Analytics Vidhya

FEBRUARY 1, 2023

The amount of data is insufficient until it does not reflect or we cannot find meaningful information that can drive business […] The post Building Customer Churn Prediction Model With Imbalance Dataset appeared first on Analytics Vidhya.

Predictive Modeling 306

Predictive Modeling Modeling Analytics IT 306

Analytics Vidhya

MARCH 10, 2021

ArticleVideo Book Introduction Ensembling is nothing but the technique to combine several individual predictive models to come up with the final predictive model. The post Basic Ensemble Techniques in Machine Learning appeared first on Analytics Vidhya.

Machine Learning 307

Machine Learning Predictive Modeling Modeling Analytics 307

Analytics Vidhya

JUNE 1, 2023

With franchise leagues like IPL and BBL, teams rely on statistical models and tools for competitive edge. Python programming predicts player performances, aiding team selections and game tactics. Python programming predicts player performances, aiding team selections and game tactics.

Predictive Modeling 291

Predictive Modeling Modeling Statistics Optimization 291

Analytics Vidhya

NOVEMBER 23, 2024

Handling missing data is one of the most common challenges in data analysis and machine learning. Regardless of the cause, these gaps can significantly impact your analysis’s or predictive models’ quality and accuracy. […] The post How to Use Pandas fillna() for Data Imputation?

Predictive Modeling 208

Predictive Modeling Machine Learning Data Collection Modeling 208

Analytics Vidhya

MAY 24, 2021

The post How to create a Stroke Prediction Model? ArticleVideo Book This article was published as a part of the Data Science Blogathon INTRODUCTION: Stroke is a medical condition that can lead to the. appeared first on Analytics Vidhya.

Predictive Modeling 271

Predictive Modeling Modeling Data Science Publishing 271

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 308

Machine Learning Metrics Modeling Analytics 308

Analytics Vidhya

FEBRUARY 4, 2022

classification refers to a predictive modeling problem where a class label is predicted for a given example of […]. The post Loan Approval Prediction Machine Learning appeared first on Analytics Vidhya.

Machine Learning 291

Machine Learning Predictive Modeling Data Processing Modeling 291

Analytics Vidhya

JULY 25, 2022

Introduction Let’s have a simple overview of what Machine Learning is. 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.

Machine Learning 271

Machine Learning Predictive Modeling Statistics Data Science 271

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 306

Machine Learning Metrics Predictive Modeling Data Science 306

O'Reilly on Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML.

Machine Learning 275

Machine Learning Modeling Testing Risk Management 275

Analytics Vidhya

JUNE 29, 2021

ArticleVideo Book Introduction: In this article, I will be implementing a predictive model on Rain Dataset to predict whether or not it will rain. The post Predictive Modelling | Rain Prediction in Australia With Python. appeared first on Analytics Vidhya.

Predictive Modeling 190

Predictive Modeling Modeling Analytics IT 190

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 272

Modeling Machine Learning Predictive Modeling Consulting 272

Analytics Vidhya

MAY 13, 2022

Introduction on AutoKeras Automated Machine Learning (AutoML) is a computerised way of determining the best combination of data preparation, model, and hyperparameters for a predictive modelling task. The AutoML model aims to automate all actions which require more time, such as algorithm selection, […].

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Predictive Modeling Machine Learning Data Science Publishing 366

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. A robust dataset is also valuable because predictions are almost always inaccurate.

Predictive Modeling 130

Predictive Modeling Forecasting Predictive Analytics Statistics 130

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

Data Science 341

Data Science Data Lake Data mining Deep Learning 341

Analytics Vidhya

DECEMBER 6, 2023

Introduction AI is experiencing a significant shift with the emergence of LLMs like GPT-4, revolutionizing machine understanding and generation of human language. emerges as a formidable tool in predictive modelling, enhancing machine learning with improved efficiency and accuracy. Alongside, xgboost 2.0

Predictive Modeling 328

Predictive Modeling Machine Learning Modeling Analytics 328

Analytics Vidhya

FEBRUARY 25, 2023

Introduction Often while working on predictive modeling, it is a common observation that most of the time model has good accuracy for the training data and lesser accuracy for the test data.

Predictive Modeling 313

Predictive Modeling Testing Machine Learning Modeling 313

CIO Business Intelligence

NOVEMBER 27, 2024

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

Data Architecture 128

Data Architecture Cost-Benefit Machine Learning Experimentation 128

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 328

Data Science Marketing Predictive Modeling Statistics 328

KDnuggets

MAY 30, 2022

A machine learning engineer is a programmer proficient in building and designing software to automate predictive models. They have a deeper focus on computer science, compared to data scientists.

Machine Learning 160

Machine Learning Predictive Modeling Software Modeling 160

KDnuggets

DECEMBER 1, 2023

Image by Author When you are getting started with machine learning, logistic regression is one of the first algorithms you’ll add to your toolbox. It's a Read more »

Predictive Modeling 158

Predictive Modeling Modeling Machine Learning IT 158

TDAN

AUGUST 17, 2021

If you are planning on using predictive algorithms, such as machine learning or data mining, in your business, then you should be aware that the amount of data collected can grow exponentially over time.

Predictive Modeling 115

Predictive Modeling Modeling Data mining Big Data 115

Analytics Vidhya

DECEMBER 22, 2022

We have various Machine Learning algorithms to build predictive models. This is the 4th article of the series of data science interview questions. In case you want to revisit the previous ones, tap here. This article will cover all you need to know about boosting algorithms.

Predictive Modeling 291

Predictive Modeling Machine Learning Data Science Modeling 291

O'Reilly on Data

JANUARY 17, 2023

Building Models. A common task for a data scientist is to build a predictive model. You know the drill: pull some data, carve it up into features, feed it into one of scikit-learn’s various algorithms. You might say that the outcome of this exercise is a performant predictive model.

Machine Learning 363

Machine Learning Predictive Modeling Software Modeling 363

KDnuggets

JUNE 4, 2024

Master the Fundamentals of Predictive Modeling with Python: An In-Depth Guide to Machine Learning Algorithms and Sci-kit Learn Implementation.

Machine Learning 128

Machine Learning Predictive Modeling Modeling 128

KDnuggets

AUGUST 31, 2022

When building a predictive model, the quality of the results depends on the data you use. In order to do so, you need to understand the difference between training and testing data in machine learning.

Machine Learning 151

Machine Learning Testing Predictive Modeling Modeling 151

Analytics Vidhya

DECEMBER 3, 2020

Introduction The general principle of ensembling is to combine the predictions of various. The post Improve your Predictive Model’s Score using a Stacking Regressor appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

Predictive Modeling 386

Predictive Modeling Data Science Publishing Modeling 386

KDnuggets

DECEMBER 23, 2021

Data Science models come with different flavors and techniques — luckily, most advanced models are based on a couple of fundamentals. Which models should you learn when you want to begin a career as Data Scientist?

Predictive Modeling 160

Predictive Modeling Modeling Data Science Machine Learning 160

Analytics Vidhya

MARCH 5, 2023

And our goal is to create a predictive model, such as Logistic Regression, etc. so that when we give the characteristics of a candidate, the model can predict whether they will recruit. Introduction In this project, we will be focusing on data from India.

Predictive Modeling 335

Predictive Modeling Strategy Modeling Analytics 335

Analytics Vidhya

MARCH 22, 2022

Introduction Feature analysis is an important step in building any predictive model. This article was published as a part of the Data Science Blogathon. It helps us in understanding the relationship between dependent and independent variables.

Predictive Modeling 332

Predictive Modeling Data Science Publishing Modeling 332

Analytics Vidhya

MAY 26, 2023

Imagine diving into the details of data analysis, predictive modeling, and ML. Envision yourself unraveling the insights and patterns for making informed decisions that shape the future. The concept of Data Science was first used at the start of the 21st century, making it a relatively new area of research and technology.

Data Science 319

Data Science Predictive Modeling Modeling Technology 319

Dataiku

FEBRUARY 25, 2021

Machine learning has become more and more accessible in the last few years. Thanks to advancements in automated machine learning (AutoML), collaborative AI , and machine learning platforms (like Dataiku ), the use of data — including for predictive modeling — across people of all different job types is on the rise.

Machine Learning 85

Machine Learning Modeling Predictive Modeling 85

DataRobot Blog

JANUARY 27, 2019

In my previous articles Predictive Model Data Prep: An Art and Science and Data Prep Essentials for Automated Machine Learning, I shared foundational data preparation tips to help you successfully. by Jen Underwood. Read More.

Machine Learning 92

Machine Learning Modeling Predictive Modeling Predictive Analytics 92

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

Cloudera

OCTOBER 14, 2020

Not many other industries have such a sophisticated business model that encompasses a culture of streamlined supply chains, predictive maintenance, and unwavering customer satisfaction. Step 1: Using the training data to create a model/classifier. Fig 2: Diagram showing how CML is used to build ML training models.

Machine Learning 97

Machine Learning Modeling Cost-Benefit Testing 97

Rocket-Powered Data Science

JULY 6, 2021

2) MLOps became the expected norm in machine learning and data science projects. MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase.

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

Dataiku

JANUARY 8, 2024

In the past few years, machine learning (ML) has gone from a discipline restricted to data scientists and engineers to the mainstream of business and analytics.

Machine Learning 81

Machine Learning Modeling Predictive Modeling Analytics 81