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.

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Machine Learning Metrics Predictive Modeling Data Science 306

Analytics Vidhya

JANUARY 12, 2021

Specific to Predictive Models). ArticleVideos This article was published as a part of the Data Science Blogathon. Hello, There Data science has been a vastly growing and improving. The post 5 Important things to Keep in Mind during Data Preprocessing! appeared first on Analytics Vidhya.

Predictive Modeling 361

Predictive Modeling Modeling Data Science Publishing 361

Analytics Vidhya

JUNE 24, 2021

The post Linear predictive models – Part 1 appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon Hello readers. This is part-1 of a comprehensive tutorial on Linear.

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Predictive Modeling Modeling Data Science Publishing 276

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

JUNE 1, 2023

Python programming predicts player performances, aiding team selections and game tactics. The analysis benefits fantasy […] The post The Science of T20 Cricket: Decoding Player Performance with Predictive Modeling appeared first on Analytics Vidhya.

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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

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.

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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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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

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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 144

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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

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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.

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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.

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Predictive Modeling Testing Machine Learning Modeling 313

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.

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Data Science Marketing Predictive Modeling Statistics 328

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 153

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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.

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Machine Learning Modeling Testing Risk Management 196

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.

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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?

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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 »

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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.

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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.

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Predictive Modeling Data Science Publishing Modeling 386

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.

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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.

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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 225

Modeling Machine Learning Predictive Modeling Consulting 225

Smart Data Collective

SEPTEMBER 30, 2021

But what if machine learning could be used beyond niche or individual contexts? Below, we’ll be exploring a few of the ways that machine learning can be used for improving our cities and making them smarter overall. There is growing evidence big data and machine learning can help save the environment.

Machine Learning 130

Machine Learning Cost-Benefit Optimization Forecasting 130

CIO Business Intelligence

OCTOBER 4, 2022

From delightful consumer experiences to attacking fuel costs and carbon emissions in the global supply chain, real-time data and machine learning (ML) work together to power apps that change industries. more machine learning use casesacross the company. By Bryan Kirschner, Vice President, Strategy at DataStax.

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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

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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

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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.

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KDnuggets

JANUARY 5, 2022

3 Tools to Track and Visualize the Execution of Your Python Code; 6 Predictive Models Every Beginner Data Scientist Should Master; What Makes Python An Ideal Programming Language For Startups; Alternative Feature Selection Methods in Machine Learning; Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor (..)

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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.

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Machine Learning Modeling Predictive Modeling Predictive Analytics 92

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.

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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.

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Decision Management Solutions

JANUARY 16, 2020

The Machine Learning Times (previously Predictive Analytics Times) is the only full-scale content portal devoted exclusively to predictive analytics. ” In his article, Eric warns, “Predictive models often fail to launch. In this month’s featured article, Eric Siegel, Ph.D.,

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Cloudera

OCTOBER 14, 2020

By combining profound airline operation expertise, data science, and engine analytics to a predictive maintenance schedule, Lufthansa Technik can now ensure critical parts are on the ground (OTG) when needed, instead of the entire aircraft being OTG and not producing revenue. Fig 2: Diagram showing how CML is used to build ML training models.

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Machine Learning Modeling Cost-Benefit Testing 98