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Predict football punt and kickoff return yards with fat-tailed distribution using GluonTS

Flipboard

With advanced analytics derived from machine learning (ML), the NFL is creating new ways to quantify football, and to provide fans with the tools needed to increase their knowledge of the games within the game of football. Models were trained and cross-validated on the 2018, 2019, and 2020 seasons and tested on the 2021 season.

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Types of Feature Extraction in Machine Learning

Pickl AI

Summary: Feature extraction in Machine Learning is essential for transforming raw data into meaningful features that enhance model performance. Understanding techniques, such as dimensionality reduction and feature encoding, is crucial for effective data preprocessing and analysis. The global market was valued at USD 36.73

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Identifying defense coverage schemes in NFL’s Next Gen Stats

AWS Machine Learning Blog

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. Visualizing data using t-SNE.” Selvaraju, Ramprasaath R.,

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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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AI in Time Series Forecasting

Pickl AI

Advanced algorithms recognize patterns in temporal data effectively. Machine Learning models adapt to changing data dynamics for reliable predictions. Machine Learning algorithms can automatically detect patterns in large datasets, making them particularly effective for time series analysis.

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Large Language Models: A Complete Guide

Heartbeat

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

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Cheat Sheets for Data Scientists – A Comprehensive Guide

Pickl AI

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. Here, we’ll explore why Data Science is indispensable in today’s world.