Analytics Vidhya

APRIL 14, 2022

This article was published as a part of the Data Science Blogathon. Overview In this article, we will be discussing the face detection process using the Dlib HOG detection algorithm. Though in this article we will not only test the frontal face but also different angles of the image and see where our model will perform […].

Modeling 301

Modeling Testing Data Science Publishing 301

Analytics Vidhya

SEPTEMBER 10, 2021

This article was published as a part of the Data Science Blogathon Introduction With ignite, you can write loops to train the network in just a few lines, add standard metrics calculation out of the box, save the model, etc. The post Training and Testing Neural Networks on PyTorch using Ignite appeared first on Analytics Vidhya.

Testing 307

Testing Metrics Data Science Publishing 307

Analytics Vidhya

DECEMBER 22, 2021

This article was published as a part of the Data Science Blogathon Dear readers, In this blog, let’s build our own custom CNN(Convolutional Neural Network) model all from scratch by training and testing it with our custom image dataset.

Modeling 362

Modeling Data Science Testing Publishing 362

Analytics Vidhya

JUNE 14, 2022

This article was published as a part of the Data Science Blogathon. Background on Flower Classification Model Deep learning models, especially CNN (Convolutional Neural Networks), are implemented to classify different objects with the help of labeled images. For example, a […].

Modeling 246

Modeling Deep Learning Testing Data Science 246

Analytics Vidhya

JUNE 29, 2022

This article was published as a part of the Data Science Blogathon. Source: Wikipedia In this article, we shall provide some background on how multilingual multi-speaker models work and test an Indic TTS model that supports 9 languages and 17 speakers (Hindi, Malayalam, Manipuri, Bengali, Rajasthani, Tamil, Telugu, Gujarati, Kannada).

Modeling 248

Modeling Testing Data Science Publishing 248

Analytics Vidhya

JANUARY 11, 2021

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

Modeling 238

Modeling Testing Data Science Publishing 238

DataKitchen

FEBRUARY 21, 2023

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” Release New Data Engineering Work Often With Low Risk: “Testing and release processes are heavily manual tasks… automate these processes.” And automate any manual steps in deployment or testing with scripted automation tools.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

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 284

Modeling Machine Learning Testing Data Science 284

TDAN

MARCH 16, 2021

The purpose of this article is to provide a model to conduct a self-assessment of your organization’s data environment when preparing to build your Data Governance program. Take the […].

Data Governance 105

Data Governance Testing Modeling Data Quality 105

Analytics Vidhya

JULY 9, 2022

This article was published as a part of the Data Science Blogathon. 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.

Machine Learning 379

Machine Learning Data Science Data Collection Testing 379

TDAN

JUNE 6, 2023

Business models are increasingly based on software applications. Implementing an optimized test data management program […] The world is in a digital revolution. IT is operating at a faster pace than ever before and has become a vital component of modern business.

Testing 75

Testing Optimization Software Management 75

Analytics Vidhya

DECEMBER 14, 2020

This article was published as a part of the Data Science Blogathon. What is a Statistical Model? “Modeling is an art, as well as. The post All about Statistical Modeling appeared first on Analytics Vidhya.

Statistics 175

Statistics Modeling Data Science Publishing 175

Analytics Vidhya

AUGUST 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction When training a machine learning model, the model can be easily overfitted or under fitted. To avoid this, we use regularization in machine learning to properly fit the model to our test set.

Machine Learning 329

Machine Learning Testing Data Science Publishing 329

Analytics Vidhya

JANUARY 3, 2022

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

Machine Learning 377

Machine Learning Testing Data Science Publishing 377

Analytics Vidhya

NOVEMBER 19, 2021

This is article was published as a part of the Data Science Blogathon. 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 346

Machine Learning Testing Data Science Optimization 346

Smart Data Collective

OCTOBER 13, 2022

This article explores the possibilities and limits of AI in research and development. Generative design is a new approach to product development that uses artificial intelligence to generate and test many possible designs. Automated Testing of Features. It involves tasks such as inspection, testing, and evaluation.

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Testing Cost-Benefit Experimentation Optimization 112

O'Reilly on Data

DECEMBER 12, 2019

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. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

CIO Business Intelligence

MARCH 25, 2024

Modern digital organisations tend to use an agile approach to delivery, with cross-functional teams, product-based operating models , and persistent funding. But to deliver transformative initiatives, CIOs need to embrace the agile, product-based approach, and that means convincing the CFO to switch to a persistent funding model.

Modeling 124

Modeling Cost-Benefit IT ROI 124

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities. So, if you have 1 trillion data points (g.,

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

DataRobot

FEBRUARY 10, 2021

Even if all the code runs and the model seems to be spitting out reasonable answers, it’s possible for a model to encode fundamental data science mistakes that invalidate its results. These errors might seem small, but the effects can be disastrous when the model is used to make decisions in the real world.

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Modeling Deep Learning Machine Learning Testing 98

Analytics Vidhya

MARCH 10, 2022

This article was published as a part of the Data Science Blogathon.

Testing 254

Testing Data Science Publishing Modeling 254

O'Reilly on Data

MAY 25, 2021

GPT-3 is essentially an auto-complete bot whose underlying Machine Learning (ML) model has been trained on vast quantities of text available on the Internet. I’d like to share my thoughts on GPT-3 in terms of risks and countermeasures, and discuss real examples of how I have interacted with the model to support my learning journey.

Modeling 346

Modeling Marketing Testing Machine Learning 346

DataKitchen

OCTOBER 28, 2021

This article was originally published in Forbes. Authors of an article published by McKinsey Global Institute assert that “more human vigilance is needed to critically analyze the unfair biases that can become baked in and scaled by AI systems.” What Is AI Bias?

Testing 130

Testing IT Manufacturing Metrics 130

Smarten

JANUARY 10, 2024

Engaging Technology – It is perhaps no surprise that Musk decided to give his AI model a bit of a personality. Training Models – The current Grok training model is based on 33 billion parameters, as compared to ChatGPT 3.5 with a 175 billion parameter training model and GPT 4 with 1.76 trillion parameters.

Marketing 52

Marketing Modeling IT Digital Transformation 52

O'Reilly on Data

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Researchers are finding more and more ways to extract training data from ChatGPT and other models. And the space is moving quickly: SORA , OpenAI’s text-to-video model, is yet to be released and has already taken the world by storm.

Modeling 275

Modeling Machine Learning Risk Advertising 275

O'Reilly on Data

FEBRUARY 16, 2023

That’s what beta tests are for. Large language models like ChatGPT and Google’s LaMDA aren’t designed to give correct results. The ability of these models to “make up” stuff is interesting, and as I’ve suggested elsewhere , might give us a glimpse of artificial imagination.

Testing 211

Testing Statistics Modeling Optimization 211

O'Reilly on Data

DECEMBER 12, 2023

If the output of a model can’t be owned by a human, who (or what) is responsible if that output infringes existing copyright? In an article in The New Yorker , Jaron Lanier introduces the idea of data dignity, which implicitly distinguishes between training a model and generating output using a model.

Modeling 253

Modeling Software Sales Statistics 253

Analytics Vidhya

APRIL 6, 2023

Introduction This article uses to predict student performance. For many applications, including online customer service, marketing, and finance, the stock price is a crucial challenge.

Finance 300

Finance Modeling Marketing Analytics 300

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. Model Visibility.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. In this article, we turn our attention to the process itself: how do you bring a product to market? Identifying the problem.

Marketing 362

Marketing Experimentation Metrics Testing 362

O'Reilly on Data

FEBRUARY 15, 2022

But a recent discussion of Google’s new Large Language Models (LLMs), and its claim that one of these models (named Gopher) has demonstrated reading comprehension approaching human performance , has spurred some thoughts about comprehension, ambiguity, intelligence, and will. That was a choice, as was writing this article.

Testing 293

Testing Modeling Measurement IT 293

O'Reilly on Data

JUNE 13, 2023

It also generated a short program that implemented the widely used Miller-Rabin primality test. OpenAI recently opened their long-awaited Plugins feature to users of ChatGPT Plus (the paid version) using the GPT-4 model. Specifically, I was compelled to re-try my prime test. I had to try this!

Testing 209

Testing Publishing IT Risk 209

O'Reilly on Data

OCTOBER 12, 2021

Kevlin Henney and I were riffing on some ideas about GitHub Copilot , the tool for automatically generating code base on GPT-3’s language model, trained on the body of code that’s in GitHub. This article poses some questions and (perhaps) some answers, without trying to present any conclusions. Some of them are awful.

Testing 300

Testing Measurement Consulting Modeling 300

Smarten

APRIL 1, 2024

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal. If you have not registered yet, Click Here to obtain your login credentials.

Predictive Modeling 62

Predictive Modeling Testing Modeling Analytics 62

KDnuggets

MARCH 17, 2022

Check out this article on using CTGANs to create synthetic datasets for reducing privacy risks, training and testing machine learning models, and developing data-centric AI products.

Machine Learning 139

Machine Learning Testing Risk Modeling 139

Analytics Vidhya

OCTOBER 29, 2021

This article was published as a part of the Data Science Blogathon Introduction to Statistics Statistics is a type of mathematical analysis that employs quantified models and representations to analyse a set of experimental data or real-world studies. Data processing is […].

Statistics 354

Statistics Data Science Experimentation Publishing 354

Smarten

FEBRUARY 1, 2024

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal. If you have not registered yet, Click Here to obtain your login credentials.

Predictive Modeling 62

Predictive Modeling Publishing Testing Modeling 62