Data Science Dojo

FEBRUARY 20, 2023

These tools will help you streamline your machine learning workflow, reduce operational overheads, and improve team collaboration and communication. Machine learning (ML) is the technology that automates tasks and provides insights. It allows data scientists to build models that can automate specific tasks.

Machine Learning 195

Machine Learning Machine Learning AWS Azure 195

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. What is data engineering?

Big Data 91

Big Data Big Data Data Engineer Data Engineering 91

Data Science Dojo

APRIL 16, 2024

Machine learning (ML) engineer Potential pay range – US$82,000 to 160,000/yr Machine learning engineers are the bridge between data science and engineering. They are responsible for building intelligent machines that transform our world.

AI 195

AI AI Machine Learning Machine Learning 195

Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

Smart Data Collective

JUNE 10, 2022

Data Engineer. In this role, you would perform batch processing or real-time processing on data that has been collected and stored. As a data engineer, you could also build and maintain data pipelines that create an interconnected data ecosystem that makes information available to data scientists.

Data Science 144

Data Science Data Scientist Machine Learning Machine Learning 144

AWS Machine Learning Blog

DECEMBER 4, 2024

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Reach out to set up a meeting with experts onsite about your AI engineering needs. This post is cowritten with Isaac Cameron and Alex Gnibus from Tecton.

ML 86

ML ML AWS AI 86

AWS Machine Learning Blog

DECEMBER 15, 2023

We are excited to announce the launch of Amazon DocumentDB (with MongoDB compatibility) integration with Amazon SageMaker Canvas , allowing Amazon DocumentDB customers to build and use generative AI and machine learning (ML) solutions without writing code. Analyze data using generative AI. Prepare data for machine learning.

Machine Learning 106

Machine Learning Machine Learning AWS ML 106

Applied Data Science

AUGUST 2, 2021

Machine learning The 6 key trends you need to know in 2021 ? Automation Automating data pipelines and models ➡️ 6. With a range of role types available, how do you find the perfect balance of Data Scientists , Data Engineers and Data Analysts to include in your team?

Data Science 130

Data Science Data Scientist ML ML 130

phData

AUGUST 6, 2024

As today’s world keeps progressing towards data-driven decisions, organizations must have quality data created from efficient and effective data pipelines. For customers in Snowflake, Snowpark is a powerful tool for building these effective and scalable data pipelines.

Data Pipeline 52

Data Pipeline Python Data Engineer Data Engineering 52

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 Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

The MLOps Blog

MAY 17, 2023

This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines. What is an ETL data pipeline in ML?

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ETL Data Pipeline ML ML 59

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. Read more to know.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

ODSC - Open Data Science

JANUARY 30, 2024

Data engineering is a hot topic in the AI industry right now. And as data’s complexity and volume grow, its importance across industries will only become more noticeable. But what exactly do data engineers do? So let’s do a quick overview of the job of data engineer, and maybe you might find a new interest.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

ODSC - Open Data Science

DECEMBER 19, 2023

Prompt engineers work closely with data scientists and machine learning engineers to ensure that the prompts are effective and that the models are producing the desired results. Data Engineer Data engineers are responsible for the end-to-end process of collecting, storing, and processing data.

Data Scientist 96

Data Scientist Machine Learning Machine Learning AI 96

ODSC - Open Data Science

FEBRUARY 17, 2023

Knowing how spaCy works means little if you don’t know how to apply core NLP skills like transformers, classification, linguistics, question answering, sentiment analysis, topic modeling, machine translation, speech recognition, named entity recognition, and others. The chart below shows what’s hot right now.

Deep Learning 111

Deep Learning Deep Learning Data Science Natural Language Processing 111

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?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Towards AI

OCTOBER 4, 2023

Advanced-Data Engineering and ML Ops with Infrastructure as Code This member-only story is on us. Photo by Markus Winkler on Unsplash This story explains how to create and orchestrate machine learning pipelines with AWS Step Functions and deploy them using Infrastructure as Code. Upgrade to access all of Medium.

Machine Learning 59

Machine Learning Machine Learning AWS ML 59

phData

JULY 19, 2024

This article was co-written by Lawrence Liu & Safwan Islam While the title ‘ Machine Learning Engineer ’ may sound more prestigious than ‘Data Engineer’ to some, the reality is that these roles share a significant overlap. Generative AI has unlocked the value of unstructured text-based data.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

AWS Machine Learning Blog

FEBRUARY 21, 2025

He specializes in large language models, cloud infrastructure, and scalable data systems, focusing on building intelligent solutions that enhance automation and data accessibility across Amazons operations. He specializes in building scalable machine learning infrastructure, distributed systems, and containerization technologies.

AWS 110

AWS Natural Language Processing Machine Learning Machine Learning 110

The MLOps Blog

SEPTEMBER 7, 2023

Best practices for building ETLs for ML Best practices for building ETLs for ML | Source: Author The significance of ETLs in machine learning projects Exploring a pivotal facet of every machine learning endeavor: ETLs. These insights are specifically curated for machine learning applications.

Machine Learning 52

Machine Learning Machine Learning ETL ML 52

ODSC - Open Data Science

JANUARY 18, 2024

Data engineering is a rapidly growing field, and there is a high demand for skilled data engineers. If you are a data scientist, you may be wondering if you can transition into data engineering. In this blog post, we will discuss how you can become a data engineer if you are a data scientist.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

ODSC - Open Data Science

JANUARY 2, 2024

We couldn’t be more excited to announce two events that will be co-located with ODSC East in Boston this April: The Data Engineering Summit and the Ai X Innovation Summit. Learn more about them below. Data Engineering Summit Our second annual Data Engineering Summit will be in-person for the first time!

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

ODSC - Open Data Science

FEBRUARY 6, 2024

Data engineering has become an integral part of the modern tech landscape, driving advancements and efficiencies across industries. So let’s explore the world of open-source tools for data engineers, shedding light on how these resources are shaping the future of data handling, processing, and visualization.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

DagsHub

SEPTEMBER 10, 2023

Join us for a month-long celebration of open-source contributions to Machine Learning and AI projects. Gain hands-on experience building datasets, models, pipelines, and more! How to participate in DagsHub's Machine Learning Challenge during Hacktoberfest? million pull/merge requests to open-source projects so far!

Machine Learning 52

Machine Learning Machine Learning Data Pipeline AI 52

Data Science Dojo

JULY 3, 2024

Data science bootcamps are intensive short-term educational programs designed to equip individuals with the skills needed to enter or advance in the field of data science. They cover a wide range of topics, ranging from Python, R, and statistics to machine learning and data visualization.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

ODSC - Open Data Science

FEBRUARY 15, 2024

We couldn’t be more excited to announce the first sessions for our second annual Data Engineering Summit , co-located with ODSC East this April. Join us for 2 days of talks and panels from leading experts and data engineering pioneers. Manual labor is no longer the only option for improving data.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

ODSC - Open Data Science

DECEMBER 14, 2023

Photo Mosaics with Nearest Neighbors: Machine Learning for Digital Art In this post, we focus on a color-matching strategy that is of particular interest to a data science or machine learning audience because it utilizes a K-nearest neighbors (KNN) modeling approach.

K-nearest Neighbors 97

K-nearest Neighbors AI AI Machine Learning 97

Mlearning.ai

APRIL 6, 2023

Automate and streamline our ML inference pipeline with SageMaker and Airflow Building an inference data pipeline on large datasets is a challenge many companies face. The Batch job automatically launches an ML compute instance, deploys the model, and processes the input data in batches, producing the output predictions.

Data Pipeline 52

Data Pipeline ML ML AWS 52

ODSC - Open Data Science

FEBRUARY 2, 2023

Just as a writer needs to know core skills like sentence structure, grammar, and so on, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and so on. Scikit-learn also earns a top spot thanks to its success with predictive analytics and general machine learning.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

Data Pipeline 40

Data Pipeline Data Governance Data Lakes Data Warehouse 40

DagsHub

MAY 7, 2024

Machine learning, particularly its subsets, deep learning, and generative ML, is currently in the spotlight. We are all still trying to figure out how to test machine learning models. What is Machine Learning Model Testing? Evaluation Vs. Testing: Are They Different?

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

MAY 7, 2024

Machine learning, particularly its subsets, deep learning, and generative ML, is currently in the spotlight. We are all still trying to figure out how to test machine learning models. What is Machine Learning Model Testing? Evaluation Vs. Testing: Are They Different?

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

OCTOBER 23, 2024

Unstructured data makes up 80% of the world's data and is growing. 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.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Women in Big Data

OCTOBER 9, 2024

These procedures are central to effective data management and crucial for deploying machine learning models and making data-driven decisions. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline. What is a Data Pipeline?

Big Data 59

Big Data Big Data Apache Kafka Data Pipeline 59

IBM Journey to AI blog

AUGUST 12, 2024

Instead, businesses tend to rely on advanced tools and strategies—namely artificial intelligence for IT operations (AIOps) and machine learning operations (MLOps)—to turn vast quantities of data into actionable insights that can improve IT decision-making and ultimately, the bottom line.

Big Data 106

Big Data Big Data ML ML 106

Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. How can data engineers address these challenges directly?

Data Governance 52

Data Governance Data Engineering Data Engineer Data Engineering 52