DagsHub

JUNE 3, 2024

The pedestrian died, and investigators found that there was an issue with the machine learning (ML) model in the car, so it failed to identify the pedestrian beforehand. But First, Do You Really Need to Fix Your ML Model? Read more about benchmarking ML models. Let’s explore methods to improve the accuracy of an ML model.

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The MLOps Blog

DECEMBER 7, 2022

And we at deployr , worked alongside them to find the best possible answers for everyone involved and build their Data and ML Pipelines. Building data and ML pipelines: from the ground to the cloud It was the beginning of 2022, and things were looking bright after the lockdown’s end. With that out of the way, let’s dig in!

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Mlearning.ai

SEPTEMBER 24, 2023

Figure 1: Brute Force Search It is a cross-validation technique. Figure 2: K-fold Cross Validation On the one hand, it is quite simple. Running a cross-validation model of k = 10 requires you to run 10 separate models. If you like this article, please clap ? ? ?. Reference: Chopra, R., England, A.

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Heartbeat

MARCH 27, 2023

Model versioning and tracking with Comet ML Photo by Maxim Hopman on Unsplash In the first part of this article , we made a point to go through the steps that are necessary for you to log a model into the registry. The next step that I will address in this article involves the development of different models.

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Pickl AI

JULY 26, 2023

To mitigate variance in machine learning, techniques like regularization, cross-validation, early stopping, and using more diverse and balanced datasets can be employed. Cross-Validation Cross-validation is a widely-used technique to assess a model’s performance and find the optimal balance between bias and variance.

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phData

MAY 24, 2024

Snowflake Cortex is an intelligent, fully-managed service within Snowflake that lets businesses leverage the power of machine learning (ML) and artificial intelligence (AI) directly on their data with minimal ML or AI knowledge. Simply upload your documents, ask a question, and get the answer!

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DagsHub

APRIL 21, 2024

A traditional machine learning (ML) pipeline is a collection of various stages that include data collection, data preparation, model training and evaluation, hyperparameter tuning (if needed), model deployment and scaling, monitoring, security and compliance, and CI/CD. We are going to discuss all of them later in this article.

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Mlearning.ai

FEBRUARY 10, 2023

In the previous articles, we saw there are two main components of error, called avoidable bias and variance. In this article, we will see how to address them. In the next article, I will discuss how you can identify and address your error using the insight from the learning curve. References [1].Ng, Ng, Andrew. URL: htts://info.

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Mlearning.ai

FEBRUARY 27, 2023

In this article, we will take a quick but practical look at how this is done by incorporating Ensemble models such as extreme gradient boosting or XGBoost and light gradient boosting or LGB models. Grid search utilizes cross validation too, so it is crucial to provide an appropriate splitting mechanism.

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DataRobot Blog

DECEMBER 20, 2022

In this article, we’ll showcase the ability of AI to improve the quality of the potential investment’s future performance, with a specific example from the real estate segment. In this article, we’ll first take a closer look at the concept of Real Estate Data Intelligence and the potential of AI to become a game changer in this niche.

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Heartbeat

OCTOBER 23, 2023

This article explores the profound impact of health informatics, focusing on data scientists and machine learning engineers who play a pivotal role in leveraging data-driven approaches to revolutionize healthcare. They evaluate algorithms' fairness, transparency, and accountability to ensure equitable and unbiased healthcare practices.

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Heartbeat

AUGUST 29, 2023

Cross-validation : Cross-validation is a method for assessing how well a model performs when applied to fresh data. Make use of cross-validation : Before deploying your model, cross-validation can help you find overfitting and generalization issues.

Deep Learning 52

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Mlearning.ai

FEBRUARY 15, 2024

Data Science Project — Predictive Modeling on Biological Data Part III — A step-by-step guide on how to design a ML modeling pipeline with scikit-learn Functions. You can refer part-I and part-II of this article. Many ML optimizing functions assume that data has variance in the same order that means it is centered around 0.

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Mlearning.ai

MAY 23, 2023

In this article, we will explore some common data science interview questions that will help you prepare and increase your chances of success. Let us first understand the meaning of bias and variance in detail: Bias: It is a kind of error in a machine learning model when an ML Algorithm is oversimplified. What is Cross-Validation?

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Heartbeat

JUNE 14, 2023

Conclusion In this article, we introduced the concept of calibration in deep neural networks. Cross Validated] Editor’s Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners. CVPR workshops.

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Mlearning.ai

JUNE 28, 2023

{This article was written without the assistance or use of AI tools, providing an authentic and insightful exploration of PyCaret} Image by Author ‍In the rapidly evolving realm of data science, the imperative to automate machine learning workflows has become an indispensable requisite for enterprises aiming to outpace their competitors.

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Mlearning.ai

MARCH 15, 2023

This is part 2 of the three-series article. If you are here for the first time then please check out this article first. The scope of this article is quite big, we will exercise the core steps of data science, let's get started… Project Layout Here are the high-level steps for this project.

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Heartbeat

MAY 29, 2023

A small portion of the LLM ecosystem; image from scalevp.com In this article, we will provide a comprehensive guide to training, deploying, and improving LLMs. In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning.

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phData

AUGUST 1, 2023

The platform accomplishes this by using a combination of no-code visual tools, for your code-averse analysts, and code-first options, for your seasoned ML practitioners. When you don’t find something that solves your problem, you can develop your own, which is what the remainder of the article will cover.

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phData

AUGUST 1, 2023

The platform accomplishes this by using a combination of no-code visual tools, for your code-averse analysts, and code-first options, for your seasoned ML practitioners. When you don’t find something that solves your problem, you can develop your own, which is what the remainder of the article will cover.

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Mlearning.ai

JANUARY 31, 2023

Photo by the author Recently I was given a Myo armband, and this article aims to describe how such a device could be exploited to control a robotic manipulator intuitively. The test runs a 5-fold cross-validation. That is, we will move our arm as if it was the actual hand of the robot. We are in the nearby of 0.9

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Mlearning.ai

APRIL 13, 2023

Hyperbolic Kernels In this article , we will discuss the different types of kernels used in machine learning with the mathematics behind them by an example and the scenarios where each is commonly used. This is often done using techniques such as cross-validation or grid search. Gaussian Kernels (Radial Basis Function) 4.

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The MLOps Blog

JUNE 6, 2023

Complete ML model training pipeline workflow | Source But before we delve into the step-by-step model training pipeline, it’s essential to understand the basics, architecture, motivations, challenges associated with ML pipelines, and a few tools that you will need to work with. It makes the training iterations fast and trustable.

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Mlearning.ai

FEBRUARY 2, 2023

In this article, I show how a Convolutional Neural Network can be used to predict a person's age based on the person's ECG Attia et al 2019 [1], showed that a person's age could be predicted from an ECG using convolutional neural networks (CNN). doing cross-validation on the training set and a mean absolute error of 8.3

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Mlearning.ai

JUNE 6, 2023

In this article, we will delve into the world of AutoML, exploring its definition, inner workings, and its potential to reshape the future of machine learning. Model Evaluation: AutoML tools employ techniques such as cross-validation to assess the performance of the generated models.

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