Smarten

JUNE 17, 2022

” The Information Technology Amendment Act of 2009 designated CERT-IN as the national agency to perform functions for cyber security, including the collection, analysis and dissemination of information on cyber incidents, as well as taking emergency measures to handle incidents and coordinating cyber incident response activities.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

Domino Data Lab

JUNE 8, 2021

Support Vector Machines (SVMs) are supervised learning models with a wide range of applications in text classification (Joachims, 1998), image recognition (Decoste and Schölkopf, 2002), image segmentation (Barghout, 2015), anomaly detection (Schölkopf et al., 1999) and more. Derivation of a Linear SVM. John Willey & Sons. Fisher, R.

Optimization 76

Optimization Machine Learning Measurement Data Science 76

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Introduction. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. This post describes the bsts software package, which makes it easy to fit some fairly sophisticated time series models with just a few lines of R code. by STEVEN L. Forecasting (e.g.

Forecasting 64

Forecasting Statistics Modeling Software 64

The Unofficial Google Data Science Blog

MARCH 13, 2017

Typically, causal inference in data science is framed in probabilistic terms, where there is statistical uncertainty in the outcomes as well as model uncertainty about the true causal mechanism connecting inputs and outputs. We are all familiar with linear and logistic regression models.

IT 68

IT Visualization Modeling Uncertainty 68

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

datapine

DECEMBER 28, 2021

1) What Is A Misleading Statistic? 2) Are Statistics Reliable? 3) Misleading Statistics Examples In Real Life. 4) How Can Statistics Be Misleading. 5) How To Avoid & Identify The Misuse Of Statistics? If all this is true, what is the problem with statistics? What Is A Misleading Statistic?

Statistics 363

Statistics Advertising Visualization Data mining 363