Analytics Vidhya

JANUARY 28, 2022

This article was published as a part of the Data Science Blogathon. Introduction A Machine Learning solution to an unambiguously defined business problem is developed by a Data Scientist ot ML Engineer. The post Deploying ML Models Using Kubernetes appeared first on Analytics Vidhya.

Modeling 346

Modeling Machine Learning Metrics Testing 346

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 329

Testing Statistics Data Science Publishing 329

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 […]. Data processing is […].

Statistics 358

Statistics Data Science Experimentation Publishing 358

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 301

Modeling Testing Data Science Publishing 301

Analytics Vidhya

MAY 5, 2024

Introduction Large Language Models (LLMs) are advanced natural language processing models that have achieved remarkable success in various benchmarks for mathematical reasoning. LLMs are typically trained on large datasets scraped from […] The post LLMs Exposed: Are They Just Cheating on Math Tests?

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Testing Modeling Analytics Deep Learning 306

Analytics Vidhya

SEPTEMBER 28, 2022

This article was published as a part of the Data Science Blogathon. First, you build software, test it for possible faults, and finally deploy it for the end user’s accessibility. The post Automate Model Deployment with GitHub Actions and AWS appeared first on Analytics Vidhya.

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Modeling Testing Software Data Science 337

Analytics Vidhya

APRIL 14, 2022

This article was published as a part of the Data Science Blogathon. 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 […]. The post Face Detection Using the DLIB Face Detector Model appeared first on Analytics Vidhya.

Modeling 306

Modeling Testing Data Science Publishing 306

Analytics Vidhya

JUNE 14, 2024

Introduction Evaluation of models and medical tests is significant in both data science and medicine. While data scientists use precision and recall, medics use specificity and sensitivity. However, these two domains use different metrics, which is confusing. appeared first on Analytics Vidhya.

Data Science 232

Data Science Metrics Testing Modeling 232

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 […].

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Modeling Deep Learning Testing Data Science 268

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).

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Modeling Testing Data Science Publishing 269

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 […].

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Modeling Machine Learning Testing Data Science 291

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 391

Machine Learning Data Science Data Collection Testing 391

Analytics Vidhya

JANUARY 3, 2022

This article was published as a part of the Data Science Blogathon. Table of Contents Introduction Machine Learning Pipeline Data Preprocessing Flow of pipeline 1. Loading data into Cloud Storage 3. Creating the Project in Google Cloud 2.

Machine Learning 380

Machine Learning Testing Data Science Publishing 380

Analytics Vidhya

FEBRUARY 4, 2020

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

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Metrics Testing Machine Learning Analytics 290

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 361

Machine Learning Testing Data Science Publishing 361

DataKitchen

APRIL 13, 2021

Testing and Data Observability. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Genie — Distributed big data orchestration service by Netflix.

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Testing Machine Learning Consulting Data Quality 312

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 343

Machine Learning Testing Data Science Publishing 343

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 232

Statistics Modeling Data Science Publishing 232

Analytics Vidhya

SEPTEMBER 15, 2021

This article was published as a part of the Data Science Blogathon Introduction: OVERFITTING! We do not even spend a single day without encountering this situation and then try different options to get the correct accuracy of the model on the test dataset.

Testing 343

Testing Data Science Publishing Modeling 343

O'Reilly on Data

OCTOBER 19, 2021

Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 350

IT Testing Experimentation Software 350

Analytics Vidhya

MARCH 10, 2022

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

Testing 270

Testing Data Science Publishing Modeling 270

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 196

Machine Learning Modeling Testing Risk Management 196

Domino Data Lab

JULY 15, 2021

In the multiverse of data science, the tool options continue to expand and evolve. While there are certainly engineers and scientists who may be entrenched in one camp or another (the R camp vs. Python, for example, or SAS vs. MATLAB), there has been a growing trend towards dispersion of data science tools.

Data Science 145

Data Science Visualization Enterprise Modeling 145

CIO Business Intelligence

JANUARY 19, 2024

According to data from PayScale, $99,842 is the average base salary for a data scientist in 2024. Check out our list of top big data and data analytics certifications.) The exam is designed for seasoned and high-achiever data science thought and practice leaders.

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Data Science Machine Learning Predictive Modeling Experimentation 126

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 290

Machine Learning Testing Modeling Analytics 290

Domino Data Lab

AUGUST 6, 2021

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. As such, model governance needs to be applied to each model for as long as it’s being used.

Machine Learning 145

Machine Learning Modeling Testing Data Science 145

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. There’s a substantial literature about ethics, data, and AI, so rather than repeat that discussion, we’ll leave you with a few resources.

Marketing 363

Marketing Experimentation Metrics Testing 363

O'Reilly on Data

MAY 14, 2020

Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model. In reality, many candidate models (frequently hundreds or even thousands) are created during the development process. Modelling: The model is often misconstrued as the most important component of an AI product.

Management 363

Management Experimentation B2B Machine Learning 363

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

Smart Data Collective

FEBRUARY 3, 2022

If you are a Data Scientist or Big Data Engineer, you probably find the Data Science environment configuration painful. If this is your case, you should consider using Docker for your day-to-day Data tasks. In this post, we will see how Docker can create a meaningful impact in your Data Science project.

Data Science 129

Data Science Data Processing Testing Big Data 129

Domino Data Lab

JANUARY 11, 2021

Data science is an exciting field, but it can be intimidating to get started, especially for those new to coding. Even for experienced developers and data scientists, the process of developing a model could involve stringing together many steps from many packages, in ways that might not be as elegant or efficient as one might like.

Modeling 145

Modeling Metrics Testing Data Science 145

CIO Business Intelligence

APRIL 25, 2022

An education in data science can help you land a job as a data analyst , data engineer , data architect , or data scientist. Here are the top 15 data science boot camps to help you launch a career in data science, according to reviews and data collected from Switchup.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

Smart Data Collective

AUGUST 18, 2021

Fortunately, recruitment software and tools allow for data-driven decision-making that eliminates human bias and uncertainties, ultimately helping you make better decisions during the hiring process with greater accuracy and peace of mind. Big data has the potential to greatly improve the hiring process for our business.

Data Science 139

Data Science Management Big Data Metrics 139

O'Reilly on Data

FEBRUARY 19, 2021

The data that powers ML applications is as important as code, making version control difficult; outputs are probabilistic rather than deterministic, making testing difficult; training a model is processor intensive and time consuming, making rapid build/deploy cycles difficult. But there are new challengers out there.

Data Lake 294

Data Lake Data Warehouse Machine Learning Modeling 294

Data Science 101

MAY 20, 2019

You can get this information as the Microsoft Azure Data Scientist Checklist. Below is the basic structure of the DP-100: Designing and Implementing a Data Science Solution on Azure. Passing the exam will qualify you for the Azure Data Scientist Associate certification. R Power BI Publishing Azure ML models.

Data Science 111

Data Science Machine Learning Deep Learning Testing 111

Analytics Vidhya

NOVEMBER 20, 2023

Whether it’s supply chain logistics or approving a loan for a customer, data holds the key. Leveraging the power of data science in the medical field can yield groundbreaking results. By analyzing vast amounts […] The post What is Data Science’s Role in Modern Medicine?

Data Science 313

Data Science Data-driven Analytics IT 313

Analytics Vidhya

JUNE 17, 2022

This article was published as a part of the Data Science Blogathon. Introduction on MLIB In this MLIB article, we will be working to predict the insurance charges that will be imposed on a customer who is willing to take the health insurance, and for predicting the same PySpark’s MLIB library is the driver to […].

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Insurance Data Science Publishing Analytics 381