Pickl AI

MAY 30, 2024

Summary: The Data Science and Data Analysis life cycles are systematic processes crucial for uncovering insights from raw data. Quality data is foundational for accurate analysis, ensuring businesses stay competitive in the digital landscape. Understanding their life cycles is critical to unlocking their potential.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Flipboard

MARCH 22, 2023

Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. Snowflake is an AWS Partner with multiple AWS accreditations, including AWS competencies in machine learning (ML), retail, and data and analytics. Matt Marzillo is a Sr. Partner Sales Engineer at Snowflake.

AWS 123

AWS Data Preparation Azure Data Scientist 123

Dataconomy

JULY 28, 2023

Data scientists must decide on appropriate strategies to handle missing values, such as imputation with mean or median values or removing instances with missing data. The choice of approach depends on the impact of missing data on the overall dataset and the specific analysis or model being used.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Pickl AI

JULY 12, 2023

We are living in a world where data drives decisions. Data manipulation in Data Science is the fundamental process in data analysis. The data professionals deploy different techniques and operations to derive valuable information from the raw and unstructured data. What is Data Manipulation?

Data Analysis 52

Data Analysis Data Analysis Database Clean Data 52

Heartbeat

MAY 29, 2023

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.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

Pickl AI

JULY 24, 2024

Clear Formatting Remove any inconsistent formatting that may interfere with data processing, such as extra spaces or incomplete sentences. Validate Data Perform a final quality check to ensure the cleaned data meets the required standards and that the results from data processing appear logical and consistent.

Data Quality 52

Data Quality Machine Learning Machine Learning Clean Data 52

phData

FEBRUARY 7, 2024

Snowpark Use Cases Data Science Streamlining data preparation and pre-processing: Snowpark’s Python, Java, and Scala libraries allow data scientists to use familiar tools for wrangling and cleaning data directly within Snowflake, eliminating the need for separate ETL pipelines and reducing context switching.

Python 52

Python ML ML SQL 52

Pickl AI

DECEMBER 3, 2024

Common Challenges in Data Preparation One of the most common challenges when preparing UCI datasets is dealing with missing data. Missing values can arise for various reasons, such as errors during data collection or inconsistencies in reporting.

Machine Learning 52

Machine Learning Machine Learning Clustering Supervised Learning 52

AWS Machine Learning Blog

DECEMBER 19, 2024

Data preprocessing Text data can come from diverse sources and exist in a wide variety of formats such as PDF, HTML, JSON, and Microsoft Office documents such as Word, Excel, and PowerPoint. Its rare to already have access to text data that can be readily processed and fed into an LLM for training. Graham Horwood is Sr.

AWS 106

AWS Machine Learning Machine Learning Data Preparation 106