KERAS in golang Keras Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
Why use Keras? Keras offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear and actionable feedback upon user error.
KERAS in golang Keras Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
Why use Keras? Keras offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear and actionable feedback upon user error.
Hi there!
Apache Spark has been written in Scala originally, although Python developers are loving it’s wrapper-known as PySpark. One can work with RDD’s and dataframes in Python too.
We,data science team @Talentica, love PySpark and mostly rely on Spark Clusters for data processing and other relevant stuffs. Recently, we faced one challange which is very important to be addressed.
Spark Context Whenever in need, one can initialize the Spark Context in their py file and reuse it.
Hi there!
Apache Spark has been written in Scala originally, although Python developers are loving it’s wrapper-known as PySpark. One can work with RDD’s and dataframes in Python too.
We, the data science team @Talentica love PySpark and always rely on Spark Clusters for data processing and other relevant stuffs. Recently, we faced one challange which is very important to be addressed.
Spark Context def get_spark_context(): conf = SparkConf().setAppName('app-name').set('spark.executor.memory', '8g').