Remove data-science-dictionary hyperparameter-tuning
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Open Data Science and Machine Learning for Business with Cloudera Data Science Workbench on HDP

Cloudera

It’s official – Cloudera and Hortonworks have merged , and today I’m excited to announce the availability of Cloudera Data Science Workbench (CDSW) for Hortonworks Data Platform (HDP). Trusted by large data science teams across hundreds of enterprises —. Sound familiar? What is CDSW?

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Ray for Data Science: Distributed Python tasks at scale

Domino Data Lab

Let’s use an actor to hold the DNS data. Until now, we’ve had a bottleneck trying to access the single dictionary and it was “stuck” in our driver ipython process. First, here’s the DNSServer Ray actor: import ray @ray.remote class DNSServer(object): def __init__(self, initial_addresses): # A dictionary of names to IP addresses.

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Towards Predictive Accuracy: Tuning Hyperparameters and Pipelines

Domino Data Lab

This article provides an excerpt of “Tuning Hyperparameters and Pipelines” from the book, Machine Learning with Python for Everyone by Mark E. The excerpt and complementary Domino project evaluates hyperparameters including GridSearch and RandomizedSearch as well as building an automated ML workflow. Introduction.

Testing 79
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Building a Named Entity Recognition model using a BiLSTM-CRF network

Domino Data Lab

The model achieves relatively high accuracy and all data and code is freely available in the article. The drawback with statistical model-based techniques is that the automated extraction of a comprehensive set of rules requires a large amount of labeled training data. Data exploration and preparation.

Modeling 111
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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Data scientists and researchers require an extensive array of techniques, packages, and tools to accelerate core work flow tasks including prepping, processing, and analyzing data. Utilizing NLP helps researchers and data scientists complete core tasks faster. Preprocessing Natural Language Data. Example 11.4