Meetups on DataScience.LA

CatBoost: Distributed Training, Uncertainty Estimation and Other News

Wed, 10 Mar 2021 08:36:43 -0800

Update: Video Recording:

▶ LA Data Science Meetup, March 30, 2021 - Stanislav Kirillov: CatBoost

Slides: here

Recent Developments in LightGBM

Tue, 15 Dec 2020 01:53:23 -0800

Update: Video recording:

▶ LA Data Science Meetup, Jan 12, 2021 - James Lamb: Recent Developments in LightGBM

Slides and code: here.

SatRday LA - R Conference Announcement

Mon, 28 Jan 2019 01:25:06 -0800

Come and have fun with local useRs at SatRday LA on April 6, 2019. This is the first SatRday in LA, and the second in the states. If you have not heard of SatRday, it is a one-day affordable, inclusive, non-profit R conference organized by local R users.

Meetup: Machine Learning Best Algorithms: Gradient Boosting Machines (GBM)

Fri, 20 Jul 2018 17:43:00 -0700

Update_1: Slides for the 4 talks added below (at each talk section separately).

Update_2: Photos from the meetup and a short description of the event added below (at the bottom of the post).

Update_3: Video recording of the meetup here:

R Meetup with Hadley Wickham

Sat, 28 Oct 2017 12:57:13 -0700

Update: Video of the 2nd half of the talk is here (1st half was not recorded, sorry):

This video is no longer available on YouTube (original link).

In our next meetup, we’ll have Hadley (I think no introduction needed).

Packages made easy
by Hadley Wickham

Meetup: Machine Learning in Production with Szilard Pafka

Fri, 28 Apr 2017 00:55:25 -0700

Update: Video recording of the meetup here:

▶ Machine Learning in Production with Szilard Pafka

Slides here:

Meetup: Stream processing with R in AWS

Wed, 08 Mar 2017 09:29:48 -0800

Update: Slides click here.

Video recording here:

This video is no longer available on YouTube (original link).

Stream processing with R in AWS
by Gergely Daróczi

Abstract: R is rarely mentioned among the big data tools, although it’s fairly well scalable for most data science problems and ETL tasks. This talk presents an open-source R package to interact with Amazon Kinesis via the MultiLangDaemon bundled with the Amazon KCL to start multiple R sessions on a machine or cluster of nodes to process data from theoretically any number of Kinesis shards. Besides the technical background and a quick introduction on how Kinesis works, this talk will feature some stream processing use-cases at CARD.com, and will also provide an overview and hands-on demos on the related data infrastructure built on the top of Docker, Amazon ECS, ECR, KMS, Redshift and a bunch of third-party APIs.

Meetup: No-Bullshit Data Science

Fri, 17 Feb 2017 11:49:40 -0800

Update: Slides here:

Slides: https://speakerdeck.com/szilard/machine-learning-meetup-febr-2017

Our next meetup:

No-Bullshit Data Science
by Szilard Pafka

Abstract: While extracting business value from data has been performed by practitioners for decades, the last several years have seen an unprecedented amount of hype in this field. This hype has created not only unrealistic expectations in results, but also glamour in the usage of the newest tools assumably capable of extraordinary feats. In this talk I will apply the much needed methods of critical thinking and quantitative measurements (that data scientists are supposed to use daily in solving problems for their companies) to assess the capabilities of the most widely used software tools for data science. I will discuss in details two such analyses, one concerning the size of datasets used for analytics and the other one regarding the performance of machine learning software used for supervised learning.

PyDSLA: PyMC3 and jobs.py

Thu, 19 Jan 2017 21:15:07 -0800

Update: Video recording of the meet up here:

This video is no longer available on YouTube (original link).

Come to the PyDSLA January Meetup to hear talks about PyMC3 and jobs.py!

For this event we are incredibly fortunate to have two incredibly speakers give really interesting talks.

Meetup: Machine Learning at Google

Thu, 24 Nov 2016 22:27:11 -0800

UPDATE: The meetup “sold out” in record time (35 minutes!) from announcing it on our mailing list. There are more than 250 people on the waiting list now.

Machine Learning at Google
#

Come and hear about a range of the work that is being done in Google’s Los Angeles office in the area of machine learning:

How-to organize a satRday conference (v0.1)

Fri, 18 Nov 2016 13:31:13 -0800

It has been over 2 months since the first satRday conference ended and I shared some quick impressions on that, where I also promised a follow-up post on my experiences as ending up being the main organizer of the event – this is what you are reading now. Although the idea was born at the EARL Boston conference last year, and I decided to take part in the project while living in Los Angeles – the conference took place in Budapest after all as logistics seemed to be easier there thanks to my closer relationship to the Hungarian R User Group.

PyDSLA: Talks from the LA Data Science Community

Fri, 14 Oct 2016 15:29:39 -0700

DATE AND TIME

Wed, November 2, 2016
6:30 PM – 9:30 PM PDT
Come to the PyDSLA November Meetup to hear talks from the community!

In the last month, the organizers of the PyDSLA Meetup sent out a call for speakers, and the community answered with a number of great members coming forward willing and able to talk about some of the cool ways they are using the Python Data Science ecosystem to do cool stuff.

DSSTNE: A New Deep Learning Framework for Large Sparse Datasets

Fri, 14 Oct 2016 15:29:22 -0700

Update: This event has ended. Slides are available here.
#

Update: Video recording by Carl Mullins:
#

This video is no longer available on YouTube (original link).

XGBoost: meetup announcement

Thu, 19 May 2016 10:06:17 -0700

XGBoost is a fantastic open source implementation of Gradient Boosting Machines, one of the most accurate general purpose supervised learning algorithms. With interfaces from both R and Python among others, it has become a favorite tool in Kaggle competitions, and it’s also widely used in real-world applications. In this meetup we’ll have a talk from the best person on the topic,Tianqi Chen, main author of XGBoost.

PyDSLA: The Nitty Gritty of Advanced Analytics Using Apache Spark in Python

Mon, 18 Apr 2016 12:57:06 -0700

Video Available Now:

▶ PyDSLA The Nitty Gritty of Advanced Analytics Using Apache Spark in Python May 5, 2016

Talk by Miklos Christine, solutions engineer at Databricks

What has Kaggle learned from 2 million machine learning models?

Fri, 05 Feb 2016 16:36:40 -0800

What has Kaggle learned from 2 million machine learning models?

Anthony Goldbloom, founder and CEO of Kaggle

UPDATE:Video recording of the talk available here

Kaggle is a community of almost 450K data scientists who have built almost 2MM machine learning models to participate in our competitions. Data scientists come to Kaggle to learn, collaborate and develop the state of the art in machine learning. This talk will cover some of the lessons on winning techniques we have learned from the Kaggle community.

PyDSLA: Erin LeDell, Presents Intro to Machine Learning with H2O and Python

Tue, 05 Jan 2016 09:30:53 -0800

Join PyDSLA for a talk by Erin LeDell Intro to Machine Learning with H2O and Python

Get your tickets HERE

Summary:

This workshop will provide an overview of how to use H2O, the scalable open source machine learning library, from Python. The core algorithms of H2O are implemented in Java, however, fully-featured APIs are available in R, Python, Scala, and also through a web interface. The focus of this hands-on workshop will be the “h2o” Python module.

LA Data Warehouse, Business Intelligence and Analytics - Jihoon Son

Tue, 05 Jan 2016 09:30:37 -0800

Tickets available HERE

Talk:

Jihoon Son Presents - Introduction to Apache Tajo: Future of Data Warehouse

Abstract: Apache Tajo is a data warehouse system for Web-scale data. It provides virtual integration of a multitude of diverse data sources, thereby facilitating easy and rapid data integration which has been regarded as an essential, but heavy step in business intelligence. In addition, it has a fault-tolerable distributed query engine for accelerating query speed. With the “query federation” and “distributed processing” capacities, Tajo is capable of providing users with reliable and efficient analysis of Web-scale data spread on multiple sources. I will introduce Apache Tajo including its overall architecture, current state and challenges, and discuss advantages what Tajo can bring to users. In addition, I will give a brief demo of Tajo.

Meetup Summary - Winning Data Science Competitions

Fri, 13 Nov 2015 12:13:40 -0800

If you’ve never heard of kaggle, I guess the first question I have to ask is “how did you end up on DataScience.LA?” :)

Kaggle is one of the foremost machine learning competition websites on the internet. Companies from GE to Criteo and everything in between create competitions. These competitions are in the form of a dataset, ranging from small to relatively large (up to many many gigabytes), a stated goal (such as predicting an event or finding a numeric value) and an evaluation criteria. The Kaggle community has grown in the last few years, so that now competitions often host thousands of participants!

Announcing Meetup! Lior Abraham of Inter|Ana

Tue, 23 Jun 2015 17:10:06 -0700

Click HERE to sign up on Eventbrite!

This is the second event of the new Data Warehouse, Business Intelligence and Analytics meetup.

Talks:

1. Eduardo Arino de la Rubia: MySQL to Vertica with Tungsten Replicator

In this very (very) short talk, I will discuss how you can, for free, stream your MySQL data to a Vertica Community Edition cluster, and do near real-time analytics on up to 1TB of data.

PyDSLA: Dato CEO, Carlos Guestrin, Presents Dato

Tue, 05 May 2015 08:40:40 -0700

*** EVENTBRITE LINK HERE ***

PyDSLA - Dato: A Platform for Practical, Large-Scale Machine Learning

Join PyDSLA for a talk by Carlos Guestrin about Presents Practical, Large-Scale Machine Learning in python.

Summary:

Data Science is perhaps the hottest profession on the market today. Folks with backgrounds ranging from Statistics and Physics to Engineering and Computer Science are eager and excited to transition to this field. However, designing and deploying data analysis and machine learning apps at scale is a significant challenge to overcome: For some folks, machine learning algorithms and methods can be obscure, too mathy, and disconnected from practice. For others, writing and deploying scalable software requires significant effort, which distracts them from focusing on their deep analytic efforts.

Data Science @ Whisper

Mon, 30 Mar 2015 09:23:55 -0700

Where were you on the evening of Monday, March 23rd? Do you remember what you were up to? If you were one of the over 100 attendees to the latest installment of Szilard’s Data Science Meetup, you definitely remember! You were at Cross Campus Santa Monica, receiving a teaser on fundamentals of probabilistic programming by LA ML Meetup founder Rob Zinkov along with a detailed master class on modern machine learning architectures and approaches by Los Angeles’ own Whisper!

Data Science/Statistics/R @Google

Fri, 27 Feb 2015 11:50:48 -0800

This meetup will be hosted by Google and we’ll have Peter Lipman and Pete Meyer talk about the data science/statistics projects they have been working on at Google.

Human Evaluation Comparisons: Common Framework with Applications

We designed a study to determine whether being on device influenced a quality evaluator’s perception of ads quality. Here, we present a common framework, developed into an internal R package, that was used to analyze the study.

Yihui Xie presents HTML Widgets

Fri, 13 Feb 2015 10:35:31 -0800

The Shiny framework, by RStudio, is growing in popularity as a tool that makes it easy for R developers to leverage the web as a deployment platform for sharing their analysis. However, since the very earliest release of Shiny, the development group has been bombarded with the same series questions over and over again, questions like “Does it work with d3.js?” and “Can I use JavaScript in Shiny?”

Joe Cheng presents Shiny

Fri, 13 Feb 2015 10:25:38 -0800

The Shiny framework is a web application framework for the R programming language, designed by Joe Cheng, to help R programmers turn their analysis into interactive web applications. Fortunately, it does without requiring that the R programmer know HTML, CSS or JavaScript - greatly widening the possible audience of users. At the January DataScience.LA R Meetup, we were fortunate to have Joe Cheng, Software Engineer at RStudio and original architect of Shiny present an introduction to Shiny.

PyDSLA - Blaze: Connecting analysts to big computation

Sat, 07 Feb 2015 15:35:01 -0800

Join PyDSLA for a talk by Matthew Rocklin about the high level APIs being developed for Python for expressive data manipulation and analysis.

Summary:

Pandas and NumPy serve us well. They give interactive high-level access to efficient low-level code. As datasets grow larger than memory this low-level code becomes obsolete but the high-level interface remains valuable. Blaze connects that high-level interface to a number of other computational systems like SQL, Mongo, or Spark, extending the scope of interactive analysis. In this talk we go over common use cases and Blaze as well as a bit of its internal design.

DataScience LA Meetup Summary: Data Science @ DataPop

Mon, 26 Jan 2015 10:41:08 -0800

Ben Zamanzadeh - Data Science @ Datapop - LA Data Science meetup - January 2015 · Speaker Deck

On January 13th, DataScience.LA held its first Data Science meetup of 2015, hosting a speaker from a local semantic advertising startup, DataPop. Their CTO, Dr. Ben Zamanzadeh, gave an in-depth presentation (linked above) of his perspective on e-commerce and advertising, which focused on extracting semantic meaning and DataPop’s marketing knowledge graph. He began his talk by discussing the evolution of e-commerce and moved quickly to semantics, making some very strong statements regarding DataPop’s architectural choices. For example, even though they provide a semantic graph, they are based on Redshift and do not use graph databases - which was quite the surprise to us here at DataScience.LA! At one point, Dr. Zamanzadeh even commented,

Data Science LA Meetup Summary: Data Science @ IRIS.TV

Thu, 08 Jan 2015 20:00:26 -0800

(Posting the slides and video recording from this event is long overdue - our apologies for the delay.)

At the September LA Data Science/Machine Learning meetup we had IRIS.TV’s Chief Data Scientist Tom Sullivan and VP of Engineering Joel Spitalnik presenting.

IRIS.TV is a video recommendation engine, and in their excellent talk Tom & Joel shared with us their approach to personalization and how they use machine learning to achieve their goals. They also shared the architecture of their systems, including how data is flowing between the various parts (i.e. the ETL pipeline). One thing that popped up as a question and I found interesting is that the usage of R and Python in their company is split 50-50. In fact, while Tom is using mainly R, Joel is using mainly Python. While this is perhaps unusual at a relatively small startup, our survey on software tools used for data science revealed that most data scientists in LA (at least those attending the meetups) are using R or Python, with a roughly equal split/small advantage for R. It just happens that for obvious reasons (such as network effects) that one tool dominates in most companies.

DataVis with Plot.ly (@plotlygraphs) - Meetup Summary

Tue, 30 Dec 2014 15:55:03 -0800

It pains me to admit it, but even though I had visited their site, created an account, and played around with their tools, I didn’t really get the value proposition behind Plot.ly. I already use ggplot, bokeh, and d3.js, I already use knitr and ipython notebooks, so why do I need a new way of posting my plots on a web page?

Meetup: DataVis with Plotly on December 16th

Fri, 12 Dec 2014 10:35:30 -0800

Plotly is a web-based platform for making graphs and analyzing data. Plotly’s APIs and web app let teams work together online to make 2D, 3D, and streaming graphs using R, Python, MATLAB, Julia, SAS, and and Excel, all together, all in one platform. The goal is to support technical and non-technical collaboration at all levels. Plotly translates ggplot2, matplotlib, and MATLAB plots into interactive, web-based, shareable plots.

Data Science Meetup - January 13: Data Science @ Datapop

Tue, 25 Nov 2014 09:45:53 -0800

Data Science @ Datapop: The Marketing Knowledge Graph

presented by Dr. Ben Zamanzadeh, CTO at DataPop

Today’s eCommerce has evolved into a complex multi-dimensional optimization problem. DataPop’s semantic technology and Marketing Knowledge Graph is used to generate Omni-Channel advertising campaigns. This presentation will review our technology stack, machine learning models, discuss what worked what did not work for us and do a live demo of Marketing Knowledge Graph.

LA R Meetup Summary: Highlights from useR! 2014 - Part 2

Tue, 18 Nov 2014 09:20:24 -0800

Last week the LA R meetup featured another round of 5 speakers each highlighting a few things they had found interesting at the useR! 2014 conference. This was the second such event after the first one in September - probably because useR! was awesome enough that it inspired 10 volunteers to stand up on stage and talk more about it.

Data Science Toolbox Survey Results... Surprise! R and Python win

Wed, 24 Sep 2014 10:25:13 -0700

This is a re-publication of a blog post from a blog I created not long before we got the idea to start DataScience.LA, and in many aspects it is the genesis of DSLA (the blog’s name, the people getting together - thanks Eduardo, Amelia and Leigh). It was also the spark that lead to the creation of the Python Data Science LA meetup.

The case for Apache Spark

Tue, 23 Sep 2014 10:00:05 -0700

I have been following Big Data, Hadoop in particular, for the past four years and a lot has changed since then. At the time I was looking for the next big wave of technologies, especially on the back end of development as that was my forte at the time. After our initial introduction, the more I learned the more I felt Hadoop was the right tool to get the job done. Focusing upon the development aspects of job vs actual maintenance of the servers/cluster has always been a no-brainer for me. Now that Hadoop has been adopted by a wide variety of industries and has grown quite popular, it has become much more apparent that there are indeed areas where Hadoop is lacking. Security and real-time analytics are two of these concerns which both affect real-time processing and reporting, but fortunately there is a lot of current work happening to address these limitations. Consequently, there is a group of big data vendors who are investing a large number of resources as a remedy, bringing us newer tools such as Yarn, Tez, Storm, etc. Also, acquisitions of XA Secure by Hortonworks and Gazzang by Cloudera are contributing to the solving these issues around security.

Announcing Partnership with LA Big Data Community

Wed, 03 Sep 2014 09:54:50 -0700

Today I am happy to announce that we are expanding our partnership on several fronts with my friend Subash D’Souza, a leader of the Big Data community in LA.

During the past few years I have been organizing several data science meetups in Los Angeles (LA R, DataVis LA, Data Science/Machine Learning) and Subash has provided the same kind of leadership on the big data front (LA Hadoop, HBase, LA Big Data). While I think of big data as primarily technology and of data science as a blend of statistics and technology (and not only for large data sets), there is clearly a significant overlap between these two fields. Considering this overlap, we have already been collaborating for some time regarding these various meetups, e.g. organizing joint events or speaking at one another’s meetups.

Win Books and T-shirts in Our DataScience.LA Meetup Raffles, Powered by R and dplyr!

Tue, 02 Sep 2014 09:41:54 -0700

We have a few pieces of swag that we are raffling off to the community at our upcoming meetup events. Our stash consists of 25 data-oriented books, primarily from O’Reilly plus 25 T-shirts from useR! 2014 conference and Revolution Analytics (see picture above). Did we get your attention?

R in Production - Panel Discussion - LA R meetup @ useR! 2014

Thu, 21 Aug 2014 14:27:50 -0700

(Please click here if the video above doesn’t load.)

The video above is from an event at useR! 2014 consisting of Yasmin Lucero’s presentation plus an incredible panel discussion, which is included here. The title of the panel was “R’s Place in the Production Environment”, and was moderated by Tareef Kawaf, President at RStudio. Five high-profile members of the R community were on this panel, spanning the gamut of the enterprise:

R in Production - Opening Talk by Yasmin Lucero - LA R meetup @ useR! 2014

Thu, 21 Aug 2014 13:54:56 -0700

(Please click here if the video above doesn’t load.)

During useR! 2014, the LA R Meetup (run by Szilard Pafka) organized an event focused on R’s status in industry. This event took the form of a presentation by Yasmin Lucero, Senior Statistician at AOL-Gravity, followed by a panel discussion. The video above captures the presentation, where Yasmin provides an excellent overview of the current status of R in the enterprise and breaks down the taxonomy of solutions for which R is commonly chosen as a development platform. From batch reporting and dashboards for internal deployment to full blown public facing analytics data products, R has certainly found a home in business. Yasmin’s talk concludes with specific, operational aspects of managing R in the enterprise, such as library and dependency management. Enjoy the video and don’t forget to tune in for Part 2 of this session where the panel discussed “R’s Place in the Production Environment.”

Meetups on DataScience.LA

CatBoost: Distributed Training, Uncertainty Estimation and Other News

Recent Developments in LightGBM

SatRday LA - R Conference Announcement

Meetup: Machine Learning Best Algorithms: Gradient Boosting Machines (GBM)

R Meetup with Hadley Wickham

Meetup: Machine Learning in Production with Szilard Pafka

Meetup: Stream processing with R in AWS

Meetup: No-Bullshit Data Science

PyDSLA: PyMC3 and jobs.py

Meetup: Machine Learning at Google

Machine Learning at Google #

How-to organize a satRday conference (v0.1)

PyDSLA: Talks from the LA Data Science Community

DSSTNE: A New Deep Learning Framework for Large Sparse Datasets

Update: This event has ended. Slides are available here. #

Update: Video recording by Carl Mullins: #

XGBoost: meetup announcement

PyDSLA: The Nitty Gritty of Advanced Analytics Using Apache Spark in Python

What has Kaggle learned from 2 million machine learning models?

PyDSLA: Erin LeDell, Presents Intro to Machine Learning with H2O and Python

LA Data Warehouse, Business Intelligence and Analytics - Jihoon Son

Meetup Summary - Winning Data Science Competitions

Announcing Meetup! Lior Abraham of Inter|Ana

PyDSLA: Dato CEO, Carlos Guestrin, Presents Dato

Data Science @ Whisper

Data Science/Statistics/R @Google

Yihui Xie presents HTML Widgets

Joe Cheng presents Shiny

PyDSLA - Blaze: Connecting analysts to big computation

DataScience LA Meetup Summary: Data Science @ DataPop

Data Science LA Meetup Summary: Data Science @ IRIS.TV

DataVis with Plot.ly (@plotlygraphs) - Meetup Summary

Meetup: DataVis with Plotly on December 16th

Data Science Meetup - January 13: Data Science @ Datapop

LA R Meetup Summary: Highlights from useR! 2014 - Part 2

Data Science Toolbox Survey Results... Surprise! R and Python win

The case for Apache Spark

Announcing Partnership with LA Big Data Community

Win Books and T-shirts in Our DataScience.LA Meetup Raffles, Powered by R and dplyr!

R in Production - Panel Discussion - LA R meetup @ useR! 2014

R in Production - Opening Talk by Yasmin Lucero - LA R meetup @ useR! 2014

Machine Learning at Google
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Update: This event has ended. Slides are available here.
#

Update: Video recording by Carl Mullins:
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