Data Science Dojo

OCTOBER 31, 2024

Familiarity with data preprocessing, feature engineering, and model evaluation techniques is crucial. Additionally, knowledge of cloud platforms (AWS, Google Cloud) and experience with deployment tools (Docker, Kubernetes) are highly valuable. Prepare to discuss your experience and problem-solving abilities with these languages.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

Flipboard

NOVEMBER 17, 2023

Specify the AWS Lambda function that will interact with MongoDB Atlas and the LLM to provide responses. As always, AWS welcomes feedback. About the authors Igor Alekseev is a Senior Partner Solution Architect at AWS in Data and Analytics domain. Choose Build and after the build is successful, choose Test.

K-nearest Neighbors 169

K-nearest Neighbors AWS Clustering Database 169

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

phData

APRIL 26, 2024

Seamless data transfer between different platforms is crucial for effective data management and analytics. One common scenario that we’ve helped many clients with involves migrating data from Hive tables in a Hadoop environment to the Snowflake Data Cloud. Spark Environment Setup on EMR Cluster a. ap-southeast-2.compute.amazonaws.com

Hadoop 52

Hadoop Clustering AWS Database 52

Pickl AI

APRIL 6, 2023

Accordingly, one of the most demanding roles is that of Azure Data Engineer Jobs that you might be interested in. The following blog will help you know about the Azure Data Engineering Job Description, salary, and certification course. How to Become an Azure Data Engineer?

Azure 52

Azure Data Engineering Data Engineering Data Engineer 52

Pickl AI

JULY 25, 2023

Unfolding the difference between data engineer, data scientist, and data analyst. Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

AWS Machine Learning Blog

MAY 16, 2024

The main AWS services used are SageMaker, Amazon EMR , AWS CodeBuild , Amazon Simple Storage Service (Amazon S3), Amazon EventBridge , AWS Lambda , and Amazon API Gateway. With Amazon EMR, which provides fully managed environments like Apache Hadoop and Spark, we were able to process data faster.

AWS 117

AWS ML ML Deep Learning 117

Data Science Blog

MAY 15, 2023

Spark ist direkt auf mehreren Cloud-Plattformen verfügbar, darunter AWS, Azure und Google Cloud Platform.Apacke Spark ist jedoch mehr als nur ein Tool, es ist die Grundbasis für die meisten anderen Tools. Delta Lake baut auf Apache Spark auf und ist auf mehreren Cloud-Plattformen verfügbar, darunter AWS, Azure und Google Cloud Platform.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

AWS Machine Learning Blog

FEBRUARY 13, 2024

Augmenting the training data using techniques like cropping, rotating, and flipping images helped improve the model training data and model accuracy. Model training was accelerated by 50% through the use of the SMDDP library, which includes optimized communication algorithms designed specifically for AWS infrastructure.

AWS 123

AWS AI AI ML 123

Analytics Vidhya

MARCH 8, 2023

The Biggest Data Science Blogathon is now live! Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon. Knowledge is power. Sharing knowledge is the key to unlocking that power.”―

Data Science 345

Data Science Analytics Analytics Apache Hadoop 345

AWS Machine Learning Blog

DECEMBER 18, 2023

sales-train-data is used to store data extracted from MongoDB Atlas, while sales-forecast-output contains predictions from Canvas. In his role Igor is working with strategic partners helping them build complex, AWS-optimized architectures. Note we have two folders.

Clustering 122

Clustering AWS Database ML 122

Pickl AI

DECEMBER 25, 2024

Programming languages like Python and R are commonly used for data manipulation, visualization, and statistical modeling. Machine learning algorithms play a central role in building predictive models and enabling systems to learn from data. Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Analytics Vidhya

JANUARY 8, 2023

Hey, are you the data science geek who spends hours coding, learning a new language, or just exploring new avenues of data science? The post Data Science Blogathon 28th Edition appeared first on Analytics Vidhya. If all of these describe you, then this Blogathon announcement is for you!

Data Science 328

Data Science Analytics Analytics Hadoop 328

phData

NOVEMBER 8, 2024

Data Versioning and Time Travel Open Table Formats empower users with time travel capabilities, allowing them to access previous dataset versions. The first insert statement loads data having c_custkey between 30001 and 40000 – INSERT INTO ib_customers2 SELECT *, '11111111111111' AS HASHKEY FROM snowflake_sample_data.tpch_sf1.customer

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

Analytics Vidhya

NOVEMBER 7, 2022

Hello, fellow data science enthusiasts, did you miss imparting your knowledge in the previous blogathon due to a time crunch? Well, it’s okay because we are back with another blogathon where you can share your wisdom on numerous data science topics and connect with the community of fellow enthusiasts.

Data Science 306

Data Science Analytics Analytics Hadoop 306

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.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

O'Reilly Media

SEPTEMBER 15, 2021

Cloud certifications, specifically in AWS and Microsoft Azure, were most strongly associated with salary increases. As we’ll see later, cloud certifications (specifically in AWS and Microsoft Azure) were the most popular and appeared to have the largest effect on salaries. The top certification was for AWS (3.9%

AI 145

AI AI Azure AWS 145

Women in Big Data

OCTOBER 9, 2024

Data Ingestion: Data is collected and funneled into the pipeline using batch or real-time methods, leveraging tools like Apache Kafka, AWS Kinesis, or custom ETL scripts. Data Processing (Preparation): Ingested data undergoes processing to ensure it’s suitable for storage and analysis.

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

ODSC - Open Data Science

JUNE 7, 2023

And with the ability to handle high workloads, users can run high-powered analyses and store data at any size while bringing out the greatest value of a business’s data asset. Snowflake Snowflake is a cross-cloud platform that looks to break down data silos. So, what are you waiting for? Get your free Expo pass now !

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Read More: Advanced SQL Tips and Tricks for Data Analysts.

ETL 40

ETL Data Pipeline Data Quality Data Warehouse 40

Pickl AI

JANUARY 13, 2025

Key Skills Experience with cloud platforms (AWS, Azure). Robotics Engineer Robotics Engineers develop robotic systems that can perform tasks autonomously or semi-autonomously. Proficiency in Data Analysis tools for market research. They ensure that data is accessible for analysis by data scientists and analysts.

AI 52

AI AI Machine Learning Machine Learning 52

Pickl AI

OCTOBER 10, 2024

Below, we explore five popular data transformation tools, providing an overview of their features, use cases, strengths, and limitations. Apache Nifi Apache Nifi is an open-source data integration tool that automates system data flow. AWS Glue AWS Glue is a fully managed ETL service provided by Amazon Web Services.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

DagsHub

OCTOBER 23, 2024

General Purpose Tools These tools help manage the unstructured data pipeline to varying degrees, with some encompassing data collection, storage, processing, analysis, and visualization. DagsHub's Data Engine DagsHub's Data Engine is a centralized platform for teams to manage and use their datasets effectively.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

ODSC - Open Data Science

JANUARY 7, 2025

Environments Data science environments encompass the tools and platforms where professionals perform their work. From development environments like Jupyter Notebooks to robust cloud-hosted solutions such as AWS SageMaker, proficiency in these systems is critical.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

The MLOps Blog

JANUARY 23, 2023

However, there are some key differences that we need to consider: Size and complexity of the data In machine learning, we are often working with much larger data. Basically, every machine learning project needs data. Given the range of tools and data types, a separate data versioning logic will be necessary.

ML 52

ML ML Data Lakes Machine Learning 52

DataRobot Blog

OCTOBER 3, 2017

Enterprise data architects, data engineers, and business leaders from around the globe gathered in New York last week for the 3-day Strata Data Conference , which featured new technologies, innovations, and many collaborative ideas. 2) When data becomes information, many (incremental) use cases surface.

Data Lakes 52

Data Lakes Azure Data Pipeline Hadoop 52

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. Thats where data engineering tools come in!

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52