data science on DataScience.LA

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.

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
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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.
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Update: Video recording by Carl Mullins:
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This video is no longer available on YouTube (original link).

XGBoost workshop and meetup talk with Tianqi Chen

Mon, 06 Jun 2016 09:00:50 -0700

XGBoost is a fantastic open source implementation of Gradient Boosting Machines, a general purpose supervised learning method that achieves the highest accuracy on a wide range of datasets in practical applications. Deep learning is all the hype now, but apart from specific domains such as images, speech or text (i.e. problems with higher-level abstractions to be learnt and/or perception problems, where deep learning achieved some remarkable results indeed), it is usually outperformed by Gradient Boosting in a majority of general business domains and supervised learning applications. Proof of this and also because XGBoost has an easy-to-use interface from both R and Python, XGBoost has become a favorite tool in Kaggle competitions. Besides feature engineering, cross-validation and ensembling, XGBoost is a key ingredient for achieving the highest accuracy in many data science competitions and more importantly in practical applications.

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.

Deep Learning @Whisper

Tue, 03 May 2016 11:37:29 -0700

Deep Learning @Whisper
talk by Nick Stucky-Mack

Video now available, thank you to community member Carl Mullins for providing video services:

▶ Deep Learning @Whisper THU, MAY 12 AT 6 00 PM, VENICE, CA

In this talk we will discuss how Whisper uses machine learning for natural language processing tasks. We will focus on how Whisper applies deep learning to moderate content created by its more than 20 million monthly active users. The talk will explore the problem of short text classification, and will cover Whisper’s choices in machine learning models, software development, and hardware.

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.

Big RAM is eating big data - Size of datasets used for analytics

Wed, 18 Nov 2015 09:41:22 -0800

With so much hype about “big data” and the industry pushing for “big data” analytical tools for everyone, the question arises how many people have big data (for analytics) and how many of them really need these tools (which are more complex and often more immature compared to the traditional tools for analytics).

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!

R and Impala: it's better to KISS than using Java

Thu, 29 Oct 2015 15:10:25 -0700

One of the best things I like in working at CARD.com is that I am not only crunching R code in 24/7, but I also have the chance to interact with and improve the related data infrastructure with some interesting technologies.

After joining the company in January, I soon realized that while Impala is a very powerful database for handling data that do not comfortably fit in MySQL, it’s still not as fast as one might expect when querying large amount of data from R. Sometimes I had to wait several minutes for a query to run! So I used this spare time to think about how to improve the workflow.

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 Video: Carlos Guestrin, CEO of DATO

Thu, 18 Jun 2015 15:53:26 -0700

On May 14th at the Venice Arts Center, the Los Angeles Python and Data Science communities were fortunate to hear a talk from world-renowned expert and CEO of Dato, Carlos Guestrin. Often times when you have a meetup where a presenter is tightly identified with a company, the concern is that the presentation will fundamentally become a product pitch. We had nothing to be worried about in this case - Carlos presented for nearly an hour on a wide range of subjects from how the Machine Learning pipeline has changed over time to Deep Learning!

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.

DW/BI/Analytics Meetup Summary: Inaugural Event

Sun, 15 Feb 2015 13:45:12 -0800

The LA Data Warehouse, Business Analytics and Analytics meetup had a fantastic first event with a great audience (full house), an awesome host (thanks Edmunds: Punnoose for taking the lead and the Team onsite and helping) and a great mix of 3 talks overviewing the field.

Re: Sorry for the mix up regarding Data Science candidates

Fri, 06 Feb 2015 11:25:56 -0800

This was originally posted on the author’s LinkedIn

You will find lots of advice on how to get a job as a data scientist. I want to add some signal to the noise.

I happen to be hiring for a Data Scientist or two as of this writing, and was thinking of doing a blog post on offering advice for those looking. But then I thought of something better and more insightful: It is a cut-and-paste of an email that I sent to our Director of Talent Acquisition last week when he asked me, “Can you share with me what you’re looking for in regards to your Data Scientist candidates?”

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,

Secure your Shiny apps (against SQL injection)

Mon, 12 Jan 2015 09:25:12 -0800

Shiny takes inputs from UI elements and sends them to the server, where the application can access them as R variables. While Shiny has security measures in place, as in any typical web application, it remains the developer’s responsibility to sanitize the inputs before using them. For example, Shiny has no way to protect you if you are using an input in a SQL query such as select ... from ... where field = 'input'. Someone manipulating the websocket communication can craft a specially-formatted input that can force the database to execute a query that it is not supposed to do, termed an SQL injection. This might give an attacker access to private data or the ability to do other nefarious things, and it is a common security issue.

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.

dplyr - some more reflections

Thu, 04 Dec 2014 09:30:00 -0800

Yesterday, I published a post here on DataScience.LA with a simple/basic benchmark for dplyr. It was the main part of a short talk at our last Los Angeles R meetup. Below, I continue my thoughts with some reflections on dplyr’s API and philosophy, AKA the other part of my talk.

dplyr and a very basic benchmark

Wed, 03 Dec 2014 09:35:05 -0800

Earlier this month I gave a short talk about dplyr at the Los Angeles R meetup. It was one of the 5 talks about the useR! 2014 conference, and you can see the summaries and slides from the other 4 talks here.

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 - January 21: RStudio's Shiny with Joe Cheng

Thu, 20 Nov 2014 10:04:38 -0800

At this meetup we’re fortunate to have RStudio’s lead developer Joe Cheng flying in from Seattle to talk about Shiny. Shiny makes it possible to develop interactive web applications by writing only a handful of R code. It lowers the barriers to constructing interactive dashboards that you can use to better explain your results to your boss and/or co-workers, or it can help you productionalize your analysis so that others in your company can make use of it regularly without the need to continually bother you.

LA R Meetup - November 11: Highlights from the useR! 2014 conference - Part 2

Wed, 29 Oct 2014 09:16:21 -0700

At this meetup, five more LA R meetup members will present short talks of what they have learned at useR! 2014. This is the 2nd round of talks about useR! since we had twice as many volunteers to speak as we could accommodate in one meetup (indeed, useR! was that awesome). The first round of talks at our September meetup is summarized here (with slides).

Going (a bit more) public

Mon, 27 Oct 2014 09:48:53 -0700

I ♥ data. But I also ♥ privacy. Even though I have been running a few data meetups for the past few years, I have managed to keep myself out of public eye - even in my professional life. I must admit, I’m giving a bit away in an recent interview with Data Science Weekly. They had excellent questions to pose, and I’d like to take a moment here to summarize two main points from the interview: my thoughts on when and how much time it took me to became a data scientist and how I feel about the hype in the field today. If you’d like, you can read the full interview here.

Python Data Science Meetup: Data Science with Python

Wed, 08 Oct 2014 09:37:41 -0700

I’m pleased to announce the first event of our new Python Data Science LA meetup, started by two of us here at DataScience.LA (our very own Szilard and Eduardo).

We’ll have 5 speakers at this event, covering various aspects of the Python Data Science ecosystem (NumPy, SciPy, pandas, matplotlib, scikit-learn, NetworkX, NLTK, IPython notebook, etc.)

A Conversation with Joe Cheng at useR! 2014

Mon, 06 Oct 2014 10:18:56 -0700

Joe Cheng is a software engineer. Unfortunately the term gets thrown around pretty lightly, so I’d like to make sure that I convey the appropriate amount of gravitas when I refer to him as such. Joe Cheng is a *great* Software Engineer. He has worked for some of the largest technology companies on the planet, building cutting edge tools which empowered the web browser as a full blown platform instead of a historical curiosity. Joe is one of those software engineers who saw a future with the web as a platform for modern software, then worked hard to make it a reality. When the time came to build the next generation of data science IDEs, an IDE targeting the web as a platform, RStudio called Joe.

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.

LA R Meetup Summary: Highlights from the useR! 2014 Conference

Wed, 10 Sep 2014 09:45:20 -0700

Last week the LA R meetup featured 5 speakers each highlighting a few things they had found interesting at the useR! 2014 conference (which I had the pleasure of helping to organize this year in Los Angeles). This meetup proved to be interesting even to those of us who attended the conference (which was about half of our audience), simply because there were so many cool things to hear and enough parallel sessions at the conference that no one could possibly capture all of the action.

The Importance of 'Janitorial Work' in Research

Tue, 02 Sep 2014 11:47:29 -0700

As someone who has spent a significant amount of time ‘data wrangling’ outside the field of data science, I found this recent New York Times article both highly interesting and nothing new - I’ve seen the same issue discussed in a variety of fields with similar automation solutions presented each time. Granted, there are fields where this janitorial drudgery is absolutely necessary, such as molecular biology. As a scientist working on researching mRNA expression you certainly have to keep RNase-free conditions, meaning you have to ‘clean up’ your bench in a more detailed way than you’d ever imagine before you can run your first PCR cycle. This includes specific protocols for washing your dishes several times with special water before you even start because if you don’t, you’re not likely to get any bands in your electrophoresis gel and you’ll lose several days (or weeks!) of work.

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?

Announcing the New Python Data Science LA Meetup Group

Fri, 29 Aug 2014 09:01:19 -0700

I am excited to announce that we are starting a new meetup group - Python Data Science LA - to serve the needs of the LA data science community using Python!

At an earlier Data Science/Machine Learning meetup we conducted an informal survey on tools for Data Science which showed that a large majority of data scientists use R or Python, with R taking a slight lead. (I know, those attending the meetups bias the results towards open source tools.)

David Smith, the useR! 2014 Interview

Mon, 25 Aug 2014 10:00:32 -0700

“At one point, the only source for daily R news was David Smith’s blog.” – Szilard Pafka

David Smith is an integral part of the R community. His background in computational statistics goes back to the early 90s . David has worked at Revolution R, one of the leading R companies, for nearly a decade. His name has been included in lists such as:

Introduction to Data Science for High School Students

Wed, 20 Aug 2014 10:02:52 -0700

Another exciting development in data science coming from our department at UCLA is a high school class called Introduction to Data Science (IDS). This project has been made possible by a National Science Foundation grant to support Mobilize, for which Rob Gould (mentioned in my previous post on DataFest) is the Principal Investigator.

Data Science meetup - September 15: Data Science @ IRIS.TV

Tue, 19 Aug 2014 10:00:44 -0700

Data Science @ IRIS.TV

by Dr. Thomas Sullivan, Chief Data Scientist and Joel Spitalnik, VP Engineering

While video recommendations best serve the viewer experience when presented in real time, machine learning is a computationally intensive process that is often done on the back end. IRIS.TV’s utilizes a hybrid process to synchronize computational tasks for learning so that engineering and data science teams can shrink the latency between analyzing history and presentation of recommended videos to improve the experience.

Making Maps with a Punchline

Wed, 06 Aug 2014 18:09:43 -0700

I’ve had a lifelong fascination with maps, and working with R definitely enables my map habit. Perhaps there’s something about being an immigrant that made me particularly introspective, since from a very early age I was aware that I was “from” one place on the map and now lived at this “other place.”

Blogging Accelerator for DataScience.LA

Wed, 06 Aug 2014 18:08:58 -0700

By now I’m sure you’ve checked out our blog and have wondered, ‘How can I contribute my ideas and share my projects with the community?’ There are two ways to contribute content to DataScience.LA, either as a regular contributor or through our Blogging Accelerator. Our vision is to help unleash you, members of the community, as effective data science communicators while establishing Los Angeles as one of the leading places for data thinking, data journalism, and data science. (Ready to write a blog post right now? Send us an email at info@datascience.la to get started as a contributor.)

Welcome to Data Science LA!

Sat, 02 Aug 2014 21:12:52 -0700

Welcome! We are launching DataScience.LA to provide a home for all the content (slides, code, videos etc.) for several meetups in LA (Data Science/Machine Learning, R, DataVis etc.) and to engage the Los Angeles data science community in an open, active discussion about best practices and new developments in the field.

data science on DataScience.LA

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

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 workshop and meetup talk with Tianqi Chen

XGBoost: meetup announcement

Deep Learning @Whisper

What has Kaggle learned from 2 million machine learning models?

Big RAM is eating big data - Size of datasets used for analytics

Meetup Summary - Winning Data Science Competitions

R and Impala: it's better to KISS than using Java

Announcing Meetup! Lior Abraham of Inter|Ana

PyDSLA Video: Carlos Guestrin, CEO of DATO

Data Science @ Whisper

Data Science/Statistics/R @Google

DW/BI/Analytics Meetup Summary: Inaugural Event

Re: Sorry for the mix up regarding Data Science candidates

DataScience LA Meetup Summary: Data Science @ DataPop

Secure your Shiny apps (against SQL injection)

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

dplyr - some more reflections

dplyr and a very basic benchmark

Data Science Meetup - January 13: Data Science @ Datapop

LA R meetup - January 21: RStudio's Shiny with Joe Cheng

LA R Meetup - November 11: Highlights from the useR! 2014 conference - Part 2

Going (a bit more) public

Python Data Science Meetup: Data Science with Python

A Conversation with Joe Cheng at useR! 2014

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

LA R Meetup Summary: Highlights from the useR! 2014 Conference

The Importance of 'Janitorial Work' in Research

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

Announcing the New Python Data Science LA Meetup Group

David Smith, the useR! 2014 Interview

Introduction to Data Science for High School Students

Data Science meetup - September 15: Data Science @ IRIS.TV

Making Maps with a Punchline

Blogging Accelerator for DataScience.LA

Welcome to Data Science LA!

Machine Learning at Google
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Update: This event has ended. Slides are available here.
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Update: Video recording by Carl Mullins:
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