Ocean Protocol

SEPTEMBER 29, 2023

Fantasy Football is a popular pastime for a large amount of the world, we gathered data around the past 6 seasons of player performance data to see what our community of data scientists could create. By leveraging cross-validation, we ensured the model’s assessment wasn’t reliant on a singular data split.

Cross Validation 59

Cross Validation Predictive Analytics Exploratory Data Analysis EDA 59

Pickl AI

JANUARY 3, 2024

Feature engineering in machine learning is a pivotal process that transforms raw data into a format comprehensible to algorithms. Through Exploratory Data Analysis , imputation, and outlier handling, robust models are crafted. Steps of Feature Engineering 1.

Machine Learning 52

Machine Learning Machine Learning Exploratory Data Analysis Cross Validation 52

Pickl AI

FEBRUARY 12, 2024

What is cross-validation, and why is it used in Machine Learning? Cross-validation is a technique used to assess the performance and generalization ability of Machine Learning models. The process is repeated multiple times, with each subset serving as both training and testing data.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Ocean Protocol

FEBRUARY 1, 2024

This is a unique opportunity for data people to dive into real-world data and uncover insights that could shape the future of aviation safety, understanding, airline efficiency, and pilots driving planes. When implementing these models, you’ll typically start by preprocessing your time series data (e.g.,

Exploratory Data Analysis 52

Exploratory Data Analysis Cross Validation Data Science Machine Learning 52

Towards AI

AUGUST 16, 2023

Data description: This step includes the following tasks: describe the dataset, including the input features and target feature(s); include summary statistics of the data and counts of any discrete or categorical features, including the target feature. Training: This step includes building the model, which may include cross-validation.

AI 91

AI AI Machine Learning Machine Learning 91

Analytics Vidhya

JULY 8, 2023

Introduction In today’s digital era, the power of data is undeniable, and those who possess the skills to harness its potential are leading the charge in shaping the future of technology.

Data Scientist 269

Data Scientist Data Science Analytics Analytics 269

Mlearning.ai

MARCH 15, 2023

Data Extraction, Preprocessing & EDA & Machine Learning Model development Data collection : Automatically download the stock historical prices data in CSV format and save it to the AWS S3 bucket. Data storage : Store the data in a Snowflake data warehouse by creating a data pipe between AWS and Snowflake.

AWS 52

AWS Python Exploratory Data Analysis EDA 52