Mlearning.ai

NOVEMBER 23, 2023

In this blog post, I’m going to show you how to use the lazypredict library on your dataset. You may need to import more libraries for EDA, preprocessing, and so on depending on the dataset you’re dealing with. Cross-Validation: Perform cross-validation to ensure the models generalize well.

Supervised Learning 52

Supervised Learning Cross Validation EDA Machine Learning 52

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.

Deep Learning 130

Deep Learning Deep Learning Machine Learning Machine Learning 130

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). It’s also a good practice to perform cross-validation to assess the robustness of your model.

Exploratory Data Analysis 52

Exploratory Data Analysis Data Science Cross Validation Machine Learning 52

Pickl AI

DECEMBER 16, 2024

This blog will explore the intricacies of AI Time Series Forecasting, its challenges, popular models, implementation steps, applications, tools, and future trends. Exploratory Data Analysis (EDA): Conduct EDA to identify trends, seasonal patterns, and correlations within the dataset. billion by 2030.

AI 52

AI AI Machine Learning Machine Learning 52

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 Extraction, Preprocessing & EDA : Extract & Pre-process the data using Python and perform basic Exploratory Data Analysis.

Python 52

Python AWS Exploratory Data Analysis Machine Learning 52

Heartbeat

MAY 29, 2023

It is also essential to evaluate the quality of the dataset by conducting exploratory data analysis (EDA), which involves analyzing the dataset’s distribution, frequency, and diversity of text. Use a representative and diverse validation dataset to ensure that the model is not overfitting to the training data.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78