AWS Big Data

MAY 4, 2023

Welcome to the era of data. The sheer volume of data captured daily continues to grow, calling for platforms and solutions to evolve. The Amazon Sustainability Data Initiative (ASDI) uses the capabilities of Amazon S3 to provide a no-cost solution for you to store and share climate science workloads across the globe.

Data Processing 94

Data Processing Metadata Informatics Interactive 94

O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

Insight

JULY 23, 2019

I frequently run into this issue in my data science workflow with complex objects in libraries, like TensorFlow. kwonlydefaults is a dictionary with keyword-only arg default values. annotations is a dictionary specifying any type annotations. args contains the argument names. kwonlyargs lists names of keyword-only args.

Testing 55

Testing Data Science IT Interactive 55

Domino Data Lab

JANUARY 21, 2021

Producing insights from raw data is a time-consuming process. The Importance of Exploratory Analytics in the Data Science Lifecycle. Exploratory analysis is a critical component of the data science lifecycle. For one, Python remains the leading language for data science research. ref: [link].

Statistics 106

Statistics Unstructured Data Data Science Predictive Modeling 106

Cloudera

NOVEMBER 3, 2021

Have you ever asked a data scientist if they wanted their code to run faster? According to a poll in Kaggle’s State of Machine Learning and Data Science 2020 , A Convolutional Neural Network was the most popular deep learning algorithm used amongst polled individuals, but it was not even in the top 3. In fact only 43.2%

Deep Learning 116

Deep Learning Machine Learning Data Science Cost-Benefit 116

Domino Data Lab

JULY 1, 2021

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

Modeling Statistics Testing Metrics 111

Domino Data Lab

AUGUST 20, 2019

Many thanks to AWP Pearson for the permission to excerpt “Manual Feature Engineering: Manipulating Data for Fun and Profit” from the book, Machine Learning with Python for Everyone by Mark E. Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models.

Testing 68

Testing Modeling Interactive Measurement 68