Analytics Vidhya

MARCH 14, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon. The post Introduction to K-Fold Cross-Validation in R appeared first on Analytics Vidhya. Photo by Myriam Jessier on Unsplash Prerequisites: Basic R programming.

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Analytics Vidhya

SEPTEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. The mportance of cross-validation: Are evaluation metrics […]. Introduction Evaluation metrics are used to measure the quality of the model.

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Mlearning.ai

FEBRUARY 2, 2023

Data scientists use a technique called cross validation to help estimate the performance of a model as well as prevent the model from… Continue reading on MLearning.ai »

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Pickl AI

FEBRUARY 12, 2024

Data Science interviews are pivotal moments in the career trajectory of any aspiring data scientist. Having the knowledge about the data science interview questions will help you crack the interview. Data Science skills that will help you excel professionally.

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Pickl AI

MARCH 26, 2024

Summary: The KNN algorithm in machine learning presents advantages, like simplicity and versatility, and challenges, including computational burden and interpretability issues. Nevertheless, its applications across classification, regression, and anomaly detection tasks highlight its importance in modern data analytics methodologies.

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Dataconomy

JUNE 29, 2023

Python machine learning packages have emerged as the go-to choice for implementing and working with machine learning algorithms. These libraries, with their rich functionalities and comprehensive toolsets, have become the backbone of data science and machine learning practices.

Machine Learning 113

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Pickl AI

MAY 17, 2023

Machine learning empowers the machine to perform the task autonomously and evolve based on the available data. However, while working on a Machine Learning algorithm , one may come across the problem of underfitting or overfitting. Both these aspects can impact the performance of the Machine Learning model.

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Pickl AI

MAY 24, 2023

To help you understand Python Libraries better, the blog will explain a Python Libraries for Data Science List which you can learn about. This may include for instance in Machine Learning, Data Science, Data Visualisation, image and Data Manipulation. What is a Python Library?

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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

JANUARY 29, 2024

Data Science Project — Build a Decision Tree Model with Healthcare Data Using Decision Trees to Categorize Adverse Drug Reactions from Mild to Severe Photo by Maksim Goncharenok Decision trees are a powerful and popular machine learning technique for classification tasks.

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NYU Center for Data Science

AUGUST 2, 2023

Currently an associate professor in the Department of Statistics at Columbia University, Arian’s research interests include high-dimensional statistics, computational imaging, compressed sensing, and machine learning. Prior to his work at Columbia, Arian was a postdoctoral scholar at Rice University.

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Towards AI

JULY 19, 2023

Check out the previous post to get a primer on the terms used) Outline Dealing with Class Imbalance Choosing a Machine Learning model Measures of Performance Data Preparation Stratified k-fold Cross-Validation Model Building Consolidating Results 1.

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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. Photo by Unsplash Earlier we saw how to collect the data and how to perform exploratory data analysis. Now comes the exciting part ….

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DrivenData Labs

MAY 24, 2023

The NAS is investing in new ways to bring vast amounts of data together with state-of-the-art machine learning to improve air travel for everyone. Federated learning is a technique for collaboratively training a shared machine learning model across data from multiple parties while preserving each party's data privacy.

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ODSC - Open Data Science

OCTOBER 24, 2023

The full details are in my new book “Statistical Optimization for Generative AI and Machine Learning”, available here. Both the new evaluation metric and new data synthesizer are now available as open-source libraries, respectively “GenAI Evaluation” and “NoGAN Synthesizer”. I provide a brief overview only.

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Pickl AI

NOVEMBER 2, 2023

A cheat sheet for Data Scientists is a concise reference guide, summarizing key concepts, formulas, and best practices in Data Analysis, statistics, and Machine Learning. What are Cheat Sheets in Data Science? Here, we’ll explore why Data Science is indispensable in today’s world.

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Data Science Dojo

AUGUST 24, 2023

While DevOps and MLOps share many similarities, MLOps requires a more specialized set of tools and practices to address the unique challenges posed by data-driven and computationally intensive ML workflows. Consider a scenario where a data science team without dedicated MLOps practices is developing an ML model for sales forecasting.

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Pickl AI

FEBRUARY 22, 2024

Summary: Dive into programs at Duke University, MIT, and more, covering Data Analysis, Statistical quality control, and integrating Statistics with Data Science for diverse career paths. offer modules in Statistical modelling, biostatistics, and comprehensive Data Science bootcamps, ensuring practical skills and job placement.

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Heartbeat

OCTOBER 23, 2023

Revolutionizing Healthcare through Data Science and Machine Learning Image by Cai Fang on Unsplash Introduction In the digital transformation era, healthcare is experiencing a paradigm shift driven by integrating data science, machine learning, and information technology.

Machine Learning 52

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Mlearning.ai

SEPTEMBER 24, 2023

Figure 1: Brute Force Search It is a cross-validation technique. This is a technique for evaluating Machine Learning models. It trains several models using k — 1 of the folds as training data. The remaining fold is used as test data to compute a performance measure. 2019) Data Science with Python.

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Ocean Protocol

SEPTEMBER 29, 2023

By leveraging cross-validation, we ensured the model’s assessment wasn’t reliant on a singular data split. Summary This challenge showed a great experiment testing machine learning tactics applied to a real-world entertainment industry.

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Ocean Protocol

FEBRUARY 1, 2024

Challenge Overview Objective : Building upon the insights gained from Exploratory Data Analysis (EDA), participants in this data science competition will venture into hands-on, real-world artificial intelligence (AI) & machine learning (ML). You can download the dataset directly through Desights.

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DrivenData Labs

JANUARY 11, 2023

The results of this GCMS challenge could not only support NASA scientists to more quickly analyze data, but is also a proof-of-concept of the use of data science and machine learning techniques on complex GCMS data for future missions. What motivated you to compete in this challenge?

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Ocean Protocol

AUGUST 8, 2023

We are excited to announce the winners of the first-ever invite-only data challenge hosted by Ocean Protocol! We received great feedback when tasked our data science community with the original sentiment analysis of the OCEAN token challenge, and now are able to share results from the second leg of this frontier.

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Mlearning.ai

MAY 23, 2023

Hey guys, in this blog we will see some of the most asked Data Science Interview Questions by interviewers in [year]. Data science has become an integral part of many industries, and as a result, the demand for skilled data scientists is soaring. What is Data Science?

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Mlearning.ai

NOVEMBER 23, 2023

This Only Applies to Supervised Learning Introduction If you’re like me then you probably like a more intuitive way of doing things. When it comes to machine learning, we often have that one (or two or three) “go-to” model(s) that we tend to rely on for most problems. Call-To-Action Enjoyed this blog post?

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Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

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Pickl AI

AUGUST 29, 2023

Parameter Estimation: Determine the parameters if the model by finding relevance to the data. This may involve finding values that best represent to observed data. Model Evaluation: Assess the quality of the midel by using different evaluation metrics, cross validation and techniques that prevent overfitting.

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Heartbeat

MARCH 27, 2023

This was necessary as the registry is where a machine learning practitioner can keep track of experiments and model versions. Sometimes this is a good thing as it may be beneficial to the outcome that a data scientist or machine learning practitioner may desire.

Machine Learning 52

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Pickl AI

FEBRUARY 4, 2024

Alteryx’s Capabilities Data Blending: Effortlessly combine data from multiple sources. Predictive Analytics: Leverage machine learning algorithms for accurate predictions. This makes Alteryx an indispensable tool for businesses aiming to glean insights and steer their decisions based on robust data.

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Mlearning.ai

FEBRUARY 27, 2023

Grid search utilizes cross validation too, so it is crucial to provide an appropriate splitting mechanism. Again, due to the nature of the problem we can’t just use plain k-fold cross validation. The parameter configuration that achieves the best result, will be the one to form the best estimator.

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Mlearning.ai

FEBRUARY 10, 2023

For example, if you are using regularization such as L2 regularization or dropout with your deep learning model that performs well on your hold-out-cross-validation set, then increasing the model size won’t hurt performance, it will stay the same or improve. Machine learning yearning. References [1].Ng, Ng, Andrew.

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Mlearning.ai

NOVEMBER 30, 2023

Mastering Tree-Based Models in Machine Learning: A Practical Guide to Decision Trees, Random Forests, and GBMs Image created by the author on Canva Ever wondered how machines make complex decisions? Just like a tree branches out, tree-based models in machine learning do something similar. Let’s get started!

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DrivenData Labs

APRIL 10, 2024

Summary of approach: In the end I managed to create two submissions, both employing an ensemble of models trained across all 10-fold cross-validation (CV) splits, achieving a private leaderboard (LB) score of 0.7318. I consider myself as a machine learning engineer who enjoys taking part in various machine learning competitions.

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Mlearning.ai

APRIL 13, 2023

Photo by Robo Wunderkind on Unsplash In general , a data scientist should have a basic understanding of the following concepts related to kernels in machine learning: 1. Machine learning algorithms rely on mathematical functions called “kernels” to make predictions based on input data. What are kernels?

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DrivenData Labs

MARCH 28, 2023

I am involved in an educational program where I teach machine and deep learning courses. Machine learning is my passion and I often take part in competitions. I (Hongwei Fan) am a PhD student affiliated with the Data Science Institute, Imperial College London. What motivated you to compete in this challenge?

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Heartbeat

FEBRUARY 20, 2023

First-time project and model registration Photo by Isaac Smith on Unsplash The world of machine learning and data science is awash with technicalities. Machine learning problems could grow to such an extent that you constantly lose track of what you are doing. The fix around this is model tracking.

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