How to Learn Machine Learning

APRIL 26, 2025

The field of data science is now one of the most preferred and lucrative career options available in the area of data because of the increasing dependence on data for decision-making in businesses, which makes the demand for data science hires peak. And Why did it happen?). or What might be the best course of action?

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Data Science Dojo

SEPTEMBER 11, 2024

In the sales context, this ensures that sales data remains consistent, accurate, and easily accessible for analysis and reporting. Synapse Data Science: Synapse Data Science empowers data scientists to work directly with secured and governed sales data prepared by engineering teams, allowing for the efficient development of predictive models.

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Data Science Dojo

SEPTEMBER 5, 2024

Algorithms and Data Structures : Deep understanding of algorithms and data structures to develop efficient and effective software solutions. Learn computer vision using Python in the cloud Data Science Statistical Knowledge : Expertise in statistics to analyze and interpret data accurately. As per the U.S.

Computer Science 195

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Data Science Dojo

SEPTEMBER 5, 2024

Algorithms and Data Structures : Deep understanding of algorithms and data structures to develop efficient and effective software solutions. Learn computer vision using Python in the cloud Data Science Statistical Knowledge : Expertise in statistics to analyze and interpret data accurately. As per the U.S.

Computer Science 195

Computer Science Computer Science Data Science Machine Learning 195

Alation

AUGUST 31, 2021

In this blog, we will discuss how Alation provides a platform for data scientists and analysts to complete projects and analysis with speed. How will you support your key users in the Data Cloud? Your data scientists and analysts will need access if they’re to conduct modeling and analysis at speed.

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Flipboard

NOVEMBER 24, 2023

In an increasingly digital and rapidly changing world, BMW Group’s business and product development strategies rely heavily on data-driven decision-making. With that, the need for data scientists and machine learning (ML) engineers has grown significantly. A data scientist team orders a new JuMa workspace in BMW’s Catalog.

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DataRobot

MAY 11, 2021

It 10x’s our world-class AI platform by dramatically increasing the flexibility of DataRobot for data scientists who love to code and share their expertise across teams of all skill levels. Data Exploration, Visualization, and First-Class Integration. Put simply, Zepl helps make DataRobot easily customizable. Stay tuned.

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Data Science Blog

SEPTEMBER 19, 2023

By automating the provisioning and management of cloud resources through code, IaC brings a host of advantages to the development and maintenance of Data Warehouse Systems in the cloud. So why using IaC for Cloud Data Infrastructures? IaC allows these teams to collaborate more effectively.

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Data Science 101

OCTOBER 24, 2020

This is a great talk for data scientists and managers of technology teams. If you do data science in 2020 or beyond, there is a good chance the cloud will be involved.

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Flipboard

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. Hear also from Adidas, GlobalFoundries, and University of California, Irvine.

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Data Science 101

MAY 20, 2019

You can get this information as the Microsoft Azure Data Scientist Checklist. Below is the basic structure of the DP-100: Designing and Implementing a Data Science Solution on Azure. Passing the exam will qualify you for the Azure Data Scientist Associate certification. General Overview.

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Pickl AI

DECEMBER 26, 2024

For instance, a Data Science team analysing terabytes of data can instantly provision additional processing power or storage as required, avoiding bottlenecks and delays. The cloud also offers distributed computing capabilities, enabling faster processing of complex algorithms across multiple nodes.

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Data Science 101

MARCH 7, 2019

In Late January 2019, Microsoft launched 3 new certifications aimed at Data Scientists/Engineers. They launched the Microsoft Professional Program in Data Science back in 2017. Here are details about the 3 certification of interest to data scientists and data engineers. Azure Data Scientist Associate.

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Data Science 101

NOVEMBER 7, 2019

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Here they are in my order of importance (based upon my opinion).

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phData

NOVEMBER 4, 2024

Snowflake’s cloud-agnosticism, separation of storage and compute resources, and ability to handle semi-structured data have exemplified Snowflake as the best-in-class cloud data warehousing solution. Snowflake supports data sharing and collaboration across organizations without the need for complex data pipelines.

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Smart Data Collective

JUNE 20, 2022

When data leaders move to the cloud, it’s easy to get caught up in the features and capabilities of various cloud services without thinking about the day-to-day workflow of data scientists and data engineers. Failing to make production data accessible in the cloud.

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Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.

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AWS Machine Learning Blog

AUGUST 4, 2023

As a result, businesses can accelerate time to market while maintaining data integrity and security, and reduce the operational burden of moving data from one location to another. With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code.

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AWS Machine Learning Blog

OCTOBER 28, 2024

Athena returns the queried data from BigQuery to SageMaker Canvas, where you can use it for ML model training and development purposes within the no-code interface.

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Dataconomy

SEPTEMBER 4, 2023

Define data ownership, access controls, and data management processes to maintain the integrity and confidentiality of your data. Data integration: Integrate data from various sources into a centralized cloud data warehouse or data lake. Ensure that data is clean, consistent, and up-to-date.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

With SageMaker MLOps tools, teams can easily train, test, troubleshoot, deploy, and govern ML models at scale to boost productivity of data scientists and ML engineers while maintaining model performance in production. Diverse requirements from all business units were collected and considered during the design and development.

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IBM Journey to AI blog

MAY 9, 2023

At IBM, we believe it is time to place the power of AI in the hands of all kinds of “AI builders” — from data scientists to developers to everyday users who have never written a single line of code. Watsonx, IBM’s next-generation AI platform, is designed to do just that. Watsonx.ai Watsonx.ai

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AWS Machine Learning Blog

FEBRUARY 23, 2023

Amazon SageMaker Ground Truth is a fully managed data labeling service that provides flexibility to build and manage custom workflows. With Ground Truth, you can label image, video, and point cloud data for object detection, object tracking, and semantic segmentation tasks.

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Smart Data Collective

OCTOBER 27, 2021

Every organization needs data to make many decisions. The data is ever-increasing, and getting the deepest analytics about their business activities requires technical tools, analysts, and data scientists to explore and gain insight from large data sets. Google BigQuery.

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Flipboard

MARCH 22, 2023

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. Shut down the Studio app and relaunch for the changes to take effect.

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Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. But governance is a time-consuming process (for users and data stewards alike).

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SAS Software

DECEMBER 28, 2023

For the data scientists and developers who use analytics to extract insights from massive volumes of data, it’s easy to see the appeal of operating in a metacloud environment. After all, analytics workloads are not only resource-intensive – they’re also highly variable and differ in terms of importance and urgency. [.]

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Snorkel AI

MARCH 14, 2023

The combination of Google Cloud services with Snorkel AI’s data-centric AI platform accelerates training data curation for ML development 10-100x [1] and empowers enterprises to solve some of their most critical challenges by accessing all of their knowledge and data to build AI systems.

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Snorkel AI

MARCH 14, 2023

The combination of Google Cloud services with Snorkel AI’s data-centric AI platform accelerates training data curation for ML development 10-100x [1] and empowers enterprises to solve some of their most critical challenges by accessing all of their knowledge and data to build AI systems.

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AWS Machine Learning Blog

MARCH 10, 2023

As LiDAR sensors become more accessible and cost-effective, customers are increasingly using point cloud data in new spaces like robotics, signal mapping, and augmented reality. In this series, we show you how to train an object detection model that runs on point cloud data to predict the location of vehicles in a 3D scene.

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Snorkel AI

FEBRUARY 2, 2023

We started by ensuring that Snorkel Flow easily deploys on Google Cloud infrastructure, ingests data from Google Cloud data sources, and integrates with Google AI and Data Cloud services.

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Snorkel AI

FEBRUARY 2, 2023

We started by ensuring that Snorkel Flow easily deploys on Google Cloud infrastructure, ingests data from Google Cloud data sources, and integrates with Google AI and Data Cloud services.

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DataRobot Blog

MARCH 16, 2023

Data scientists run experiments. To work effectively, data scientists need agility in the form of access to enterprise data, streamlined tooling, and infrastructure that just works. We’ve tightened the loop between ML data prep , experimentation and testing all the way through to putting models into production.

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Alation

JUNE 21, 2022

The audience grew to include data scientists (who were even more scarce and expensive) and their supporting resources (e.g., After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that. Data engineers want to catalog data pipelines.

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ODSC - Open Data Science

JUNE 16, 2023

Data security posture management is particularly beneficial for organizations that have committed to a cloud-first vision and are moving away from a mixed cloud/on-premises infrastructure. Automatically find and categorize data across all clouds. Avoid exposing cloud data and reduce the attack surface.

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DataRobot Blog

SEPTEMBER 6, 2022

How do you drive collaboration across teams and achieve business value with data science projects? With AI projects in pockets across the business, data scientists and business leaders must align to inject artificial intelligence into an organization.

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Data Science 101

OCTOBER 24, 2020

This is a great talk for data scientists and managers of technology teams. If you do data science in 2020 or beyond, there is a good chance the cloud will be involved.

Data Science 52

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