Data Science Dojo

FEBRUARY 20, 2023

Machine learning (ML) is the technology that automates tasks and provides insights. It allows data scientists to build models that can automate specific tasks. It comes in many forms, with a range of tools and platforms designed to make working with ML more efficient. It also has tools for creating custom models.

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The MLOps Blog

FEBRUARY 5, 2023

This pipeline facilitates the smooth, automated flow of information, preventing many problems that enterprises face, such as data corruption, conflict, and duplication of data entries. A streaming data pipeline is an enhanced version which is able to handle millions of events in real-time at scale. Happy Learning!

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DagsHub

APRIL 21, 2024

A traditional machine learning (ML) pipeline is a collection of various stages that include data collection, data preparation, model training and evaluation, hyperparameter tuning (if needed), model deployment and scaling, monitoring, security and compliance, and CI/CD. What is MLOps?

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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

JANUARY 31, 2024

In this blog, we’ll show you how to build a robust energy price forecasting solution within the Snowflake Data Cloud ecosystem. We’ll cover how to get the data via the Snowflake Marketplace, how to apply machine learning with Snowpark , and then bring it all together to create an automated ML model to forecast energy prices.

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Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used.

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DagsHub

DECEMBER 11, 2023

It does not support the ‘dvc repro’ command to reproduce its data pipeline. DVC Released in 2017, Data Version Control ( DVC for short) is an open-source tool created by iterative. However, these tools have functional gaps for more advanced data workflows. It provides both community and enterprise editions.

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Pickl AI

MAY 15, 2024

As a Data Analyst, you’ve honed your skills in data wrangling, analysis, and communication. But the allure of tackling large-scale projects, building robust models for complex problems, and orchestrating data pipelines might be pushing you to transition into Data Science architecture.

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Mlearning.ai

JUNE 16, 2023

Increase your productivity in software development with Generative AI As I mentioned in Generative AI use case article, we are seeing AI-assisted developers. Overall Generative AI in SDLC Here is how Generative AI can help in SDLC stages (we may see more use cases as Generative AI matures).

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The MLOps Blog

MARCH 21, 2023

From gathering and processing data to building models through experiments, deploying the best ones, and managing them at scale for continuous value in production—it’s a lot. As the number of ML-powered apps and services grows, it gets overwhelming for data scientists and ML engineers to build and deploy models at scale.

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DataRobot

SEPTEMBER 14, 2021

Time and time again, we hear about the need for AI to support cross-functional teams and users. To provide the ability to integrate diverse data sources. To offer the flexibility to deploy AI solutions anywhere. The DataRobot AI Cloud Platform is the culmination of nearly a decade of pioneering AI innovation, representing 1.5

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phData

JULY 18, 2023

The good news is that there’s a concept called the Modern Data Stack that when utilized properly, consistently helps empower organizations to harness the full potential of their data. Throughout this journey, we’ve helped hundreds of clients achieve eye-opening results by moving to the Modern Data Stack.

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