree,labelDeIndex))   In this code, the document...

    https://www.kdnuggets.com/2017/11/natural-language-processing-library-apache-spark.html

  • Deep Learning With Apache Spark: Part 2

    ...worth taking a look of it. Some of the advantages of this library compared to the ones that joins Spark with DL are: In the spirit of Spark and Spark MLlib, it provides easy-to-use APIs that enable deep learning in very few lines of code. It focuses on ease of use and integration, without...

    https://www.kdnuggets.com/2018/05/deep-learning-apache-spark-part-2.html

  • Python eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018: Trends and Analysis">Platinum BlogPython eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018: Trends and Analysis

    ...33% 5.7% 8.5% SAS Enterprise Miner -30% 4.3% 6.2% IBM SPSS Modeler -29% 4.9% 6.9% Scala -29% 5.9% 8.3% SAS Base -29% 5.5% 7.7% Alteryx -28% 4.0% 5.7% MLlib -26% 3.8% 5.1% Theano -25% 4.9% 6.5% Deep Learning Tools The share of voters who used Deep Learning tools remained stable, at 33% of voters, vs...

    https://www.kdnuggets.com/2018/05/poll-tools-analytics-data-science-machine-learning-results.html

  • zulily: Machine Learning Engineer

    ...tions: 3+ years of software development experience building and operating high traffic web services and platforms Familiarity with frameworks such as MLlib, H2O, TensorFlow, Theano, Caffe, scikit-learn, Torch Experience with Spark, Hadoop, Pig, MapReduce technologies Ability to explore new ideas...

    https://www.kdnuggets.com/jobs/17/06-07-zulily-machine-learning-engineer.html

  • Sony: Staff Machine Learning Engineer

    ...skills; proficient in data-driven clustering, classification, ranking, and estimation techniques Experience with machine learning frameworks such as MLlib, TensorFlow, Caffe, Torch, or Theano. Experience programming in Python, Java, Scala, or similar modern language Experience with Agile/Scrum...

    https://www.kdnuggets.com/jobs/17/06-12-sony-staff-machine-learning-engineer.html

  • The Two Sides of Getting a Job as a Data Scientist">Gold BlogThe Two Sides of Getting a Job as a Data Scientist

    ...ish. He loves new challenges, working with a good team and having interesting problems to solve. He is part of Apache Spark collaboration, helping in MLlib, Core and the Documentation. He loves applying his knowledge and expertise in science, data analysis, visualization, and automatic learning to...

    https://www.kdnuggets.com/2018/03/two-sides-getting-job-data-scientist.html

  • Data Science & Machine Learning Platforms for the Enterprise

    …em available as self-contained artifacts that are ready to be plugged into any data pipeline. Library vs. Registry Things like scikit-learn and Spark MLlib hold a collection of unique algorithms. That’s a library. A data science & machine learning platform is a registry. It contains multiple…

    https://www.kdnuggets.com/2017/05/data-science-machine-learning-platforms-enterprise.html

  • Accenture: Big Data Engineer

    ...luding Cortana, Watson, TensorFlow), JSON, XML, unstructured data Machine Learning tools, interfaces & Libraries: R, R-Studio, Spark R, sparklyr, MLlib, H2O etc. Hadoop platforms & distributions: Cloudera, Hortonworks, BigInsights, MapR, EMR NoSQL: HBase, Cassandra, MongoDB, CouchDB,...

    https://www.kdnuggets.com/jobs/17/08-09-accenture-big-data-engineer.html

  • Pitfalls in pseudo-random number sampling at scale with Apache Spark

    …hat won’t fit in single memory, ngauss variable above. Luckily, there are set of library functions one can use to generate random data as an RDD from mllib, see randomRDD. But for the remainder of this post, we will use our home made random RDD.   Concept of Partitions As RDDs are distributed…

    https://www.kdnuggets.com/2017/06/pitfalls-random-number-sampling-apache-spark.html

  • Emerging Ecosystem: Data Science and Machine Learning Software, Analyzed">Gold Blog, Jun 2017Emerging Ecosystem: Data Science and Machine Learning Software, Analyzed

    ...prise Miner 162 29.0% 25.9% Alteryx 152 35.5% 23.7% Other free analytics/data mining tools 139 38.8% 51.1% Other Deep Learning Tools 138 68.1% 100.0% MLlib 130 90.8% 66.2% IBM Watson / Watson Analytics 125 52.8% 40.0% Microsoft R Server (former Revolution Analytics) 125 63.2% 55.2% QlikView 121...

    https://www.kdnuggets.com/2017/06/ecosystem-data-science-machine-learning-software.html

  • Dataiku DSS 3.1 – Now with 5 ML Backends & Scala!

    ...l predictive applications within a code-free interface. Users of all skill levels can now leverage HPE Vertica machine learning, H2O Sparkling Water, MLlib, Scikit-Learn, and XGBoost directly from within the visual analysis section of Dataiku DSS 3.1 to apply powerful machine learning algorithms to...

    https://www.kdnuggets.com/2016/08/dataiku-dss-31-machine-learning-backends-scala.html

  • Big Data Key Terms, Explained

    ...plications as a library, or to perform ad-hoc data analysis interactively. Spark powers a stack of libraries including SQL, DataFrames, and Datasets, MLlib for machine learning, GraphX for graph processing, and Spark Streaming. You can combine these libraries seamlessly in the same application. As...

    https://www.kdnuggets.com/2016/08/big-data-key-terms-explained.html

  • Accenture: Data Science Consultant

    ...models Classification and regression techniques Matrix factorization/singular value decomposition Expertise with the following software: Hadoop Spark/MLLib/Graph Mahou Graphlab Other machine learning libraries Pig and UDFs Hive and UDFs Build tools: ant, maven Cloud storage and computation such as...

    https://www.kdnuggets.com/jobs/17/08-09-accenture-data-science-consultant.html

  • KNIME Summit, San Francisco, Sep 14-16, KDnuggets Offer

    ...ytics Platform can be used to build powerful analytics workflows and integrate other data processing and analysis tools such as R, Python, Spark, and MLlib. The main Summit takes place on Thursday/Friday September 15+16 with talks by the KNIME team and over a dozen KNIME users ranging from Under...

    https://www.kdnuggets.com/2016/08/knime-summit-san-francisco-september.html

  • Kabbage: Machine Learning Engineer

    ...rk, Hive, and Presto. You have strong expertise in machine learning, and are familiar with one or more of the common frameworks such as scikit-learn, mllib, and tensorflow. You have a Ph.D. in CS, statistics, or some other quantitative field or an M.S. and 2 years of experience in the software...

    https://www.kdnuggets.com/jobs/16/12-12-kabbage-machine-learning-engineer.html

  • Apache Spark: O’Reilly Certification, EU Training, University Program

    ...data science, and machine learning – or other academic areas that leverage Spark, such as genomics and physical sciences. Please contact: training-feedback@databricks.com Related: Apache Spark, the hot new trend in Big Data 18 essential Hadoop tools MLlib: Apache Spark component for machine...

    https://www.kdnuggets.com/2014/09/apache-spark-training-certification-program.html

  • LeapYear: Lead Data Scientist

    ...t Expert knowledge of data analytics architecture, including knowledge of RDBMS, ETL, BI, and advanced machine learning libraries (e.g. Scikit-learn, MLlib, TensorFlow, Theano, Caffe), etc. Deep understanding of data science process, machine learning, data architecture, and IT systems Experience...

    https://www.kdnuggets.com/jobs/17/03-15-leapyear-lead-data-scientist.html

  • Dask and Pandas and XGBoost: Playing nicely between distributed systems

    ...le often ask what machine learning capabilities Dask provides, how they compare with other distributed machine learning libraries like H2O or Spark’s MLLib. For gradient boosted trees the 200-line dask-xgboost package is the answer. Dask has no need to make such an algorithm because XGBoost already...

    https://www.kdnuggets.com/2017/04/dask-pandas-xgboost-playing-nicely-distributed-systems.html

  • A “Weird” Introduction to Deep Learning">Silver BlogA “Weird” Introduction to Deep Learning

    ...ish. He loves new challenges, working with a good team and having interesting problems to solve. He is part of Apache Spark collaboration, helping in MLlib, Core and the Documentation. He loves applying his knowledge and expertise in science, data analysis, visualization, and automatic learning to...

    https://www.kdnuggets.com/2018/03/weird-introduction-deep-learning.html

  • The Data Scientist’s Guide to Apache Spark™

    ...hambers. Download this eBook to: Learn the fundamentals of advanced analytics and receive a crash course in machine learning. Get a deep dive on MLlib, the primary machine learning package in Spark's advanced analytics toolkit. Discover key use cases for implementing recommendation engines,...

    https://www.kdnuggets.com/2018/02/data-scientists-guide-apache-spark.html

  • Deep Learning Made Easy with Deep Cognition

    ...g Data, Data Science, Machine Learning and Computational Cosmology. Since 2015, he has been part of the collaboration of Apache Spark in the Core and MLlib library. He’s Chief Data Scientist at Iron performing distributed processing, data analysis, machine learning and directing data projects for...

    https://www.kdnuggets.com/2017/12/deep-learning-made-easy-deep-cognition.html

  • Deep Learning With Apache Spark: Part 1

    ...I, so is worth taking a look of it. Some of the advantages of this library compared to the ones I listed before are: In the spirit of Spark and Spark MLlib, it provides easy-to-use APIs that enable deep learning in very few lines of code. It focuses on ease of use and integration, without...

    https://www.kdnuggets.com/2018/04/deep-learning-apache-spark-part-1.html

  • Apache Spark : Python vs. Scala">Silver BlogApache Spark : Python vs. Scala

    ...r versions. But for NLP, Python is preferred as Scala doesn’t have many tools for machine learning or NLP. Moreover for using GraphX, GraphFrames and MLLib, Python is preferred. Python’s visualization libraries complement Pyspark as neither Spark nor Scala have anything comparable.   Code...

    https://www.kdnuggets.com/2018/05/apache-spark-python-scala.html

  • U. Chicago Center for Data Science and Public Policy: Postdoc in Natural Language Processing

    ...rd, phrase, and document embeddings Experience building classifiers on word embeddings, especially with limited negative cases Experience with Spark, MLLib, and processing text at scale Strong programming skills (ideally in Python) Strong database skills Data analysis, machine learning, data mining...

    https://www.kdnuggets.com/jobs/16/06-29-dsapp-postdoc-natural-language-processing-b.html

  • Detecting Breast Cancer with Deep Learning

    ...ish. he loves new challenges, working with a good team and having interesting problems to solve. He is part of Apache Spark collaboration, helping in MLLib, Core and the Documentation. He loves applying his knowledge and expertise in science, data analysis, visualization and data processing to help...

    https://www.kdnuggets.com/2018/05/detecting-breast-cancer-deep-learning.html

  • Another Day in the Life of a Data Scientist

    ...osmology. I have a passion for science, philosophy, programming and data science. Since 2015, I've collaborated with Apache Spark in the Core and the MLlib library. I'm the Chief Data Scientist at Iron performing distributed processing, data analysis, machine learning and directing data projects...

    https://www.kdnuggets.com/2017/12/another-day-life-data-scientist.html

  • Citrix: Machine Learning / AI Architect – Research & Development

    ...pothesis testing, probability theory, etc.) Strong hands-on experience with statistical packages and ML libraries (e.g. R, Python scikit learn, Spark MLlib, etc.) Experience in effective data exploration and visualization (e.g. Excel, Power BI, Tableau, Qlik, etc.) Experience in developing and...

    https://www.kdnuggets.com/jobs/17/11-07-citrix-machine-learning-ai-architect.html

  • How LinkedIn Makes Personalized Recommendations via Photon-ML Machine Learning tool">Silver BlogHow LinkedIn Makes Personalized Recommendations via Photon-ML Machine Learning tool

    ...l parameters to be learned from the data is huge (e.g. tens of billions). If we naively train the model using standard machine learning methods (e.g. MLlib provided by Spark), the network communication cost for updating the large number of parameters is too high to be computationally feasible. The...

    https://www.kdnuggets.com/2017/10/linkedin-personalized-recommendations-photon-ml.html

  • Top Machine Learning Libraries for Javascript

    ...t to let me know, Python is not the only option. There are Java-based tools (Deeplearning4j, Weka), those integrated with Apache Spark and/or Hadoop (MLlib, Mahout), C++ solutions (TensorFlow is written in C++, as are many others in the Python ecosystem), and even those for Clojure, F#, Rust, and a...

    https://www.kdnuggets.com/2016/06/top-machine-learning-libraries-javascript.html

  • Data Scientist Guide to Apache Spark

    ...hambers. Download this eBook to: Learn the fundamentals of advanced analytics and receive a crash course in machine learning. Get a deep dive on MLlib, the primary machine learning package in Spark’s advanced analytics toolkit. Discover key use cases for implementing recommendation engines,...

    https://www.kdnuggets.com/2017/10/databricks-data-scientist-guide-apache-spark.html

  • A Day in the Life of a Data Scientist">Silver BlogA Day in the Life of a Data Scientist

    ...ngs - including not just emails and meetings. I could be using Hive to pull data, using it to merge data (or using Impala), I could be using PySpark (Mllib) to make churn models or do k means clustering. I could be pulling data in an excel file to make summaries and I could be making data...

    https://www.kdnuggets.com/2017/11/day-life-data-scientist.html

  • An Inside Update on Natural Language Processing

    ...with VW, and then read the resulting model back in to Scala and serialize the whole thing. Having said that, we are now exploring using toolkits like MLlib and H2O (for standard model types) since they integrate natively with with Spark jobs. We also have our own proprietary models, which are...

    https://www.kdnuggets.com/2016/06/inside-update-natural-language-processing.html

  • A Guide to Understanding AI Toolkits

    ...source tools include R and Python; the big data platforms Apache Spark and Hadoop also have their own toolkits for parallel machine learning (Spark’s MLLIB and Apache Mahout). Currently, Python is emerging as the most popular programming language for data science in industry, thanks to projects...

    https://www.kdnuggets.com/2017/08/guide-understanding-ai-toolkits.html

  • PredictionIO: Machine Learning Engineer (Evangelist)

    ...ta scientists from Google, Palantir and world class universities including Stanford and Berkeley, on a cutting edge tech stack: Scala, Hadoop, Spark, MLlib. Build something truly great - it's not Skynet but it is the MySQL of machine learning! We are looking for a Machine Learning Engineer...

    https://www.kdnuggets.com/jobs/15/02-26-predictionio-machine-learning-engineer-b.html

  • PredictionIO: Machine Learning Evangelist

    ...ta scientists from Google, Palantir and world class universities including Stanford and Berkeley, on a cutting edge tech stack: Scala, Hadoop, Spark, MLlib. Build something truly great - it's not Skynet but it is the MySQL of machine learning! We are looking for a Machine Learning Evangelist: Good...

    https://www.kdnuggets.com/jobs/15/02-04-predictionio-machine-learning-evangelist.html

  • Surfing the Big Data Wave at H2O World

    ...n be run on Hadoop (YARN) and there is a project (Sparkling Water) to run H2O as an application on top of Spark. They plan to interoperate with Spark MLLib. Arno Candel gave a comprehensive tutorial on doing deep learning using H2O. Free booklets on using R and on running deep learning are...

    https://www.kdnuggets.com/2014/11/surfing-big-data-wave-h2o-world.html

  • Interview: Ted Dunning, MapR on Apache Mahout & Technology Landscape in ML

    ...that it compiles linear algebra expressions into efficient programs for back-ends like Spark (or H2O). Clearly also, H2O has a huge lead over Spark's MLLib in terms of numerical performance and sophisticated learning algorithms. Mahout is also the only system that fully supports indicator-based...

    https://www.kdnuggets.com/2015/03/interview-ted-dunning-apache-mahout-machine-learning.html

  • Machine Learning Table of Elements Decoded

    ...ckages in Java (Green): Weka Mallet Knime RapidMiner Encog ELKI DL4J Machine Learning Packages for Big Data (Dark Blue): Mahout Conjecture SAMOA Oryx MLLib MLbase Machine Learning Packages in Lua/JS/Clojure (Red): Torch April ConvNetJS jsLDA Machine learning library for Node.js clj-ml Machine...

    https://www.kdnuggets.com/2015/03/machine-learning-table-elements.html

  • PredictionIO (Open Source Version) vs Microsoft Azure Machine Learning

    ...Microsoft’s algorithms will be used by default (supposedly the same as those used in Xbox, Bing, Cortana...), whereas PredictionIO comes with Spark’s MLlib library, deep learning library and other JVM-based algorithm libraries. You can still use other libraries or your own custom algorithms....

    https://www.kdnuggets.com/2015/03/predictionio-open-source-vs-microsoft-azure-machine-learning.html

  • GBDC: Real-Time Big Data Developer (focus on Spark, Storm, Flink, Kafka), Santa Clara, Apr 23-24

    ...day one, we will introduce Spark Core Concepts, Scala , SBT & Labs. Day two will consists of Spark SQL, Spark Streaming, Machine Learning , Spark MLlib, Data Frames, Advanced Spark & hands-on sessions. Also, Technical talks on Storm, Flink , Kafka & Lambda architecture will be covered....

    https://www.kdnuggets.com/2015/03/gbdc-real-time-big-data-developer-santa-clara-april.html

  • R and Hadoop make Machine Learning Possible for Everyone

    ...to datastores (Hbase, Cassandra, Redis, Voldermort, etc.), to schedulers (Oozie, Cascading, Scalding, etc.), and finally to Machine Learning (Mahout, MLlib, H2O, etc.) among many other applications. Unfortunately, there is not a simple way to see all of these technologies and easily install with...

    https://www.kdnuggets.com/2014/11/r-hadoop-make-machine-learning-possible-everyone.html

  • Skyhigh Networks: Data Scientist – Big Data

    ...ce in Java or Scala, 2+ years programming experience with scripting languages such as Perl or Python Working knowledge of Map-Reduce and Hive, (Spark MLLib a strong plus) Passion for working with big data coupled with professional experience in data mining, statistical analysis, predictive modeling...

    https://www.kdnuggets.com/jobs/14/09-16-skyhighnetworks-data-scientist.html

  • MADlib: Big Data Machine Learning in SQL for Data Scientists

    ...cludes researchers from Stanford and University of Florida. Learn more and download at madlib.net/ Mayur Rustagi on LinkedIn also suggested a related MLlib - machine learning library - developed on top of Apache Spark. It leverages the in-memory capabilities of Spark for iterative processing often...

    https://www.kdnuggets.com/2014/01/madlib-big-data-machine-learning-sql-for-data-scientists.html

  • KDnuggets™ News 14:n09, Apr 16

    ...ook - Interviews with Data Scientists and CEO, free download; An Introduction to Deep Learning in Java Top KDnuggets tweets, Apr 9-10 - Apr 11, 2014. MLlib: Scalable Machine Learning on Spark (free ebook); Ensemble methods usually give best results in Machine Learning - an overview; Prediction.io...

    https://www.kdnuggets.com/2014/n09.html

  • Alpine Data expects faster, easier Data Science with Spark

    ...rs of magnitude. But it comes with a number of goodies that are very appealing to the data scientist. The addition of a machine learning library with MLLib provides the potential for a general framework for advanced analytics on big data; Scala is a very natural basis for doing data science...

    https://www.kdnuggets.com/2014/03/alpine-data-labs-certified-spark-faster-easier-data-science.html

  • Apache Spark, the hot new trend in Big Data

    ...se Python. Spark has generality or platform compatibility in both directions meaning it integrates nicely with SQL engines (Shark), Machine Learning (MLlib), and streaming (Spark Streaming) without requiring new software installed on the cluster using Hadoop’s new YARN cluster manager.   At...

    https://www.kdnuggets.com/2014/04/apache-spark-hot-new-trend-big-data.html

  • OpenML: Share, Discover and Do Machine Learning

    …projects in machine learning, deep learning and also big data analytics during her study at NYU. With the background in Financial Engineering for undergrad study, she is also interested in business analytics. Related: Prediction.io open source machine learning server MLlib: Apache Spark component…

    https://www.kdnuggets.com/2014/08/openml-share-discover-do-machine-learning.html

  • YARN is All the Rage at Hadoop Summit 2014

    ...ht require a separate processing framework for each stage, but the demo showed how to leverage the versatility of the Spark runtime to combine Shark, MLlib, and Spark Streaming and the same time perform all of the processing by a single, small program. This arrangement allows us to reuse code and...

    https://www.kdnuggets.com/2014/06/yarn-all-rage-hadoop-summit.html

  • Strata + Hadoop World 2015, London, May 5-7, Watch Live

    ...iness problems (eg fraud identification) The move of Apache Spark through the hype cycle, picking up vast amounts of ML functionality on the way (via MLlib) Data Science focused cloud environments (AzureML is the tip of the iceberg here) NoSQL dominating the world of databases Internet of Things...

    https://www.kdnuggets.com/2015/05/strata-hadoop-world-2015-london-may-watch-live.html

  • Gaming Analytics Summit 2015, San Francisco – Day 1 Highlights

    ...insights on the player behavior. He explained the data architecture, which included Amazon web services, Apache Spark, Apache Kafka, SparkSQL, R and MLlib. For BI Services, Tableau, Vertica, and Redshift are used. The future plans include providing real time insights and visualizations using Spark...

    https://www.kdnuggets.com/2015/05/gaming-analytics-summit-san-francisco-highlights-day1.html

  • A Look Back on the 1st Three Months of Becoming a Data Scientist

    ...ss. Between this past summer course I took and now, Spark has totally changed the paradigm they use for Machine Learning. Gone are LabeledPoints with MLLib and here to replace them are Spark DataFrames, SparkSQL and ML. So what does this all mean for you? It means that if you’re actively learning...

    https://www.kdnuggets.com/2016/01/look-back-1st-three-months-data-scientist.html

  • Quad Analytix: Data Scientist

    ...ession, Deep Learning) and other related topics. Strong coding skills in Python/Java. Working knowledge of NoSQL stack a plus. Familiarity with Spark/MLlib a strong plus.   OTHER CHARACTERISTICS: Strong communication skills and ability to work effectively independently and in teams (local and...

    https://www.kdnuggets.com/jobs/16/01-08-quadanalytix-data-scientist.html

  • Research Leaders on Data Mining, Data Science and Big Data key advances, top trends

    ...for commoditization of data analytics. While there is a long way to go, these systems make it possible to mine big(ger) data. Examples include Spark MLlib and Petuum for general mining/learning tasks, GraphX for graph-parallel computations, Arabesque for graph pattern mining, various systems to...

    https://www.kdnuggets.com/2016/01/research-leaders-data-science-big-data-top-trends.html

  • Top Spark Ecosystem Projects

    ...on Spark Streaming - an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of live data streams MLlib - Spark's machine learning library, consisting of common learning algorithms and utilities, including classification, regression, clustering,...

    https://www.kdnuggets.com/2016/03/top-spark-ecosystem-projects.html

  • Spark 2.0 Preview Now on Databricks Community Edition: Easier, Faster, Smarter

    ...ary ML API: With Spark 2.0, the spark.ml package, with its “pipeline” APIs, will emerge as the primary machine learning API. While the original spark.mllib package is preserved, future development will focus on the DataFrame-based API. Machine learning pipeline persistence: Users can now save and...

    https://www.kdnuggets.com/2016/05/spark-2-preview-databricks-community-edition.html

  • Ravel: Senior Data Scientist

    ...stering, and sequence classification algorithms Familiarity with libraries and tools such as OpenNLP, StanfordNLP, Mallet, Factorie, word2vec, Spark, MLLIB, H2O, and Weka Some exposure to or experience with Scala or Java is helpful. Python and SQL are also supported in our environment. Strong...

    https://www.kdnuggets.com/jobs/16/04-06-ravellaw-senior-data-scientist.html

  • Portable Format for Analytics: moving models to production

    ...ski, DMG. As a data scientist today, you have a lot of tools to choose from. Thousands of R packages are available on CRAN, libraries like Mahout and MLlib bring machine learning to the Hadoop/Spark ecosystem, and Python has a growing set of analysis tools based on Numpy, Scipy, and Scikit-Learn....

    https://www.kdnuggets.com/2016/01/portable-format-analytics-models-production.html

  • Beginners Guide: Apache Spark Machine Learning with Large Data

    ...aries import org.apache.spark.ml.feature.{HashingTF, Tokenizer} import org.apache.spark.ml.classification .LogisticRegression import org.apache.spark.mllib.evaluation .BinaryClassificationMetrics import org.apache.spark.ml.Pipeline 5. Parsing XML We need to extract Body, Text and Tags from the...

    https://www.kdnuggets.com/2015/11/petrov-apache-spark-machine-learning-large-data.html

  • To Code or Not to Code with KNIME

    ...ot also add nodes that allow the integration of code that runs directly on Hadoop as well? With version 2.12, KNIME has nodes to encapsulate calls to MLlib and enables Spark operations to be modeled. A special Spark Scripting node encapsulates functionality that has not yet been exposed as a native...

    https://www.kdnuggets.com/2015/07/knime-code-not-code.html

  • Introduction to Big Data with Apache Spark

    …and with improved performance. PageRank Algorithm – a popular graph processing algorithm outperforms in Apache Spark environment over map-reduce. 2) MLLib – Machine learning library built on the top of Spark and supports many complex machine learning algorithms which runs 100x faster than…

    https://www.kdnuggets.com/2015/06/introduction-big-data-apache-spark.html

  • Interview: Brian Kursar, Toyota on Big Data & Advanced Analytics – Cornerstones of Innovation

    ...ueprint for Big Data and Advanced Analytics at Toyota. Our platform is built primarily on Open Source technologies. In production, we are using Spark MLLib, Core, and SparkSQL, Stanford NLP, Solr for Data Discovery, Apache HBase, and D3 for visualizations. We also recently started using Alpine. AR:...

    https://www.kdnuggets.com/2015/07/interview-brian-kursar-toyota-big-data-advanced-analytics.html

  • SFBayACM Silicon Valley Data Science Camp 2015

    ...proposed sessions on the Campsite. The keynote will be "Spark for Data Science, Big and Small", given by Joseph Bradley, a Spark Committer working on MLlib at Databricks. The optional morning tutorial ($40) will be "Intro to R Mining of Big Data", by Joseph Rickert of Microsoft. Sessions in past...

    https://www.kdnuggets.com/2015/09/sfbayacm-data-science-camp-2015.html

  • SFBayACM Silicon Valley Data Science Camp, Oct 24 2015

    ...proposed sessions on the Campsite. The keynote will be "Spark for Data Science, Big and Small", given by Joseph Bradley, a Spark Committer working on MLlib at Databricks. The optional morning tutorial ($40) will be "Intro to R Mining of Big Data", by Joseph Rickert of Microsoft. Sessions in past...

    https://www.kdnuggets.com/2015/10/sfbayacm-data-science-camp-2015.html

  • The Big Data Ecosystem is Too Damn Big">2016 Silver BlogThe Big Data Ecosystem is Too Damn Big

    ...d Kafka, in various combinations, vie for mindshare. And while big data machine learning started with Apache Mahout, it seems to be shifting to Spark MLlib and elsewhere. Then there are the permutations. For example, Spark can run on YARN, Hadoop 2.0’s resource manager. But it doesn’t have to. And...

    https://www.kdnuggets.com/2016/06/big-data-ecosystem-too-damn-big.html

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