Data Science Dojo

AUGUST 28, 2023

Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production. Exploratory Data Analysis (EDA) Data collection: The first step in LLMOps is to collect the data that will be used to train the LLM.

Exploratory Data Analysis 195

Exploratory Data Analysis Data Preparation Machine Learning Machine Learning 195

Dataconomy

JULY 28, 2023

Integration also helps avoid duplication and redundancy of data, providing a comprehensive view of the information. Exploratory data analysis (EDA) Before preprocessing data, conducting exploratory data analysis is crucial to understand the dataset’s characteristics, identify patterns, detect outliers, and validate missing values.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Becoming Human

MAY 15, 2023

For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis. First learn the basics of Feature Engineering, and EDA then take some different-different data sheets (data frames) and apply all the techniques you have learned to date.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Towards AI

JULY 19, 2023

Last Updated on July 19, 2023 by Editorial Team Author(s): Yashashri Shiral Originally published on Towards AI. Data Preparation — Collect data, Understand features 2. Visualize Data — Rolling mean/ Standard Deviation— helps in understanding short-term trends in data and outliers.

Cross Validation 98

Cross Validation Clustering EDA Data Preparation 98

Towards AI

AUGUST 16, 2023

Last Updated on August 17, 2023 by Editorial Team Author(s): Jeff Holmes MS MSCS Originally published on Towards AI. Data preparation: This step includes the following tasks: data preprocessing, data cleaning, and exploratory data analysis (EDA).

AI 96

AI AI Machine Learning Machine Learning 96

Iguazio

DECEMBER 14, 2023

There are 6 high-level steps in every MLOps project The 6 steps are: Initial data gathering (for exploration). Exploratory data analysis (EDA) and modeling. Data and model pipeline development (data preparation, training, evaluation, and so on).

ML 52

ML ML Data Science Data Preparation 52

ODSC - Open Data Science

AUGUST 9, 2023

A cordial greeting to all data science enthusiasts! I consider myself fortunate to have the opportunity to speak at the upcoming ODSC APAC conference slated for the 22nd of August 2023. The inferSchema parameter is set to True to infer the data types of the columns, and header is set to True to use the first row as headers.

Machine Learning 52

Machine Learning Machine Learning AWS Big Data 52