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The history of ESG: A journey towards sustainable investing

IBM Big Data Hub

It refers to a set of metrics used to measure an organization’s environmental and social impact and has become increasingly important in investment decision-making over the years. In response, asset managers began to develop ESG strategies and metrics to measure the environmental and social impact of their investments.

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The change management Informatica needed to overhaul its business model

CIO Business Intelligence

When we were taken private in 2015, we were a traditional software vendor, but the market was starting to embrace the cloud. Then at the other end, we did a fantastic job involving the sales operations, finance, and marketing teams in the testing and design, and we did a great job training people. Take sales territories for example.

Modeling 114
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Top 10 Management Reporting Best Practices To Create Effective Reports

datapine

As Tyrone Cotie, treasurer of Clearwater Seafoods says in 2015 Benchmarking the Accounting & Finance Function report , “…no matter how quickly you compile and release historical financial statements, you never make a decision from them. Contrasting different KPIs and metrics against each other. They’re also slow.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. After forming the X and y variables, we split the data into training and test sets. 2015) for additional details. random_state=seed) y_train.value_counts(). See Wei et al.

Modeling 139
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Introducing the vector engine for Amazon OpenSearch Serverless, now in preview

AWS Big Data

The vector engine supports the popular distance metrics such as Euclidean, cosine similarity, and dot product, and can accommodate 16,000 dimensions, making it well-suited to support a wide range of foundational and other AI/ML models. To create the vector index, you must define the vector field name, dimensions, and the distance metric.

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

Domino Data Lab

from keras import optimizers from keras.models import Model from keras.models import Input from keras_contrib.layers import CRF from keras_contrib import losses from keras_contrib import metrics. Number of sentences in the training dataset: 43163 Number of sentences in the test dataset : 4796. Evaluation and testing. verbose=2).

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