IBM Big Data Hub

JULY 6, 2023

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics. ” “Data science” was first used as an independent discipline in 2001.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

O'Reilly on Data

MAY 27, 2020

In 2001, just as the Lexile system was rolling out state-wide, a professor of education named Stephen Krashen took to the pages of the California School Library Journal to raise an alarm. His system was needed because “beginning teachers and librarians” were less expert at “forecasting comprehension rates” than the algorithm was.

Risk 356

Risk Testing Measurement Reporting 356

Jet Global

AUGUST 25, 2020

Let’s take a closer look at what corporate performance management is, why it’s important, and the common problems presented by many CPM software solutions. Rather, it represents the management framework put in place by corporate leadership to monitor and respond to important metrics. Budgeting, planning, and forecasting in finance.

Software 96

Software Metrics Finance Key Performance Indicator 96

Domino Data Lab

MAY 20, 2021

We present the inner workings of the SMOTE algorithm and show a simple “from scratch” implementation of SMOTE. def get_neigbours(M, k): nn = NearestNeighbors(n_neighbors=k+1, metric="euclidean").fit(M) Here is a simplified version of the SMOTE algorithm: import random import pandas as pd import numpy as np.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136