Remove 2024 Remove Exploratory Data Analysis Remove ML
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Predicting the 2024 U.S. Presidential Election Winner Using Machine Learning

Towards AI

Predicting the elections, however, presents challenges unique to it, such as the dynamic nature of voter preferences, non-linear interactions, and latent biases in the data. The points to cover in this article are as follows: Generating synthetic data to illustrate ML modelling for election outcomes.

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From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams

Towards AI

Last Updated on August 8, 2024 by Editorial Team Author(s): Gift Ojeabulu Originally published on Towards AI. Outline The Essence of Collaboration: From an Individual Working Environment to a Collaborative Data Science Environment. Why VS Code might be better for many data scientists and ML engineers than Jupyter Notebook.

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Data Workflows in Football Analytics: From Questions to Insights

Data Science Dojo

Explore the role and importance of data normalization You might come across certain matches that have missing data on shot outcomes, or any other metric. Correcting these issues ensures your analysis is based on clean, reliable data. Different types of models can help analyze different aspects and predict outcomes.

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2024 Tech breakdown: Understanding Data Science vs ML vs AI

Pickl AI

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. The collective strength of both forms the groundwork for AI and Data Science, propelling innovation.

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Modernize and migrate on-premises fraud detection machine learning workflows to Amazon SageMaker

AWS Machine Learning Blog

In this post, we share how Radial optimized the cost and performance of their fraud detection machine learning (ML) applications by modernizing their ML workflow using Amazon SageMaker. Businesses need for fraud detection models ML has proven to be an effective approach in fraud detection compared to traditional approaches.

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Navigating the Exciting Stages: The Journey of a Machine Learning Project Life Cycle

Towards AI

Last Updated on February 3, 2024 by Editorial Team Author(s): Kamireddy Mahendra Originally published on Towards AI. From Predicting the behavior of a customer to automating many tasks, Machine learning has shown its capacity to convert raw data into actionable insights. This process is called Exploratory Data Analysis(EDA).

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From Development to Deployment of an AI Model Using Azure

Towards AI

Last Updated on April 7, 2024 by Editorial Team Author(s): Prashant Kalepu Originally published on Towards AI. Today, we’re going to discuss about the often overlooked but incredibly crucial aspect of Building ML models, i.e, Why learning to deploy the ML model is important? Deploying machine learning models.

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