Databricks

apache spark sparkaisummit spark + ai summit

 * spark summit ai

 * big data

 * machine learning

 * databricks databricks * 2019 * 
apache spark

 * spark + ai summit * apache spark

 * machine learning big data spark data science mlflow apache spark 2.0 spark sql dataframes structured streaming spark streaming tensorflow model management hadoop deep learning pipelines python ai deep learning spark summit east 2017 delta lake pyspark databricks cloud sparkr strata san jose apache spark

 * bay area apache spark meetup keras unified analytics platform apache spark 2.3 machine learning pipelines cloud graphframes mllib tungsten spark performance tuning data pipeline etl spark summit east 2016 datasets r pandas lakehouse * artificial neural networks neural networks ml model tracking machine learning model management databricks delta kubernetes and spark distributed data advanced analytics scale catalyst streaming performance jit-dw r on spark data warehousing scala data mlflow model serving spark + ai summit 2020 mlops automate koalas linkedin sparkasisummit ml model management ml model experimentaiton pytorch open source apachespark continuous applications devops apache spark 2.2 ml pipelines hdfs azure sql spark clusters gpu acceleration tensorframes database spark ml mllib spark 2.0 rdds aws spark meetup graph algorithms vida ha dataframe free training torchscript torchserv automl pycaret sql analytics nvidia rapids mlflow deployment rapids nvidia model serving model deployment mlflow integration redisai schema management autologging project zen pandas udf sql join hints dynamic partition prunning adaptive query execution data lake bogota spark meetup apache spark 3.0 2020 model registry databricks unified analytics platform microsoft azure structures nubank democratization customer experience real time meaning maps facebook apps acid orc spark core loss prevention fastai knowledge graph cosmos db workshop ml stack factory building scalable forecast dynamic partition pruning deep anomaly detection streaming analytics model reasoning kubeflow rest backend data quality astronomical data processing lsst scale spark operator vectorized hyperparameter data agility data abstraction dalispark views apache hive presto data access dalispark cost based optimizer microsoft onnx pydatamiami datat science ml end-to-end lifecycle ml model experimentation model tracking rstudio sparksaturday distributed training horovod mpi spark mllib uber distributed deep learning databricks unified platform spark+aisummit security salesforce wibd real-time model scoring threat detection cybersecurity continuous streaming databricks runtime 4.0 ci/cd women in big data women in apache spark graph analytics apach spark jsonnet basel kubernetes deployment models spark summit 2017 kinesis firehose data analytics odsc dapply spark-sklearn distributed computing gpu stanford multicore parallelization weld r packages rlang distributed sparksql etl pipeline cloud data womenintech executive leadership development equality women spark production production streaming applications advanced streaming analytics cloud storage storage best practices use case model training amplab apache spark 2.0 structured streaming databricks advanced analytics online analytics predictionio tensorframes tensorflow sparkr r r statistics webinar motif finding graph queries motif cdc schema on read change data capture quick start scikit-learn deploying spark spark summit 2016 real-time generalized linear model matei zaharia community edition just-in-time data warehousing apache spark 1.6 dataset spark use cases healthcare data mining sketch sampling strata new york stratified sampling count-min sketch frequent items bloom filter hyperloglog parviz deyhim apache spark 1.5 patrick wendell mlconf seattle strata london datab data source api data visualization ml jvm debugging testing groupbykey errors holden karau reducebykey serialization shuffling sparkcamp