Analytics Vidhya

FEBRUARY 21, 2022

Image designed by the author – Shanthababu Introduction Every ML Engineer and Data Scientist must understand the significance of “Hyperparameter Tuning (HPs-T)” while selecting your right machine/deep learning model and improving the performance of the model(s). This article was published as a part of the Data Science Blogathon.

ML Engineer 337

ML Engineer Data Scientist Deep Learning Data Science 337

Towards AI

FEBRUARY 21, 2023

A sensible proxy sub-question might then be: Can ChatGPT function as a competent machine learning engineer? The Set Up If ChatGPT is to function as an ML engineer, it is best to run an inventory of the tasks that the role entails. ChatGPT’s job as our ML engineer […]

ML Engineer 98

ML Engineer ML ChatGPT Computer Vision 98

AWS Machine Learning Blog

OCTOBER 22, 2024

Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. He focuses on architecting and implementing large-scale generative AI and classic ML pipeline solutions.

ML Engineer 110

ML Engineer Data Scientist Machine Learning ML 110

Marktechpost

NOVEMBER 16, 2024

It includes three self-paced courses covering generative AI basics, prompt engineering, and tools like GitHub Co-pilot and ChatGPT, with hands-on projects to apply skills in real-world scenarios. AI Prompt Engineering for Beginners This course focuses on prompt engineering for AI language tools like ChatGPT.

Artificial Intelligence 103

Artificial Intelligence Artificial Intelligence Prompt Engineer Prompt Engineering 103

Towards AI

AUGUST 7, 2024

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS Code extensions that enhance productivity and collaboration for data scientists and machine learning (ML) engineers.

Data Science 116

Data Science ML ML Engineer Data Scientist 116

Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. Data scientists and ML engineers require capable tooling and sufficient compute for their work.

ML 152

ML DevOps Data Scientist ML Engineer 152

AWS Machine Learning Blog

SEPTEMBER 20, 2023

In these scenarios, as you start to embrace generative AI, large language models (LLMs) and machine learning (ML) technologies as a core part of your business, you may be looking for options to take advantage of AWS AI and ML capabilities outside of AWS in a multicloud environment.

ML 126

ML Python Deep Learning Machine Learning 126

AWS Machine Learning Blog

FEBRUARY 11, 2025

Get started with SageMaker JumpStart SageMaker JumpStart is a machine learning (ML) hub that can help accelerate your ML journey. Deploying a Falcon 3 model through SageMaker JumpStart offers two convenient approaches: using the intuitive SageMaker JumpStart UI or implementing programmatically through the SageMaker Python SDK.

ML 81

ML Machine Learning Python Computer Vision 81

Unite.AI

JUNE 19, 2024

In world of Artificial Intelligence (AI) and Machine Learning (ML), a new professionals has emerged, bridging the gap between cutting-edge algorithms and real-world deployment. Meet the MLOps Engineer: the orchestrating the seamless integration of ML models into production environments, ensuring scalability, reliability, and efficiency.

Software Engineer 182

Software Engineer DevOps Machine Learning ML 182

Marktechpost

JANUARY 31, 2024

Data scientists and ML engineers often need help to build full-stack applications. It is a Python-based framework for data scientists and machine learning engineers. These professionals typically have a firm grasp of data and AI algorithms. This is where Taipy comes into play.

Data Scientist 133

Data Scientist Machine Learning Python ML Engineer 133

AWS Machine Learning Blog

OCTOBER 28, 2024

Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. SageMaker Model Monitor monitors the quality of SageMaker ML models in production. Your client applications invoke this endpoint to get inferences from the model.

ML 107

ML Metadata Data Scientist DevOps 107

AWS Machine Learning Blog

JANUARY 23, 2025

The solution described in this post is geared towards machine learning (ML) engineers and platform teams who are often responsible for managing and standardizing custom environments at scale across an organization. This approach helps you achieve machine learning (ML) governance, scalability, and standardization.

Automation 106

Automation DevOps Machine Learning ML 106

Pickl AI

JANUARY 30, 2023

Hence for an individual who wants to excel as a data scientist, learning Python is a must. The role of Python is not just limited to Data Science. In fact, Python finds multiple applications. It’s a universal programming language that finds application in different technologies like AI, ML, Big Data and others.

Python 97

Python DevOps Machine Learning Data Science 97

The MLOps Blog

MAY 10, 2023

When working on real-world machine learning (ML) use cases, finding the best algorithm/model is not the end of your responsibilities. Reusability & reproducibility: Building ML models is time-consuming by nature. Save vs package vs store ML models Although all these terms look similar, they are not the same.

Python 105

Python Metadata ML Machine Learning 105

Flipboard

MARCH 7, 2023

This post presents and compares options and recommended practices on how to manage Python packages and virtual environments in Amazon SageMaker Studio notebooks. Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models.

Python 123

Python Data Science Data Scientist Automation 123

IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

Data Science 170

Data Science DevOps Machine Learning Data Scientist 170

AWS Machine Learning Blog

JANUARY 28, 2025

FMEval is an open source LLM evaluation library, designed to provide data scientists and machine learning (ML) engineers with a code-first experience to evaluate LLMs for various aspects, including accuracy, toxicity, fairness, robustness, and efficiency. This allows you to keep track of your ML experiments.

LLM 103

LLM Large Language Models ML Algorithm 103

AWS Machine Learning Blog

JULY 8, 2024

As industries begin adopting processes dependent on machine learning (ML) technologies, it is critical to establish machine learning operations (MLOps) that scale to support growth and utilization of this technology. There were noticeable challenges when running ML workflows in the cloud.

Data Scientist 117

Data Scientist ML Engineer Machine Learning Data Science 117

AWS Machine Learning Blog

JUNE 23, 2023

For data scientists, moving machine learning (ML) models from proof of concept to production often presents a significant challenge. Additionally, you can use AWS Lambda directly to expose your models and deploy your ML applications using your preferred open-source framework, which can prove to be more flexible and cost-effective.

Large Language Models 100

Large Language Models ML Python Machine Learning 100

Marktechpost

DECEMBER 1, 2024

This is where Stacklock ‘s newly released Python library, Promptwright , aims to bridge the gap. Additionally, Promptwright includes a command line interface (CLI), making it convenient to execute dataset generation tasks directly from the terminal without writing additional Python scripts.

Python 88

Python LLM Data Scarcity Data Scientist 88

ODSC - Open Data Science

MARCH 10, 2025

Training Sessions Bayesian Analysis of Survey Data: Practical Modeling withPyMC Allen Downey, PhD, Principal Data Scientist at PyMCLabs Alexander Fengler, Postdoctoral Researcher at Brown University Bayesian methods offer a flexible and powerful approach to regression modeling, and PyMC is the go-to library for Bayesian inference in Python.

Data Scientist 52

Data Scientist Data Science LLM Machine Learning 52

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Machine learning (ML) projects are inherently complex, involving multiple intricate steps—from data collection and preprocessing to model building, deployment, and maintenance. To start our ML project predicting the probability of readmission for diabetes patients, you need to download the Diabetes 130-US hospitals dataset.

ML 86

ML Computer Vision Data Scientist Machine Learning 86

AWS Machine Learning Blog

NOVEMBER 21, 2023

By taking care of the undifferentiated heavy lifting, SageMaker allows you to focus on working on your machine learning (ML) models, and not worry about things such as infrastructure. Prior to working at Amazon Music, Siddharth was working at companies like Meta, Walmart Labs, Rakuten on E-Commerce centric ML Problems.

ML 108

ML Deep Learning Machine Learning DevOps 108

AWS Machine Learning Blog

DECEMBER 19, 2023

Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production at scale is challenging and requires a set of best practices.

Machine Learning 130

Machine Learning ML Engineer DevOps ML 130

AWS Machine Learning Blog

DECEMBER 10, 2024

You can try this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms and models that can be deployed with one click for running inference. Discover Pixtral 12B in SageMaker JumpStart You can access Pixtral 12B through SageMaker JumpStart in the SageMaker Studio UI and the SageMaker Python SDK.

ML 101

ML Generative AI Computer Vision ML Engineer 101

Salmon Run

DECEMBER 31, 2024

As an ML Engineer, we are generally tasked with solving some business problem with technology. Generally, unless it is a very simple problem, there would be more than one ML model involved, maybe different types of models depending on the sub-task, maybe other supporting tools such as a Search Index

ML 59

ML ML Engineer Software Engineer Python 59

Marktechpost

OCTOBER 10, 2024

Machine learning (ML) is a subset of artificial intelligence (AI) that builds algorithms capable of learning from data. Unlike traditional programming, where rules are explicitly defined, ML models learn patterns from data and make predictions or decisions autonomously. What is Machine Learning? fraud detection).

Data Science 106

Data Science Machine Learning Data Scientist ML Engineer 106

AWS Machine Learning Blog

AUGUST 22, 2024

In this post, we show you how to convert Python code that fine-tunes a generative AI model in Amazon Bedrock from local files to a reusable workflow using Amazon SageMaker Pipelines decorators. You can use Amazon SageMaker Model Building Pipelines to collaborate between multiple AI/ML teams. Create and run the SageMaker pipeline.

Generative AI 124

Generative AI Metadata Python ML 124

AWS Machine Learning Blog

FEBRUARY 7, 2025

This post, part of the Governing the ML lifecycle at scale series ( Part 1 , Part 2 , Part 3 ), explains how to set up and govern a multi-account ML platform that addresses these challenges. An enterprise might have the following roles involved in the ML lifecycles. This ML platform provides several key benefits.

ML 63

ML Data Scientist ML Engineer Data Science 63

AWS Machine Learning Blog

SEPTEMBER 4, 2024

Its scalability and load-balancing capabilities make it ideal for handling the variable workloads typical of machine learning (ML) applications. Amazon SageMaker provides capabilities to remove the undifferentiated heavy lifting of building and deploying ML models. They often work with DevOps engineers to operate those pipelines.

DevOps 103

DevOps ML Engineer ML Metadata 103

AWS Machine Learning Blog

FEBRUARY 11, 2025

in SageMaker JumpStart SageMaker JumpStart provides FMs through two primary interfaces: SageMaker Studio and the SageMaker Python SDK. SageMaker Studio is a comprehensive IDE that offers a unified, web-based interface for performing all aspects of the machine learning (ML) development lifecycle. Discover Meta SAM 2.1 Deploy Meta SAM 2.1

Computer Vision 81

Computer Vision ML Python Automation 81

AWS Machine Learning Blog

FEBRUARY 29, 2024

Creating scalable and efficient machine learning (ML) pipelines is crucial for streamlining the development, deployment, and management of ML models. Configuration files (YAML and JSON) allow ML practitioners to specify undifferentiated code for orchestrating training pipelines using declarative syntax.

Automation 119

Automation Python Machine Learning ML 119

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

ML 52

ML Python Machine Learning Data Scientist 52

Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

ML 52

ML Python Machine Learning Data Scientist 52

O'Reilly Media

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. What does a modern technology stack for streamlined ML processes look like?

DevOps 145

DevOps Software Engineer Data Scientist ML 145

Flipboard

SEPTEMBER 4, 2023

Envision yourself as an ML Engineer at one of the world’s largest companies. You make a Machine Learning (ML) pipeline that does everything, from gathering and preparing data to making predictions. This is suitable for making a variety of Python applications with other dependencies being added to it at the user’s convenience.

Machine Learning 152

Machine Learning Computer Vision Deep Learning Python 152

O'Reilly Media

MARCH 18, 2025

Bringing AI into a company means you have new roles to fill (data scientist, ML engineer) as well as new knowledge to backfill in existing roles (product, ops). We know Python. All this AI stuff is Python. Their code may pass the Python interpreter, but it’s all Java constructs. How hard could it be?

Software Development 52

Software Development Python Data Scientist AI 52