Analytics Vidhya

JUNE 1, 2023

With franchise leagues like IPL and BBL, teams rely on statistical models and tools for competitive edge. The analysis benefits fantasy […] The post The Science of T20 Cricket: Decoding Player Performance with Predictive Modeling appeared first on Analytics Vidhya.

Predictive Modeling 275

Predictive Modeling Modeling Statistics Optimization 275

Analytics Vidhya

FEBRUARY 20, 2023

Time series analysis is a statistical technique used to analyze data […] The post How to Build Your Time Series Model? Before we take up a time series problem, we must familiarise ourselves with the concept of forecasting. So now the question is, what is a time series? appeared first on Analytics Vidhya.

Modeling 275

Modeling Statistics Forecasting Analytics 275

Analytics Vidhya

NOVEMBER 23, 2021

Regression analysis is used to solve problems of prediction based on data statistical parameters. In this article, we will look at the use of a polynomial regression model on a simple example using real statistic data. The post Building an end-to-end Polynomial Regression Model in R appeared first on Analytics Vidhya.

Modeling 394

Modeling Statistics Data Science Publishing 394

Analytics Vidhya

APRIL 4, 2022

Introduction One of the key challenges in Machine Learning Model is the explainability of the ML Model that we are building. In general, ML Model is a Black Box. As Data scientists, we may understand the algorithm & statistical methods used behind the scene. […].

Modeling 270

Modeling Machine Learning Statistics Data Science 270

Analytics Vidhya

MAY 2, 2019

Introduction What is one of the most important and core concepts of statistics that enables us to do predictive modeling, and yet it often. The post Statistics 101: Introduction to the Central Limit Theorem (with implementation in R) appeared first on Analytics Vidhya.

Statistics 299

Statistics Predictive Modeling Modeling Analytics 299

O'Reilly on Data

OCTOBER 24, 2023

At some point in the near future, new models will be trained on code that they have written. At least one research group has experimented with training a generative model on content generated by generative AI, and has found that the output, over successive generations, was more tightly constrained, and less likely to be original or unique.

Modeling 225

Modeling Statistics Software Reporting 225

KDnuggets

FEBRUARY 23, 2023

Knowing these 5 statistical paradoxes is essential for data scientists to improve their analyses and machine learning models.

Statistics 157

Statistics Machine Learning Modeling Data Science 157

Analytics Vidhya

MARCH 1, 2022

Credit evaluations have progressed from being subjective decisions by the bank’s credit experts to a more statistically advanced evaluation. The post Gaussian Naive Bayes Algorithm for Credit Risk Modelling appeared first on Analytics Vidhya. Banks rapidly recognize the increased need for comprehensive credit risk […].

Risk 267

Risk Modeling Statistics Data Science 267

KDnuggets

AUGUST 14, 2019

At times it may seem Machine Learning can be done these days without a sound statistical background but those people are not really understanding the different nuances. Code written to make it easier does not negate the need for an in-depth understanding of the problem.

Machine Learning 122

Machine Learning Statistics Modeling IT 122

Analytics Vidhya

JUNE 20, 2023

SARIMA is an excellent time series forecasting technique for estimating time series […] The post SARIMA Model for Forecasting Currency Exchange Rates appeared first on Analytics Vidhya. Currency forecasting may assist people, corporations, and financial organizations make educated financial decisions.

Forecasting 346

Forecasting Modeling Analytics Statistics 346

Analytics Vidhya

JANUARY 20, 2022

Table of contents Introduction Multilevel Models Advantages of Multilevel models When do we use Multilevel Models Types of Multilevel Model Random intercept model Random coefficient model Hypothesis testing: Likelihood Ratio Testing End-Note Introduction Suppose, you have a dataset of faculty salaries of a university […].

Modeling 325

Modeling Testing Data Science Publishing 325

Analytics Vidhya

DECEMBER 23, 2021

Optimization aims to reduce training errors, and Deep Learning Optimization is concerned with finding a suitable model. The post Introduction to Linear Model for Optimization appeared first on Analytics Vidhya. Another goal of optimization in deep learning is to minimize generalization errors. In this article, we will […].

Optimization 325

Optimization Modeling Deep Learning Data Science 325

Analytics Vidhya

JULY 2, 2023

Introduction Comprehending and unleashing the intricate affinities among variables in the expansive realm of statistics is integral. Everything from data-driven decision-making to scientific discoveries to predictive modeling depends on our potential to disentangle the hidden connections and patterns within complex datasets.

Statistics 261

Statistics Predictive Modeling Data-driven Modeling 261

Dataiku

APRIL 15, 2020

Statistics can be tremendously beneficial for data scientists, both those that are new to the field and those who have been practicing for a number of years. While many data scientists do not have formal training in statistics, having a foundation of the basics can be critical.

Statistics 115

Statistics Machine Learning Modeling 115

Analytics Vidhya

MAY 4, 2022

Introduction to Random Forest Missing values have always been a concern for any statistical analysis. They significantly reduce the study’s statistical powers, which may lead to faulty conclusions. Most of the algorithms used in statistical modellings such as Linear regression, Logistic Regression, […].

Statistics 394

Statistics Data Science Publishing Modeling 394

Analytics Vidhya

OCTOBER 28, 2020

Introduction A popular and widely used statistical method for time series forecasting. The post How to Create an ARIMA Model for Time Series Forecasting in Python appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

Forecasting 210

Forecasting Modeling Statistics Data Science 210

IBM Big Data Hub

APRIL 13, 2023

After developing a machine learning model, you need a place to run your model and serve predictions. If your company is in the early stage of its AI journey or has budget constraints, you may struggle to find a deployment system for your model. Also, a column in the dataset indicates if each flight had arrived on time or late.

Modeling 90

Modeling Statistics Machine Learning Testing 90

Analytics Vidhya

JUNE 17, 2023

Data science for marketing is a discipline that combines statistical analysis, machine learning, and predictive modeling to extract meaningful patterns […] The post How to Use Data Science for Marketing? appeared first on Analytics Vidhya.

Data Science 309

Data Science Marketing Predictive Modeling Statistics 309

Analytics Vidhya

JULY 5, 2022

Introduction to Imbalanced Datasets The accuracy achieved by many of the machine learning models using traditional statistical algorithms increases by just around 2% or so when the size of the training dataset is increased from 20% to 80%. This article was published as a part of the Data Science Blogathon.

Statistics 339

Statistics Machine Learning Data Science Publishing 339

Analytics Vidhya

SEPTEMBER 29, 2020

The post How Machine Learning Models Fail to Deliver in Real-World Scenarios appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. Introduction Yesterday, my brother broke an antique at home. I began to.

Machine Learning 319

Machine Learning Modeling Data Science Publishing 319

Analytics Vidhya

OCTOBER 11, 2020

So you have successfully built your classification model. The post HOW TO CHOOSE EVALUATION METRICS FOR CLASSIFICATION MODEL appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. INTRODUCTION Yay!! What should.

Metrics 315

Metrics Modeling Data Science Publishing 315

Analytics Vidhya

OCTOBER 9, 2020

Introduction: Probabilistic Graphical Models (PGM) capture the complex relationships between random variables. The post Complete R Tutorial To Build Probabilistic Graphical Models! This article was published as a part of the Data Science Blogathon. appeared first on Analytics Vidhya.

Modeling 306

Modeling Data Science Publishing Analytics 306

Analytics Vidhya

SEPTEMBER 6, 2021

The post Q-Q plot – Ensure Your ML Model is Based on the Right Distribution appeared first on Analytics Vidhya. As the name suggests, they plot the quantiles of a sample distribution against quantiles of a theoretical distribution.

Modeling 346

Modeling Data Science Publishing Analytics 346

Analytics Vidhya

DECEMBER 16, 2020

The post Decluttering the performance measures of classification models appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. Introduction There are so many performance evaluation measures when it comes to.

Measurement 295

Measurement Modeling Data Science Publishing 295

IBM Big Data Hub

OCTOBER 3, 2023

Every week during football season, an estimated 60 million Americans pore over player statistics, point projections and trade proposals, looking for those elusive insights to guide their roster decisions and lead them to victory. But numbers only tell half the story. These features help us do just that.”

Modeling 96

Modeling Statistics Consulting Unstructured Data 96

O'Reilly on Data

SEPTEMBER 27, 2018

They recently wrote a survey paper, “A Critical Review of Fair Machine Learning,” where they carefully examined the standard statistical tools used to check for fairness in machine learning models. Continue reading Why it’s hard to design fair machine learning models.

Machine Learning 195

Machine Learning Modeling Statistics IT 195

KDnuggets

APRIL 19, 2022

Statistical performance metrics aren’t enough to pick the right models to bring to market.

Modeling 108

Modeling Data Science Statistics Metrics 108

DataCamp

MAY 5, 2020

This tutorial will define statistical bias in a machine learning model and demonstrate how to perform the test on synthetic data.

Machine Learning 96

Machine Learning Statistics Testing Measurement 96

Analytics Vidhya

JULY 20, 2021

The post Metrics to Evaluate your Classification Model to take the right decisions appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon Evaluation Metrics for Classification Problem Image source ?[link] link] Abstract The most.

Metrics 270

Metrics Modeling Data Science Publishing 270

Analytics Vidhya

JULY 23, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Logistic Regression is another statistical model which is used for. The post Geometrical Approach To Understand Logistic Regression appeared first on Analytics Vidhya.

Statistics 342

Statistics Data Science Publishing Modeling 342

Analytics Vidhya

MARCH 29, 2022

Introduction to Linear Regression Image 1: Sales vs Budget data with a linear model representation Linear regression is a statistical method that presumes a linear relationship between the input and the output variables. This article was published as a part of the Data Science Blogathon.

Statistics 265

Statistics Sales Data Science Publishing 265

Analytics Vidhya

NOVEMBER 25, 2020

The post Creating Linear Model, It’s Equation and Visualization for Analysis appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. Introduction Have you ever been tasked with visualizing the relationship between each.

Visualization 284

Visualization Modeling Data Science Publishing 284

Analytics Vidhya

JULY 25, 2022

Machine Learning is the method of teaching computer programs to do a specific task accurately (essentially a prediction) by training a predictive model using various statistical algorithms leveraging data. Introduction Let’s have a simple overview of what Machine Learning is. Source: [link] For […].

Machine Learning 267

Machine Learning Predictive Modeling Statistics Data Science 267

Rocket-Powered Data Science

JULY 6, 2023

These AI applications are essentially deep machine learning models that are trained on hundreds of gigabytes of text and that can provide detailed, grammatically correct, and “mostly accurate” text responses to user inputs (questions, requests, or queries, which are called prompts). Guess what? It isn’t.

Statistics 151

Statistics Deep Learning Machine Learning Modeling 151

Analytics Vidhya

AUGUST 5, 2019

Overview Evaluating a model is a core part of building an effective machine learning model There are several evaluation metrics, like confusion matrix, cross-validation, The post 11 Important Model Evaluation Metrics for Machine Learning Everyone should know appeared first on Analytics Vidhya.

Machine Learning 307

Machine Learning Metrics Modeling Analytics 307

Analytics Vidhya

OCTOBER 30, 2019

Overview Gaussian Mixture Models are a powerful clustering algorithm Understand how Gaussian Mixture Models work and how to implement them in Python We’ll also. The post Build Better and Accurate Clusters with Gaussian Mixture Models appeared first on Analytics Vidhya.

Modeling 259

Modeling Analytics Structured Data Statistics 259

Analytics Vidhya

MAY 28, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Logistic Regression, a statistical model is a very popular and. The post 20+ Questions to Test your Skills on Logistic Regression appeared first on Analytics Vidhya.

Testing 315

Testing Statistics Data Science Publishing 315