Канал: SF Big Analytics

GraphHouse and Training GNNs at Internet Scale

GraphHouse and Training GNNs at Internet Scale

SF Big Analytics 2024-06-27: Confidential Containers for GPU Compute: Lift-and-Shift Strategy for AI

SF Big Analytics 2024-06-27: Confidential Containers for GPU Compute: Lift-and-Shift Strategy for AI

Evaluation of LLMs and LLM Systems: Ensuring Relevance and Effectiveness in Real-World Applications

Evaluation of LLMs and LLM Systems: Ensuring Relevance and Effectiveness in Real-World Applications

Federated Learning: from simulation to production, cross-device and cross-silo

Federated Learning: from simulation to production, cross-device and cross-silo

Change Stream Processing with Debezium and Apache Flink

Change Stream Processing with Debezium and Apache Flink

Unlocking LLM Potential: From Federated Learning to Introspection

Unlocking LLM Potential: From Federated Learning to Introspection

Declarative Reasoning with Timelines: The Next Step in Event Processing

Declarative Reasoning with Timelines: The Next Step in Event Processing

NVIDIA: Accelerate Spark With RAPIDS For Cost Savings

NVIDIA: Accelerate Spark With RAPIDS For Cost Savings

NVIDIA RAPIDS Accelerator for Apache Spark ML

NVIDIA RAPIDS Accelerator for Apache Spark ML

NVIDIA: Federated XGBoost - Formulation to Implementation

NVIDIA: Federated XGBoost - Formulation to Implementation

Data Lake to Dashboard

Data Lake to Dashboard

Fraud Detection with Graph Features and Graph Neural Networks

Fraud Detection with Graph Features and Graph Neural Networks

Time Series Data and Stream Processing Performance Tuning

Time Series Data and Stream Processing Performance Tuning

Large-scale Data Process and ML Pipelines

Large-scale Data Process and ML Pipelines

SFBigAnalytics_20220920: DoorDash: Building Scalable Real Time Event Processing with Kafka and Flink

SFBigAnalytics_20220920: DoorDash: Building Scalable Real Time Event Processing with Kafka and Flink

Fast Analytics with Presto and Alluxio

Fast Analytics with Presto and Alluxio

SFBigAnalytics: A Data Engineer Odyssey - The Pains Leading to Data Observability Best Practices

SFBigAnalytics: A Data Engineer Odyssey - The Pains Leading to Data Observability Best Practices

Modern Data Processing Pipelines

Modern Data Processing Pipelines

SFBigAnalytics_20220707: Getting The Most From Your Data With Open Metadata

SFBigAnalytics_20220707: Getting The Most From Your Data With Open Metadata

Run Spark Applications As A Service In Large Scale On Kubernetes

Run Spark Applications As A Service In Large Scale On Kubernetes

SFBigAnalytics_20220607: Zookeeper vs Raft: Stateful Distributed Coordination with High Availability

SFBigAnalytics_20220607: Zookeeper vs Raft: Stateful Distributed Coordination with High Availability

SF Big Analytics_20220505: How can StarRocks outperform ClickHouse, Apache Druid and Trino

SF Big Analytics_20220505: How can StarRocks outperform ClickHouse, Apache Druid and Trino

The Modern Data Team

The Modern Data Team

SFBigAnalytics_20220315: Persia: Scaling DL Based Recommenders Up To 100 Trillion Parameters

SFBigAnalytics_20220315: Persia: Scaling DL Based Recommenders Up To 100 Trillion Parameters

SFBigAnalytics: Federated Learning Application Runtime Environment for Developing Robust AI Models

SFBigAnalytics: Federated Learning Application Runtime Environment for Developing Robust AI Models

New Trends of DataOps -- Perspectives from China

New Trends of DataOps -- Perspectives from China

SFBigAnalyttics_20211213: Optimizing Storage Efficiency for Meta Video Processing

SFBigAnalyttics_20211213: Optimizing Storage Efficiency for Meta Video Processing

Professional Career: Techniques to Practice Rigor and Avoid Ten Mistakes

Professional Career: Techniques to Practice Rigor and Avoid Ten Mistakes

SFBigAnalytics_20211027: Iceberg for Data Engineers

SFBigAnalytics_20211027: Iceberg for Data Engineers

SFBIgAnalytics_20211109: Semantic Search and Neural Information Retrieval

SFBIgAnalytics_20211109: Semantic Search and Neural Information Retrieval

SFBigAnalytics_20211018: Dagster: The orchestrator for the full data lifecycle

SFBigAnalytics_20211018: Dagster: The orchestrator for the full data lifecycle

SF BIg Analytics_202109_28: Beyond t-tests: Randomization, Traffic Allocation, & Multi-Armed Bandits

SF BIg Analytics_202109_28: Beyond t-tests: Randomization, Traffic Allocation, & Multi-Armed Bandits

SFBigAnalytics_2021071312 : System Design for Recommendations and Search

SFBigAnalytics_2021071312 : System Design for Recommendations and Search

SFBigAnalytics_2021_06_21: Delight: An Improved Apache Spark UI, Free and Cross-Platform

SFBigAnalytics_2021_06_21: Delight: An Improved Apache Spark UI, Free and Cross-Platform

SFBigAnalytics_20210601: Full Page Handwriting Recognition via Image to Sequence Extraction

SFBigAnalytics_20210601: Full Page Handwriting Recognition via Image to Sequence Extraction

SFBigAnalytics_20210512: Ballista- Distributed Compute with Apache Arrow and Rust

SFBigAnalytics_20210512: Ballista- Distributed Compute with Apache Arrow and Rust

SFBigAnalytics_20210414: Inside Apache Druid Storage and Query Engine

SFBigAnalytics_20210414: Inside Apache Druid Storage and Query Engine

SFBigAnaytics_20210414 Project Nessie: A git-like experience for Data Lakes

SFBigAnaytics_20210414 Project Nessie: A git-like experience for Data Lakes

SFBigAnalytics_20210311:A missing link in the ML infrastructure stack

SFBigAnalytics_20210311:A missing link in the ML infrastructure stack

SFBigAnalytics20210216:Production ML Monitoring: Outliers, Drift, Explainers & Stats Performance

SFBigAnalytics20210216:Production ML Monitoring: Outliers, Drift, Explainers & Stats Performance

SFBigAnalytics_20210212: Data Discovery - why, what & how: Talks from Lyft & Shopify

SFBigAnalytics_20210212: Data Discovery - why, what & how: Talks from Lyft & Shopify

SFBIgAnalytics_20201215: Being an engineer is not enough

SFBIgAnalytics_20201215: Being an engineer is not enough

SFBigAnalytics_20201110 Getting Started with Apache Spark on Kubernetes

SFBigAnalytics_20201110 Getting Started with Apache Spark on Kubernetes

SFBigAnalytics_20201029 : Mastering the Industrial IoT with Apache StreamPipes

SFBigAnalytics_20201029 : Mastering the Industrial IoT with Apache StreamPipes

SFBigAnalytics_20200908: Magnet Shuffle Service: Push-based Shuffle at LinkedIn

SFBigAnalytics_20200908: Magnet Shuffle Service: Push-based Shuffle at LinkedIn

SFBigAnalytics_20200116: Elastic Distributed DL Training at large scale on-prem & cloud productions

SFBigAnalytics_20200116: Elastic Distributed DL Training at large scale on-prem & cloud productions

SFBigAnalytics_20200825: Bootstrapping meaning with embodied language learning

SFBigAnalytics_20200825: Bootstrapping meaning with embodied language learning

SFBigAnalytics_20200825: Apache Submarine: State of the union

SFBigAnalytics_20200825: Apache Submarine: State of the union

SF Big Analytics_20200813: The missing story about the columnar format & Apache Kylin

SF Big Analytics_20200813: The missing story about the columnar format & Apache Kylin

SFBigAnalytics_20200804:Streamlit Components: Displaying complex JS and HTML components in Streamlit

SFBigAnalytics_20200804:Streamlit Components: Displaying complex JS and HTML components in Streamlit

Facets & the What-If Tool - ML model understanding with interactive visualizations.

Facets & the What-If Tool - ML model understanding with interactive visualizations.

SFBigAnalytics_20200728:Reshape Data Lake and Intro to HTAP

SFBigAnalytics_20200728:Reshape Data Lake and Intro to HTAP

SFBigAnalytics_20200714: Productionalizing Big Data (talks from Lyft and Workday)

SFBigAnalytics_20200714: Productionalizing Big Data (talks from Lyft and Workday)

SFBigAnalytics_20200702:Building A Scalable Experimentation Platform

SFBigAnalytics_20200702:Building A Scalable Experimentation Platform

SF Big Analytics_20200608: Migrating from Hive to Open Source Delta Lake+Hive

SF Big Analytics_20200608: Migrating from Hive to Open Source Delta Lake+Hive

SFBigAnalytics_20200608: Determined: open-source deep learning training platform

SFBigAnalytics_20200608: Determined: open-source deep learning training platform

SFBigAnalytics_20200116:Google:Improving Apache Spark Downscaling

SFBigAnalytics_20200116:Google:Improving Apache Spark Downscaling

SFBigAnalytics_20200116:Alibaba: Building an AI engine for time series data analytics

SFBigAnalytics_20200116:Alibaba: Building an AI engine for time series data analytics

SFBigAnalytics_20191112: Uncovering performance regressions in the TCP SACKs vulnerability fixes

SFBigAnalytics_20191112: Uncovering performance regressions in the TCP SACKs vulnerability fixes

SFBigAnalytics_20191112:Data driven development in autonomous-driving

SFBigAnalytics_20191112:Data driven development in autonomous-driving

SF Big Analytics 20190724: Monitoring Kafka like a Pro

SF Big Analytics 20190724: Monitoring Kafka like a Pro

SFBigAnalytics 20190724: Apache Pulsar

SFBigAnalytics 20190724: Apache Pulsar

Building highly efficient data lakes using Apache Hudi: SFBigAnalytics_20190612

Building highly efficient data lakes using Apache Hudi: SFBigAnalytics_20190612

SFBigAnalytics_20190612:Managing Uber’s Data workflow at Scale

SFBigAnalytics_20190612:Managing Uber’s Data workflow at Scale

SFBigAnalytics_20190612:Scaling Apache Spark on Kubernetes at Lyft

SFBigAnalytics_20190612:Scaling Apache Spark on Kubernetes at Lyft

SFBigAnalytics_20190410: Apache Airflow At Lyft

SFBigAnalytics_20190410: Apache Airflow At Lyft

SFBigAnalytics_20190410:Airbnb's end-to-end machine learning platform

SFBigAnalytics_20190410:Airbnb's end-to-end machine learning platform

SFBigAnalytics_20190412: Hybrid data management using CDAP

SFBigAnalytics_20190412: Hybrid data management using CDAP

SFBigAnalytics_20190313 (SlideOnly) Google/SalesForce/IBM AutoML +DL for Medical Diagnosis

SFBigAnalytics_20190313 (SlideOnly) Google/SalesForce/IBM AutoML +DL for Medical Diagnosis

ML For Mitosis Detection from Big Medical Images

ML For Mitosis Detection from Big Medical Images

SFBigAnalytics (slide-only): Workday:Document Understanding using Multi stage Machine Learning

SFBigAnalytics (slide-only): Workday:Document Understanding using Multi stage Machine Learning

SFBigAnalytics (slide Only):Facebook: Efficient Deep Learning for Computer Vision on Mobile Devices

SFBigAnalytics (slide Only):Facebook: Efficient Deep Learning for Computer Vision on Mobile Devices

SFBigAnalytics_2019_02_27: Document Understanding using Multi-stage Machine Learning

SFBigAnalytics_2019_02_27: Document Understanding using Multi-stage Machine Learning

SFBIgAnalytics_2019_02_27: Efficient Deep Learning for Computer Vision on Mobile Devices

SFBIgAnalytics_2019_02_27: Efficient Deep Learning for Computer Vision on Mobile Devices

Dynamic pricing of Lyft rides using streaming

Dynamic pricing of Lyft rides using streaming

Python Streaming Pipelines with Beam on Flink

Python Streaming Pipelines with Beam on Flink

Overview of Apache Beam

Overview of Apache Beam

TensorFlow Extended (TFX) with Apache Beam

TensorFlow Extended (TFX) with Apache Beam

SFBigAnalytics_20190116 (slide-only): Uber's Michelangelo PyML

SFBigAnalytics_20190116 (slide-only): Uber's Michelangelo PyML

SFBigAnalytics_20190116 (GoPro Version): Uber’s Michelangelo PyML

SFBigAnalytics_20190116 (GoPro Version): Uber’s Michelangelo PyML

SFBigAnalytics_20190116 (Slide Only): Uber’s Big Data Platform

SFBigAnalytics_20190116 (Slide Only): Uber’s Big Data Platform

SFBigAnalytics_20190116 (GoPro Version): Uber’s Big Data Platform

SFBigAnalytics_20190116 (GoPro Version): Uber’s Big Data Platform

Panel Discussion - Women in Data

Panel Discussion - Women in Data

Agile Data Science at Salesforce - Sarah Aerni

Agile Data Science at Salesforce - Sarah Aerni

Workflow orchestration system at Pinterest - Indy Prentice

Workflow orchestration system at Pinterest - Indy Prentice

reCAPTCHA: Easy for humans, hard for bots, good for humanity by Ying Liu

reCAPTCHA: Easy for humans, hard for bots, good for humanity by Ying Liu

SFBigAnalytics_2018_09_26: Vespa big data serving engine & Lambda Architecture in Practice

SFBigAnalytics_2018_09_26: Vespa big data serving engine & Lambda Architecture in Practice

SFBigAnalytics_2018-0912: Introduction to envoy

SFBigAnalytics_2018-0912: Introduction to envoy

SFBigAnalytics_20180912:Project Hydrogen: State-of-the-Art Deep Learning on Apache Spark

SFBigAnalytics_20180912:Project Hydrogen: State-of-the-Art Deep Learning on Apache Spark

SFBA_20180823:TensorFlow Probability and how Yelp use ML to identify popular dishes

SFBA_20180823:TensorFlow Probability and how Yelp use ML to identify popular dishes

Foundations of streaming SQL by Tyler Akidau

Foundations of streaming SQL by Tyler Akidau

The rise of operational analytic data stores by Gian Merlino

The rise of operational analytic data stores by Gian Merlino

Data modeling tradeoffs with Druid by Maxime Beauchemin

Data modeling tradeoffs with Druid by Maxime Beauchemin

Streaming SQL and Druid by Arup Malakar

Streaming SQL and Druid by Arup Malakar

How Apache Calcite brings SQL and sanity to streaming and spatial data - Julian Hyde

How Apache Calcite brings SQL and sanity to streaming and spatial data - Julian Hyde

Kinesis at Lyft - by Hafiz Hamid

Kinesis at Lyft - by Hafiz Hamid

SFBigAnalytics_20180613: ML with Kubeflow, Genomics on Deepsea, Random Walk with Spark

SFBigAnalytics_20180613: ML with Kubeflow, Genomics on Deepsea, Random Walk with Spark

SFBigAnalytics_20180418: Evolution of GoPro Data Platform & Detect Cancer with Deep Learning

SFBigAnalytics_20180418: Evolution of GoPro Data Platform & Detect Cancer with Deep Learning

SFBigAnalytics 20180405: Deep Learning in Biomedicine and Genomics

SFBigAnalytics 20180405: Deep Learning in Biomedicine and Genomics

SFBigAnalytics_20180329: Online Experimentation at Scale

SFBigAnalytics_20180329: Online Experimentation at Scale

Lighting Talk: Visualize Food insecurity

Lighting Talk: Visualize Food insecurity

SFBigAnalytics_20180329: A Philosophy for Product Experimentation, Airbnb

SFBigAnalytics_20180329: A Philosophy for Product Experimentation, Airbnb

SFBigAnalytics20180215: Learning with limited supervision

SFBigAnalytics20180215: Learning with limited supervision

SFBigAnalytics_20180117: Advanced Data Engineering Patterns with Apache Airflow

SFBigAnalytics_20180117: Advanced Data Engineering Patterns with Apache Airflow

SF Big Analytics_20180117:Stream All Things - Patterns of Modern Data Integration

SF Big Analytics_20180117:Stream All Things - Patterns of Modern Data Integration

SF Big Analytics20171128: Google's Neural Machine Translation System and Research progress

SF Big Analytics20171128: Google's Neural Machine Translation System and Research progress

SFBigAnalytics 20171025 : Streaming, HBase and Data at Lyft

SFBigAnalytics 20171025 : Streaming, HBase and Data at Lyft

Tensorflow on Apache Hadoop YARN (Low res, but with full picture)

Tensorflow on Apache Hadoop YARN (Low res, but with full picture)

Tensorflow on Apache Hadoop YARN

Tensorflow on Apache Hadoop YARN

SFBigAnalytics_20170822 : Airbnb Data Science & Democratizing Data

SFBigAnalytics_20170822 : Airbnb Data Science & Democratizing Data

sfbiganalytics20170726 Hoodie

sfbiganalytics20170726 Hoodie

SFBigAnalytics 20170706: Push the Limits of Kafka & Streaming Analytics with HTM

SFBigAnalytics 20170706: Push the Limits of Kafka & Streaming Analytics with HTM

SFBigAnalytics 2017-05-10 GoPro data pipeline & Analytics

SFBigAnalytics 2017-05-10 GoPro data pipeline & Analytics

SFBigAnalytics 20170417 RNN real time Anomaly detection

SFBigAnalytics 20170417 RNN real time Anomaly detection

SFBigAnalytics 20170405: TensorFlowOnSpark for Scalable Deep Learning

SFBigAnalytics 20170405: TensorFlowOnSpark for Scalable Deep Learning

SFBigAnalytics 20170328: Vicarious AI's Generative Models for Training with Very Little Data

SFBigAnalytics 20170328: Vicarious AI's Generative Models for Training with Very Little Data

SFBigAnalytics 03 21 2017 Adam

SFBigAnalytics 03 21 2017 Adam

SFBigAnalytics 03 21 2017: Deep Learning in Production with GPUs

SFBigAnalytics 03 21 2017: Deep Learning in Production with GPUs

SFBigAnalytics 20160221 : Improving Hardware Efficiency for DNN Applications

SFBigAnalytics 20160221 : Improving Hardware Efficiency for DNN Applications

SFBA 20170111-- DevOps for Data Science

SFBA 20170111-- DevOps for Data Science

2017-01-26 VEGAS: The missing Matplotlib for Spark, presented by Netflix

2017-01-26 VEGAS: The missing Matplotlib for Spark, presented by Netflix

SFbigAnalytics 2016 12 05

SFbigAnalytics 2016 12 05

SF Big Analytics: Introduction to Succinct by UC Berkeley AmpLab

SF Big Analytics: Introduction to Succinct by UC Berkeley AmpLab

SF Big Analytics 20161005: Robust Stream Processing with Apache Flink

SF Big Analytics 20161005: Robust Stream Processing with Apache Flink

Introduction to Apache SparkR

Introduction to Apache SparkR

SF Big Analytics: Building/Running Netflix's Data Pipeline using Apache Kafka

SF Big Analytics: Building/Running Netflix's Data Pipeline using Apache Kafka

Streaming Data Pipelines With Container

Streaming Data Pipelines With Container

Real-Time Machine Learning Visualization with Spark

Real-Time Machine Learning Visualization with Spark

SF Big Analytics: Next-generation Python Big Data Tooling, powered by Apache Arrow

SF Big Analytics: Next-generation Python Big Data Tooling, powered by Apache Arrow

SF Big Analytics: Distributed Time Travel for Feature Generation at Netflix

SF Big Analytics: Distributed Time Travel for Feature Generation at Netflix

The Big Data Mechanic Workshop 1

The Big Data Mechanic Workshop 1

Introduction to Apache Tajo

Introduction to Apache Tajo

SF Big Analytics: Knowledge graph and inference -- 02-01-2015

SF Big Analytics: Knowledge graph and inference -- 02-01-2015

Alpine Academy Series : Spark Workshop Part 2 -- Introduction to Spark ML

Alpine Academy Series : Spark Workshop Part 2 -- Introduction to Spark ML

SF Big Analytics : Analyzing and Visualizing Neuroscience data by Jeremy Freeman 032615

SF Big Analytics : Analyzing and Visualizing Neuroscience data by Jeremy Freeman 032615

SF Big Analytics Running Production Hadoop Clusters in Docker Containers Nasser Manesh 04 15 2015

SF Big Analytics Running Production Hadoop Clusters in Docker Containers Nasser Manesh 04 15 2015

SF Big Analytics: Interactive Data Science and Sharing with Jupyter and IPython by Min RK

SF Big Analytics: Interactive Data Science and Sharing with Jupyter and IPython by Min RK

SF Big Analytics : "Machine Learning in Presto" And "Non-Parametric Bayesian"

SF Big Analytics : "Machine Learning in Presto" And "Non-Parametric Bayesian"

SF Big Analytics event at Baidu: Part 3 Deep Speech Awni Hannun

SF Big Analytics event at Baidu: Part 3 Deep Speech Awni Hannun

SF Big Analytics Event At Baidu: Part 2 Why HPC is important to AI Bryan Catanzaro

SF Big Analytics Event At Baidu: Part 2 Why HPC is important to AI Bryan Catanzaro

SF Big Analytics event at Baidu : Part 1 Deep Learning by Prof Andrew Ng

SF Big Analytics event at Baidu : Part 1 Deep Learning by Prof Andrew Ng

SF Big Analytics Chisam Data Visualization Platform By Curran Kelleher

SF Big Analytics Chisam Data Visualization Platform By Curran Kelleher

SF Big Analytics IBM SystemML

SF Big Analytics IBM SystemML

SF BIG ANALYTICS 10 15 2015 GPU enabled data processing%2C machine learning%2C and visualization

SF BIG ANALYTICS 10 15 2015 GPU enabled data processing%2C machine learning%2C and visualization

SF BIG ANALYTICS 10 15 2015 Anomaly Detection and Root Cause Analysis

SF BIG ANALYTICS 10 15 2015 Anomaly Detection and Root Cause Analysis

SF Big Analytics: Machine Learning at the Limit by Prof John Canny

SF Big Analytics: Machine Learning at the Limit by Prof John Canny

SF Big Analytics 12-01-2015 : Druid: Interactive Exploratory Analytics at Scale

SF Big Analytics 12-01-2015 : Druid: Interactive Exploratory Analytics at Scale

SF Big Analytics: Apache Kafka and the Rise of The Stream Data Platform

SF Big Analytics: Apache Kafka and the Rise of The Stream Data Platform

2015-10-20 Pinterest Chief Scientist Prof. Jure Leskovec: Discovering Networks of Products

2015-10-20 Pinterest Chief Scientist Prof. Jure Leskovec: Discovering Networks of Products