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 241

Machine Learning Modeling Statistics IT 241

Analytics Vidhya

DECEMBER 2, 2024

As indicated in machine learning and statistical modeling, the assessment of models impacts results significantly. Accuracy falls short of capturing these trade-offs as a means to work with imbalanced datasets, especially in terms of precision and recall ratios.

Machine Learning 208

Machine Learning Statistics Measurement Modeling 208

Analytics Vidhya

NOVEMBER 25, 2024

The normal distribution, also known as the Gaussian distribution, is one of the most widely used probability distributions in statistics and machine learning. Understanding its core properties, mean and variance, is important for interpreting data and modelling real-world phenomena.

Statistics 204

Statistics Machine Learning Modeling Analytics 204

Analytics Vidhya

JULY 9, 2024

Introduction Few concepts in mathematics and information theory have profoundly impacted modern machine learning and artificial intelligence, such as the Kullback-Leibler (KL) divergence.

Machine Learning 256

Machine Learning Metrics Deep Learning Statistics 256

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 291

Modeling Machine Learning Statistics Data Science 291

Analytics Vidhya

MAY 21, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Whenever we build any machine learning model, we feed it. The post 4 Ways to Evaluate your Machine Learning Model: Cross-Validation Techniques (with Python code) appeared first on Analytics Vidhya.

Machine Learning 258

Machine Learning Modeling Data Science Publishing 258

Analytics Vidhya

OCTOBER 12, 2020

Introduction Machine learning is about building a predictive model using historical data. The post Quick Guide to Evaluation Metrics for Supervised and Unsupervised Machine Learning appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

Machine Learning 308

Machine Learning Metrics Predictive Modeling Data Science 308

Analytics Vidhya

JUNE 26, 2023

Introduction “Data Science” and “Machine Learning” are prominent technological topics in the 25th century. They are utilized by various entities, ranging from novice computer science students to major organizations like Netflix and Amazon. appeared first on Analytics Vidhya.

Machine Learning 324

Machine Learning Data Science Big Data Measurement 324

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 123

Machine Learning Statistics Modeling IT 123

O'Reilly on Data

JULY 15, 2019

As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. What cultural and organizational changes will be needed to accommodate the rise of machine and learning and AI?

Machine Learning 52

Machine Learning Management Enterprise Risk Management 52

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 354

Statistics Machine Learning Data Science Publishing 354

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

Modeling 278

Modeling Machine Learning Predictive Modeling Consulting 278

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 291

Predictive Modeling Modeling Statistics Optimization 291

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 291

Modeling Statistics Forecasting Analytics 291

David Menninger's Analyst Perspectives

JANUARY 15, 2025

So, it is essential to incorporate external data in forecasting, planning and budgeting, especially for predictive analytics and machine learning to support artificial intelligence. This provides useful information about what to do next time to achieve a better outcome and how to refine the model to improve its accuracy.

Predictive Modeling 130

Predictive Modeling Forecasting Predictive Analytics Statistics 130

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 330

Data Science Marketing Predictive Modeling Statistics 330

O'Reilly on Data

NOVEMBER 19, 2024

Reasons for using RAG are clear: large language models (LLMs), which are effectively syntax engines, tend to “hallucinate” by inventing answers from pieces of their training data. See the primary sources “ REALM: Retrieval-Augmented Language Model Pre-Training ” by Kelvin Guu, et al., at Facebook—both from 2020.

Unstructured Data 318

Unstructured Data Structured Data Statistics Modeling 318

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 344

Modeling Testing Data Science Publishing 344

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 397

Statistics Data Science Publishing Modeling 397

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 271

Risk Modeling Statistics Data Science 271

KDnuggets

FEBRUARY 23, 2023

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

Statistics 159

Statistics Machine Learning Modeling Data Science 159

Analytics Vidhya

MAY 27, 2023

This post will examine how statistical machine-learning […] The post End-to-End Case Study: Bike Sharing Demand Prediction appeared first on Analytics Vidhya. The purpose of this analysis is to understand the patterns and trends in bike usage and make predictions about future demand.

Machine Learning 320

Machine Learning Statistics Analytics Forecasting 320

Analytics Vidhya

JULY 9, 2022

Introduction In order to build machine learning models that are highly generalizable to a wide range of test conditions, training models with high-quality data is essential. Unfortunately, a large part of the data collected is not readily ideal for training machine learning models, this increases […].

Machine Learning 391

Machine Learning Data Science Data Collection Testing 391

Analytics Vidhya

SEPTEMBER 17, 2022

Introduction Conventionally, an automatic speech recognition (ASR) system leverages a single statistical language model to rectify ambiguities, regardless of context. This article was published as a part of the Data Science Blogathon. However, we can improve the system’s accuracy by leveraging contextual information.

Metadata 400

Metadata Statistics Data Science Publishing 400

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

Management 363

Management Machine Learning Experimentation Metrics 363

Analytics Vidhya

JUNE 8, 2023

Introduction Imagine you’re working on a dataset to build a Machine Learning model and don’t want to spend too much effort on exploratory data analysis codes. You may sometimes find it confusing to sort, filter, or group data to obtain the required information.

Machine Learning 371

Machine Learning Modeling Analytics IT 371

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 330

Metrics Modeling Data Science Publishing 330

Business Over Broadway

AUGUST 4, 2020

Only 1/4 of respondents said they do research to advance the state of the art of machine learning. We know that data professionals, when working on data science and machine learning projects, spend their time on a variety of different activities (e.g., Experimentation and iteration to improve existing ML models (39%).

Machine Learning 145

Machine Learning Data Science Statistics Experimentation 145

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI As model building become easier, the problem of high-quality data becomes more evident than ever. In this post, we shed some light on various efforts toward generating data for machine learning (ML) models.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

Smart Data Collective

NOVEMBER 1, 2020

Machines, artificial intelligence (AI), and unsupervised learning are reshaping the way businesses vie for a place under the sun. With that being said, let’s have a closer look at how unsupervised machine learning is omnipresent in all industries. What Is Unsupervised Machine Learning? Source ].

Machine Learning 145

Machine Learning Data mining Visualization Statistics 145

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 235

Forecasting Modeling Statistics Data Science 235

Analytics Vidhya

MAY 9, 2024

Introduction Cross-validation is a machine learning technique that evaluates a model’s performance on a new dataset. This prevents overfitting by encouraging the model to learn underlying trends associated with the data.

Machine Learning 320

Machine Learning Testing Modeling Analytics 320

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 354

Statistics Data Science Publishing Modeling 354

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 308

Measurement Modeling Data Science Publishing 308

Analytics Vidhya

FEBRUARY 17, 2022

Introduction Machine learning models are garbage in garbage-out boxes, and it is essential to address any missing data before feeding it to your model. This article was published as a part of the Data Science Blogathon. Missing data in your dataset could be due to multiple reasons like 1) The data was not available.

Machine Learning 329

Machine Learning Data Science Publishing Modeling 329

Analytics Vidhya

MAY 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In Machine learning or Deep Learning, some of the models. The post How to transform features into Normal/Gaussian Distribution appeared first on Analytics Vidhya.

Deep Learning 337

Deep Learning Machine Learning Data Science Publishing 337

Smart Data Collective

OCTOBER 8, 2021

Learn how genetic algorithms and machine learning can help hedge fund organizations manage a business. This article looks at how genetic algorithms (GA) and machine learning (ML) can help hedge fund organizations. Modern machine learning and back-testing; how quant hedge funds use it. Pre-train tests.

Machine Learning 132

Machine Learning Testing Strategy Modeling 132