AWS Machine Learning Blog

FEBRUARY 21, 2025

Data exploration and model development were conducted using well-known machine learning (ML) tools such as Jupyter or Apache Zeppelin notebooks. Apache Hive was used to provide a tabular interface to data stored in HDFS, and to integrate with Apache Spark SQL.

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Data Science AWS Hadoop Data Scientist 74

Dataconomy

AUGUST 7, 2023

An AI database is not merely a repository of information but a dynamic and specialized system meticulously crafted to cater to the intricate demands of AI and ML applications. Herein lies the crux of the AI database’s significance: it is tailored to meet the intricate requirements that underpin the success of AI and ML endeavors.

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ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. Hosted on Amazon ECS with tasks run on Fargate, this platform streamlines the end-to-end ML workflow, from data ingestion to model deployment.

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Tableau

DECEMBER 1, 2021

Query allowed customers from a broad range of industries to connect to clean useful data found in SQL and Cube databases. The prototype could connect to multiple data sources at the same time—a precursor to Tableau’s investments in data federation. Visual encoding is key to explaining ML models to humans.

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The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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phData

SEPTEMBER 27, 2024

Introduction: The Customer Data Modeling Dilemma You know, that thing we’ve been doing for years, trying to capture the essence of our customers in neat little profile boxes? For years, we’ve been obsessed with creating these grand, top-down customer data models. Yeah, that one.

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52

Mlearning.ai

APRIL 29, 2023

This case study as we’ve mentioned above is all about calculating metrics, and growth and helping the business analyze their data in a smart way to better forecast and plan for their future developments! Submission Suggestions 8-Week SQL Challenge: Data Bank was originally published in MLearning.ai BECOME a WRITER at MLearning.ai

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SQL Power BI Cloud Data Data Analysis 52

The MLOps Blog

OCTOBER 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. How do I develop my body of work?

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Tableau

DECEMBER 1, 2021

Query allowed customers from a broad range of industries to connect to clean useful data found in SQL and Cube databases. The prototype could connect to multiple data sources at the same time—a precursor to Tableau’s investments in data federation. Visual encoding is key to explaining ML models to humans.

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Pickl AI

OCTOBER 16, 2024

Summary: Relational Database Management Systems (RDBMS) are the backbone of structured data management, organising information in tables and ensuring data integrity. This article explores RDBMS’s features, advantages, applications across industries, the role of SQL, and emerging trends shaping the future of data management.

Database 52

Database SQL Big Data Analytics 52

Tableau

OCTOBER 8, 2021

Leveraging Looker’s semantic layer will provide Tableau customers with trusted, governed data at every stage of their analytics journey. With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics.

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DagsHub

DECEMBER 11, 2023

DagsHub DagsHub is a centralized Github-based platform that allows Machine Learning and Data Science teams to build, manage and collaborate on their projects. In addition to versioning code, teams can also version data, models, experiments and more. DVC can efficiently handle large files and machine learning models.

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AWS Machine Learning Blog

AUGUST 21, 2023

Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. Data professionals such as data scientists want to use the power of Apache Spark , Hive , and Presto running on Amazon EMR for fast data preparation; however, the learning curve is steep.

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Mlearning.ai

JUNE 16, 2023

Generative AI can be used to automate the data modeling process by generating entity-relationship diagrams or other types of data models and assist in UI design process by generating wireframes or high-fidelity mockups. GPT-4 Data Pipelines: Transform JSON to SQL Schema Instantly Blockstream’s public Bitcoin API.

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phData

MARCH 4, 2024

By utilizing Snowflake as its central repository for user data and integrating it with various machine-learning tools, the service would be able to store and analyze petabytes of data efficiently, providing accurate recommendations at scale.

AI 52

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Pickl AI

APRIL 6, 2023

Understand the fundamentals of data engineering: To become an Azure Data Engineer, you must first understand the concepts and principles of data engineering. Knowledge of data modeling, warehousing, integration, pipelines, and transformation is required. Hands-on experience working with SQLDW and SQL-DB.

Azure 52

Azure Data Engineer Data Engineering Data Engineering 52

DagsHub

APRIL 21, 2024

Source: [link] Similarly, while building any machine learning-based product or service, training and evaluating the model on a few real-world samples does not necessarily mean the end of your responsibilities. You need to make that model available to the end users, monitor it, and retrain it for better performance if needed.

Machine Learning 59

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Mlearning.ai

AUGUST 18, 2023

As an ML engineer you’re in charge of some code/model. MLOps cover all of the rest, how to track your experiments, how to share your work, how to version your models etc (Full list in the previous post. ). Not having a local model is not an excuse to throw organization, versioning and just good ol’ clean code patterns for.

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ML ML Python Data Modeling 52

IBM Journey to AI blog

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. What is machine learning?

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AWS Machine Learning Blog

MAY 4, 2023

Simple methods for time series forecasting use historical values of the same variable whose future values need to be predicted, whereas more complex, machine learning (ML)-based methods use additional information, such as the time series data of related variables. You should see the data imports in progress.

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AWS ML ML Data Scientist 126

Tableau

OCTOBER 8, 2021

Leveraging Looker’s semantic layer will provide Tableau customers with trusted, governed data at every stage of their analytics journey. With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics.

Tableau 98

Tableau Analytics Analytics Machine Learning 98

DataRobot

FEBRUARY 22, 2021

DataRobot’s team of elite data scientists and thought leaders have created, curated, and taught rigorous courses that empower 10X Academy students to take control of their future by gaining the skills required to solve complex problems. Your Data Science Education Starts Here.

Data Science 52

Data Science Data Scientist Citizen Data Scientist Data Analyst 52

Mlearning.ai

FEBRUARY 16, 2023

Companies can build Snowflake databases expeditiously and use them for ad-hoc analysis by making SQL queries. Machine Learning Integration Opportunities Organizations harness machine learning (ML) algorithms to make forecasts on the data. ML models, in turn, require significant volumes of adequate data to ensure accuracy.

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Pickl AI

MAY 30, 2023

Moreover, you can easily opt for 6 month certification program that pays well in the field that will allow you to gain perfection in ML. Learn the techniques in Machine Learning Use different tools for applications of ML and NLP Salary of the ML Engineer in India ranges between 3 Lakhs to 20.8 Lakhs annually.

Data Science 52

Data Science Data Mining Data Mining Data Mining 52

Pickl AI

JANUARY 9, 2025

Key Takeaways Operations Analysts optimise efficiency through data-driven decision-making. Expertise in tools like Power BI, SQL, and Python is crucial. Expertise in programs like Microsoft Excel, SQL , and business intelligence (BI) tools like Power BI or Tableau allows analysts to process and visualise data efficiently.

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The MLOps Blog

MARCH 15, 2023

If you will ask data professionals about what is the most challenging part of their day to day work, you will likely discover their concerns around managing different aspects of data before they get to graduate to the data modeling stage. You can learn more about the benefits of having a data pipeline in place here.

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Data Pipeline ETL SQL Data Quality 59

AWS Machine Learning Blog

MAY 31, 2024

Select the uploaded file and from Actions dropdown and choose the Query with S3 Select option to query the.csv data using SQL if the data was loaded correctly. In this demonstration, let’s assume that you need to remove the data related to a particular customer.

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Flipboard

MARCH 23, 2023

Applications built on top of models like ChatGPT have to watch for prompt injection, an attack first described by Riley Goodside. Prompt injection is similar to SQL injection, in which an attacker inserts a malicious SQL statement into an application’s entry field. What Is the Future?

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phData

OCTOBER 27, 2023

Using dbt to transform data into features allows engineers to take advantage of the expressibility of SQL without worrying about data lineage. Navigate to the dbt_tasty_bytes folder location in the terminal and run the command dbt run to create the data models in Snowflake, our offline feature store.

Machine Learning 52

Machine Learning Machine Learning Python ML 52

Alation

SEPTEMBER 7, 2021

Organizations need to ensure that data use adheres to policies (both organizational and regulatory). In an ideal world, you’d get compliance guidance before and as you use the data. Imagine writing a SQL query or using a BI dashboard with flags & warnings on compliance best practice within your natural workflow. In Summary.

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Data Governance Data Scientist Data Quality Data Profiling 59

DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. What is Unstructured Data?

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

phData

SEPTEMBER 28, 2023

Attach a Common Data Model Folder (preview) When you create a Dataflow from a CDM folder, you can establish a connection to a table authored in the Common Data Model (CDM) format by another application. We suggest establishing distinct Dataflows for various source types like on-premises, cloud, SQL Server, and Databricks.

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Mlearning.ai

FEBRUARY 13, 2023

With the use of keys, relational databases can easily define relationships between data elements, making them ideal for structured data like customer information, financial transactions, and product inventory. Some of the most popular relational databases include Oracle, MySQL, and Microsoft SQL Server. Popular relational DBs 2.

Database 52

Database Data Modeling Data Models Big Data 52

phData

JULY 18, 2023

Why Migrate to a Modern Data Stack? Data teams can focus on delivering higher-value data tasks with better organizational visibility. Move Beyond One-off Analytics: The Modern Data Stack empowers you to elevate your data for advanced analytics and integration of AI/ML, enabling faster generation of actionable business insights.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

Mlearning.ai

JULY 2, 2023

Protection against notorious menaces like Cross-Site Scripting (XSS), Cross-Site Request Forgery (CSRF), and SQL Injection attacks comes as a natural part of the Django experience. With Django, handling vast and intricate datasets becomes a seamless endeavor, and navigating complex data models feels like a walk in the park.

Data Science 52

Data Science Analytics Analytics Python 52

AWS Machine Learning Blog

MARCH 18, 2025

SQL is one of the key languages widely used across businesses, and it requires an understanding of databases and table metadata. This can be overwhelming for nontechnical users who lack proficiency in SQL. This application allows users to ask questions in natural language and then generates a SQL query for the users request.

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