Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). We will explore how to better understand the data that these models are trained on, and how to evaluate and optimize them for real-world use. This process ensures that the dataset is of high quality and suitable for machine learning.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

Pickl AI

DECEMBER 16, 2024

Long Short-Term Memory (LSTM) A type of recurrent neural network (RNN) designed to learn long-term dependencies in sequential data. Facebook Prophet A user-friendly tool that automatically detects seasonality and trends in time series data. Cleaning Data: Address any missing values or outliers that could skew results.

AI 52

AI AI Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Analysis: This step involves applying statistical and Machine Learning techniques to analyse the cleaned data and uncover patterns, trends, and relationships.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

AWS Machine Learning Blog

FEBRUARY 10, 2023

Quantitative evaluation We utilize 2018–2020 season data for model training and validation, and 2021 season data for model evaluation. He is broadly interested in Deep Learning and Natural Language Processing. Each season consists of around 17,000 plays. Outside of work, he enjoys soccer and video games.

ML 76

ML ML Machine Learning Machine Learning 76

Pickl AI

DECEMBER 10, 2024

This process often involves cleaning data, handling missing values, and scaling features. Feature extraction automatically derives meaningful features from raw data using algorithms and mathematical techniques. Cross-validation ensures these evaluations generalise across different subsets of the data.

Machine Learning 52

Machine Learning Machine Learning Algorithm Deep Learning 52