datapine

MAY 14, 2019

2) “Deep Learning” by Ian Goodfellow, Yoshua Bengio and Aaron Courville. Best for: This best data science book is especially effective for those looking to enter the data-driven machine learning and deep learning avenues of the field. “Machine Learning Yearning” by Andrew Ng.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

Insight

JANUARY 14, 2020

CNNs have been widely considered state-of-the-art tools for computer vision since 2012, when AlexNet won the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Keras is an open source deep learning API that was written in Python and runs on top of Tensorflow, so it’s a little more user-friendly and high-level than Tensorflow.

Metrics 58

Metrics Optimization Modeling Testing 58

Sisense

MAY 26, 2020

Amit Bendov was appointed CEO in July 2012. Also deep learning models like recurrent neural networks help machines to understand the context of the words used. Scott enables our data-driven culture by using insights to make actionable decisions by ongoing review of Marketing, Sales, and Customer Success performance metrics.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

Domino Data Lab

APRIL 21, 2021

deep learning) there is no guaranteed explainability. from sklearn import metrics. With this criterion in mind, we can define a distance metric to the top left corner of the curve and find a threshold that minimises it. It is also suitable for online applications, as the scoring function is usually very lightweight.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Domino Data Lab

JULY 22, 2019

I went to a meeting at Starbucks with the founder of Alation right before they launched in 2012, drawing on the proverbial back-of-the-napkin. and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries. You started to see point solutions.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

MARCH 3, 2019

What metrics are used to evaluate success? O’Reilly Media had an earlier survey about deep learning tools which showed the top three frameworks to be TensorFlow (61% of all respondents), Keras (25%), and PyTorch (20%)—and note that Keras in this case is likely used as an abstraction layer atop TensorFlow.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

SEPTEMBER 9, 2019

For example, with those open source licenses we can download their text, parse, then compare similarity metrics among them: In [12]: pairs = [?. ["mit", "asl"],?. ["asl", "bsd"],?. ["bsd", "mit"] ?]? ?for deep learning on edge devices. for a, b in pairs:?. print(a, b, lic[a].similarity(lic[b])).

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110