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

KDnuggets

JUNE 19, 2024

Perform data integrity tests and generate model evaluation reports by writing a few lines of code.

Testing 136

Testing Machine Learning Data Integration Reporting 136

Analytics Vidhya

JANUARY 28, 2022

Introduction A Machine Learning solution to an unambiguously defined business problem is developed by a Data Scientist ot ML Engineer. The Model development process undergoes multiple iterations and finally, a model which has acceptable performance metrics on test data is taken to the production […].

Modeling 324

Modeling Machine Learning Metrics Testing 324

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 196

Machine Learning Modeling Testing Risk Management 196

Analytics Vidhya

MAY 9, 2024

Introduction Cross-validation is a machine learning technique that evaluates a model’s performance on a new dataset. It involves dividing a training dataset into multiple subsets and testing it on a new set. This prevents overfitting by encouraging the model to learn underlying trends associated with the data.

Machine Learning 314

Machine Learning Testing Modeling Analytics 314

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 339

Modeling Testing Data Science Publishing 339

Domino Data Lab

AUGUST 6, 2021

In the world of machine learning (ML) and artificial intelligence (AI), governance is a lifelong pursuit. All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards.

Machine Learning 145

Machine Learning Modeling Testing Data Science 145

Smart Data Collective

JULY 30, 2020

The article “Deep learning-based real-time VPN encrypted traffic identification methods” delves into the use of machine learning to improve encryption models. However, there are other ways that machine learning is improving the quality of VPN technology. It is also used for testing more effectively.

Machine Learning 90

Machine Learning Testing Deep Learning Advertising 90

Analytics Vidhya

AUGUST 17, 2022

A team at Google Brain developed Transformers in 2017, and they are now replacing RNN models like long short-term memory(LSTM) as the model of choice for NLP […]. The post Test your Data Science Skills on Transformers library appeared first on Analytics Vidhya.

Testing 280

Testing Data Science Publishing Modeling 280

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g.

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

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 328

Testing Statistics Data Science Publishing 328

Dataiku

APRIL 10, 2023

The process of converting a trained machine learning (ML) model into actual large-scale business and operational impact (known as operationalization) is one that can only happen once model deployment takes place.

Machine Learning 52

Machine Learning Modeling Testing Strategy 52

Domino Data Lab

NOVEMBER 2, 2021

Training a machine learning (ML) model is a process in which a machine learning algorithm is fed with training data from which it can learn.

Machine Learning 90

Machine Learning Modeling IT Testing 90

DataRobot Blog

JULY 21, 2022

Download the Machine Learning Project Checklist. Planning Machine Learning Projects. Machine learning and AI empower organizations to analyze data, discover insights, and drive decision making from troves of data. More organizations are investing in machine learning than ever before.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

Analytics Vidhya

FEBRUARY 4, 2020

Introduction Most Kaggle-like machine learning hackathons miss a core aspect of a machine learning workflow – preparing an offline evaluation environment while building an. The post How to Create a Test Set to Approximate Business Metrics Offline appeared first on Analytics Vidhya.

Metrics 279

Metrics Testing Machine Learning Analytics 279

KDnuggets

MARCH 13, 2020

I train a series of Machine Learning models using the iris dataset, construct synthetic data from the extreme points within the data and test a number of Machine Learning models in order to draw the decision boundaries from which the models make predictions in a 2D space, which is useful for illustrative purposes and understanding on how different (..)

Machine Learning 119

Machine Learning Modeling Testing 119

Analytics Vidhya

OCTOBER 26, 2021

This article was published as a part of the Data Science Blogathon Introduction Instance-based learning is an important aspect of supervised machine learning. The modus operandi of this algorithm is that the training examples are being stored and when the test […].

Modeling 288

Modeling Machine Learning Testing Data Science 288

IBM Big Data Hub

MAY 20, 2024

Machine learning (ML) has become a critical component of many organizations’ digital transformation strategy. The answer lies in the data used to train these models and how that data is derived. The answer lies in the data used to train these models and how that data is derived.

Machine Learning 87

Machine Learning Modeling Metadata Digital Transformation 87

Domino Data Lab

MARCH 11, 2021

Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and easier. Machine learning is used in almost every industry, notably finance , insurance , healthcare , and marketing. How to choose the right ML Framework.

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

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

AUGUST 21, 2023

In the streets of NYC, an upcoming AI startup named Arthur is making waves in the world of machine learning. As the buzz around generative AI grows, Arthur steps up to the plate with a revolutionary solution set to change the game for companies seeking the best language models for their jobs.

Modeling 252

Modeling Machine Learning Analytics Testing 252

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.

Machine Learning 117

Machine Learning Testing Strategy Modeling 117

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Model development. Model governance.

Modeling 194

Modeling Machine Learning Testing Metrics 194

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 285

Predictive Modeling Testing Machine Learning Modeling 285

Cloudera

JUNE 24, 2024

In the fast-evolving landscape of data science and machine learning, efficiency is not just desirable—it’s essential. Welcome to the era of Cloudera Copilot for Cloudera Machine Learning. The complexities of modern data workflows often translate into countless hours spent coding, debugging, and optimizing models.

Machine Learning 70

Machine Learning Data Science Data-driven Testing 70

Analytics Vidhya

FEBRUARY 20, 2023

Introduction Testing your machine learning model on an unseen dataset is a mandatory step to evaluate the model performance and gain insights into the overall behavior after the pre-training stage.

Machine Learning 278

Machine Learning Testing Modeling Analytics 278

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Introduction.

Machine Learning 136

Machine Learning Data Science Data Lake Modeling 136

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. The Process.

Machine Learning 97

Machine Learning Modeling Cost-Benefit Testing 97

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 380

Machine Learning Data Science Data Collection Testing 380

Analytics Vidhya

JANUARY 3, 2022

Table of Contents Introduction Machine Learning Pipeline Data Preprocessing Flow of pipeline 1. Loading Data Into Big Query Training the model Evaluating the Model Testing the model Summary Shutting down the […]. This article was published as a part of the Data Science Blogathon.

Machine Learning 378

Machine Learning Testing Data Science Publishing 378

Smart Data Collective

JANUARY 27, 2021

Machine learning technology has made cryptocurrency investing opportunities more lucrative than ever. The impact of machine learning on the market for bitcoin and other cryptocurrencies is multifaceted. Importance of machine learning in forecasting cryptocurrency prices.

Machine Learning 139

Machine Learning Forecasting Predictive Analytics Marketing 139

Smart Data Collective

OCTOBER 13, 2021

It’s similar to prices – price optimization through machine learning is a great tool to grow your revenue. What can you learn from real-market examples? Figuring out the best pricing model can be tricky. That’s where machine learning algorithms come into place. Do an A/B testing and find out.

Machine Learning 126

Machine Learning Optimization Software Modeling 126

Analytics Vidhya

JANUARY 11, 2021

Introduction The main objectives of a model validation include the testing. The post Validation of Classification Model appeared first on Analytics Vidhya. ArticleVideos This article was published as a part of the Data Science Blogathon.

Modeling 245

Modeling Testing Data Science Publishing 245

Smart Data Collective

NOVEMBER 1, 2021

Machine learning technology has become an integral part of many different design processes. Many entrepreneurs use machine learning to improve logo designs. One of the areas where machine learning has proven particularly useful has been with 3D printing. However, there are a lot of other benefits as well.

Machine Learning 135

Machine Learning Cost-Benefit Manufacturing Optimization 135

Smart Data Collective

MARCH 31, 2022

Machine learning technology is changing many sectors in tremendous ways. A lot of accountants are discovering innovative ways to take advantage of the benefits of machine learning. A lot of accountants are discovering innovative ways to take advantage of the benefits of machine learning.

Machine Learning 111

Machine Learning Insurance Finance Cost-Benefit 111

Analytics Vidhya

NOVEMBER 19, 2021

In the model-building phase of any supervised machine learning project, we train a model with the aim to learn the optimal values for all the weights and biases from labeled examples. If we use the same labeled examples for testing our model […].

Machine Learning 350

Machine Learning Testing Data Science Publishing 350

CIO Business Intelligence

APRIL 26, 2024

Once completed within two years, the platform, OneTru, will give TransUnion and its customers access to TransUnion’s behemoth trove of consumer data to fuel next-generation analytical services, machine learning models and generative AI applications, says Achanta, who is driving the effort, and held similar posts at Neustar and Walmart.

Modeling 107

Modeling IT Machine Learning Data Governance 107