Data Science Dojo

JUNE 7, 2023

In this article, we will delve into the fascinating realm of Data Science and examine why it is fast becoming one of the most in-demand professions. What is data science? The primary aim is to make sense of the vast amounts of data generated daily by combining statistical analysis, programming, and data visualization.

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Pickl AI

NOVEMBER 18, 2024

Tools and Techniques Commonly Used Data Analysts rely on various tools to streamline their work. Software like Microsoft Excel and SQL helps them manipulate and query data efficiently. They use data visualisation tools like Tableau and Power BI to create compelling reports.

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Pickl AI

JULY 17, 2024

Summary: The row_number function in SQL assigns unique row numbers within defined partitions, enhancing tasks like ranking and pagination. Its integration as a window function streamlines complex operations, optimising database performance and query readability for SQL developers. SQL Server Error 26 and Methods to Resolve It.

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Pickl AI

SEPTEMBER 19, 2024

Summary: The CASE statement in SQL provides conditional logic within queries, enabling flexible data manipulation. Proper usage and optimisation enhance query performance and adaptability, making it a crucial tool for effective SQL data management. What is a CASE Statement in SQL? ELSE : An optional clause.

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Pickl AI

AUGUST 1, 2023

Aspiring and experienced Data Engineers alike can benefit from a curated list of books covering essential concepts and practical techniques. These 10 Best Data Engineering Books for beginners encompass a range of topics, from foundational principles to advanced data processing methods. What is Data Engineering?

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How to Learn Machine Learning

DECEMBER 11, 2022

Introduction to Pandas – The fundamentals Pandas is a popular and powerful open-source data analysis and manipulation library for the Python programming language. It is used by us, almighty data scientists and analysts to work with large datasets, perform complex operations, and create powerful data visualizations.

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Dataconomy

APRIL 27, 2023

They are also designed to handle concurrent access by multiple users and applications, while ensuring data integrity and transactional consistency. Examples of OLTP databases include Oracle Database, Microsoft SQL Server, and MySQL. OLAP systems support business intelligence, data mining, and other decision support applications.

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Pickl AI

APRIL 18, 2023

Data Analysis is the process of collecting, cleaning, transforming, and modeling data to extract useful information and insights. In today’s data-driven world, data analysis has become an essential skill for organizations across industries to make informed decisions and improve business outcomes.

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phData

SEPTEMBER 11, 2024

With Cortex Analyst from the Snowflake AI Data Cloud , business users can transform plain English questions into SQL queries, enabling self-service analytics and making data insights more accessible. Traditional data analysis often requires writing SQL to derive insights. Booked: Date the stay was booked.

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ODSC - Open Data Science

JULY 27, 2023

When choosing a data lake, here’s something else to consider. Emily Webber of AWS on Pretraining Large Language Models Celebrating the recent release of her popular book, Pretrain Vision and Large Language Models in Python, we spoke to Emily Webber of AWS about LLMs and AI advancements in this interview. Register now for 60% off.

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Dataconomy

MAY 2, 2023

By acquiring expertise in statistical techniques, machine learning professionals can develop more advanced and sophisticated algorithms, which can lead to better outcomes in data analysis and prediction. It is essential to delve deeply into programming books and explore new concepts to gain a competitive edge in the field.

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Mlearning.ai

SEPTEMBER 4, 2023

SQL-like Filtering with .query() query() method that allows you to perform SQL-like filtering on your DataFrame. It's like sorting your favorite books from the library. SQL Simplified: Apply SQL-like filtering using .query(). It's like crafting a secret code to unlock your data's secrets.

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ODSC - Open Data Science

JUNE 12, 2023

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling.

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Mlearning.ai

FEBRUARY 13, 2023

where each book represents a record, each chapter represents a field, and each shelf represents a table. These databases are the most common type used today and store data in a structured format using tables, rows, and columns. Some of the most popular relational databases include Oracle, MySQL, and Microsoft SQL Server.

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Snorkel AI

DECEMBER 5, 2023

In my demonstration, I store the extracted data in a Pandas dataframe. If we were to productionize this application, we would move these predictions into an appropriate SQL database for long-term use and storage. See what Snorkel can do to accelerate your data science and machine learning teams. Book a demo today.

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Snorkel AI

DECEMBER 5, 2023

In my demonstration, I store the extracted data in a Pandas dataframe. If we were to productionize this application, we would move these predictions into an appropriate SQL database for long-term use and storage. Book a demo today. See what Snorkel option is right for you.

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Mlearning.ai

JUNE 10, 2023

LLM is trained on diverse text sources like books, articles, websites, and more, allowing them to acquire a broad knowledge base and linguistic patterns. They’ve read tons of books and articles and can understand and talk like a human.

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Pickl AI

DECEMBER 5, 2024

This makes it a powerful tool for creating applications that require dynamic and up-to-date data. LangChain’s data handling capabilities allow you to seamlessly integrate data from structured databases (like SQL ) or unstructured sources (such as websites or CSV files).

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AWS Machine Learning Blog

NOVEMBER 18, 2024

Large language models (LLMs) can help uncover insights from structured data such as a relational database management system (RDBMS) by generating complex SQL queries from natural language questions, making data analysis accessible to users of all skill levels and empowering organizations to make data-driven decisions faster than ever before.

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