Flipboard

JUNE 14, 2023

Learn about some of the best Python libraries for programming Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). A lot of …

Machine Learning 153

Machine Learning Machine Learning Python Deep Learning 153

Flipboard

APRIL 24, 2025

The API is linked to an AWS Lambda function, which implements and orchestrates the processing steps described earlier using a programming language of the users choice (such as Python) in a serverless manner. She holds a PhD from the University of Michigan in Computer Science and Engineering.

SQL 152

SQL Database AWS ML 152

AWS Machine Learning Blog

MARCH 8, 2023

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. Create a custom container image for ML model training and push it to Amazon ECR.

ML 133

ML ML AWS Python 133

Flipboard

NOVEMBER 30, 2023

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML) models at any scale. Deploy traditional models to SageMaker endpoints In the following examples, we showcase how to use ModelBuilder to deploy traditional ML models.

ML 167

ML ML AWS Python 167

Flipboard

AUGUST 17, 2023

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

ML 123

ML ML AWS Data Warehouse 123

AWS Machine Learning Blog

NOVEMBER 30, 2023

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at scale. It’s a low-level API available for Java, C++, Go, JavaScript, Node.js, PHP, Ruby, and Python. For that, we are offering improvements in the Python SDK.

ML 129

ML ML AWS Python 129

Flipboard

DECEMBER 5, 2023

Available as a Python package, the framework allows users to integrate AI — from machine learning (ML) models to their … San Francisco-based SuperDuperDB, an Intel Ignite portfolio company working to simplify how teams build and deploy AI apps, today released version 0.1 of its open-source framework.

Database 168

Database Machine Learning Machine Learning ML 168

AWS Machine Learning Blog

MAY 10, 2023

Project Jupyter is a multi-stakeholder, open-source project that builds applications, open standards, and tools for data science, machine learning (ML), and computational science. Given the importance of Jupyter to data scientists and ML developers, AWS is an active sponsor and contributor to Project Jupyter.

ML 104

ML ML AWS AI 104

AWS Machine Learning Blog

OCTOBER 29, 2024

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. This post provides guidance on how you can create a video insights and summarization engine using AWS AI/ML services.

AWS 112

AWS AI AI ML 112

Women in Big Data

JANUARY 24, 2023

Women in Big Data Northwest chapter hosted a Python-AI-ML workshop, this Data Science hands-on workshop focused on Data Science Life Cycle concepts, Python, and AI/ML technical skills. He has a Bachelor’s Degree in both Computer Science and Philosophy.

ML 52

ML ML Python Data Science 52

Dataconomy

MAY 2, 2023

What do machine learning engineers do: ML engineers design and develop machine learning models The responsibilities of a machine learning engineer entail developing, training, and maintaining machine learning systems, as well as performing statistical analyses to refine test results. Is ML engineering a stressful job?

ML 110

ML ML Machine Learning Machine Learning 110

PyImageSearch

JANUARY 13, 2025

Using Python # Load a model model = YOLO("yolo11n.pt") # Predict with the model results = model("[link] First, we load the YOLO11 object detection model. We must note 2 key points: The Python approach gives us more flexibility to integrate the model into larger projects and customize the outputs programmatically. Here, yolo11n.pt

Python 107

Python Deep Learning Deep Learning Computer Science 107

AWS Machine Learning Blog

DECEMBER 6, 2024

You can try these models 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. It provides a collection of pre-trained models that you can deploy quickly, accelerating the development and deployment of ML applications.

AWS 104

AWS ML ML AI 104

O'Reilly Media

FEBRUARY 25, 2025

Hi, I am a professor of cognitive science and design at UC San Diego, and I recently wrote posts on Radar about my experiences coding with and speaking to generative AI tools like ChatGPT. Python Tutor is mainly used by students to understand and debug their homework assignment code step-by-step by seeing its call stack and data structures.

AI 84

AI AI Python Computer Science 84

AWS Machine Learning Blog

MAY 31, 2024

The Falcon 2 11B model is available on SageMaker JumpStart, a machine learning (ML) hub that provides access to built-in algorithms, FMs, and pre-built ML solutions that you can deploy quickly and get started with ML faster. strip() print(response) The code uses Falcon 2 11B to generate a Python function that writes a JSON file.

AWS 121

AWS Python ML ML 121

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.

AWS 121

AWS ML ML Data Scientist 121

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?

ML 145

ML ML Data Scientist AWS 145

AWS Machine Learning Blog

NOVEMBER 14, 2023

Examples include: Cultivating distrust in the media Undermining the democratic process Spreading false or discredited science (for example, the anti-vax movement) Advances in artificial intelligence (AI) and machine learning (ML) have made developing tools for creating and sharing fake news even easier.

Computer Science 132

Computer Science Computer Science AWS Python 132

AWS Machine Learning Blog

JANUARY 30, 2025

result = invoke_with_guardrails(prompt) print(result) Deploy DeepSeek-R1 with SageMaker JumpStart SageMaker JumpStart is a machine learning (ML) hub with FMs, built-in algorithms, and prebuilt ML solutions that you can deploy with just a few clicks. He holds a Bachelors degree in Computer Science and Bioinformatics.

AWS 135

AWS Python AI AI 135

Dataconomy

APRIL 4, 2025

Understanding of AI, ML, and NLP A strong grasp of machine learning concepts, algorithms, and natural language processing is essential in this role. Programming skills Proficiency in programming, particularly Python, is critical. This core knowledge helps in optimizing AI performance and the effectiveness of prompts.

AI 91

AI AI Natural Language Processing Machine Learning 91

AWS Machine Learning Blog

DECEMBER 24, 2024

aws sagemaker create-cluster --cli-input-json file://cluster-config.json --region $AWS_REGION You should be able to see your cluster by navigating to SageMaker Hyperpod in the AWS Management Console and see a cluster named ml-cluster listed. Step 1: Environment setup You first need to install the required Python packages for fine tuning.

AWS 106

AWS Clustering Deep Learning Deep Learning 106

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. While knowing Python, R, and SQL are expected, you’ll need to go beyond that.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

AWS Machine Learning Blog

APRIL 7, 2025

Discover Llama 4 models in SageMaker JumpStart SageMaker JumpStart provides FMs through two primary interfaces: SageMaker Studio and the Amazon SageMaker Python SDK. Alternatively, you can use the SageMaker Python SDK to programmatically access and use SageMaker JumpStart models. Malav holds a Masters degree in Computer Science.

AWS 116

AWS Machine Learning Machine Learning ML 116

AWS Machine Learning Blog

MAY 2, 2023

SageMaker provides single model endpoints , which allow you to deploy a single machine learning (ML) model against a logical endpoint. Triton supports various backends as engines to support the running and serving of various ML models for inference. base}/sagemaker-tritonserver:23.02-py3".format(

ML 87

ML ML Python Machine Learning 87

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.

AWS 104

AWS ML ML AI 104

Towards AI

JANUARY 6, 2025

Professional certificate for computer science for AI by HARVARD UNIVERSITY Professional certificate for computer science for AI is a 5-month AI course that is inclusive of self-paced videos for participants; who are beginners or possess intermediate-level understanding of artificial intelligence.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence AI AI 105

AWS Machine Learning Blog

APRIL 25, 2023

Data scientists typically carry out several iterations of experimentation in data processing and training models while working on any ML problem. They want to run this ML code and carry out the experimentation with ease of use and minimal code change.

Machine Learning 100

Machine Learning Machine Learning ML ML 100

ODSC - Open Data Science

APRIL 14, 2025

Finale Doshi Velez, PhD, Professor at Harvard University Finale Doshi-Velez is a Herchel Smith Professor in Computer Science at the Harvard Paulson School of Engineering and Applied Sciences. He has taught Python and ML since 2015 through LinkedIn Learning, Stanford, andUCSD.

Data Science 52

Data Science Machine Learning Machine Learning ML 52

AWS Machine Learning Blog

FEBRUARY 16, 2024

You can try out this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML. Invoke a SageMaker endpoint After the endpoint is deployed, you can carry out inference by using Boto3 or the SageMaker Python SDK.

Python 134

Python Machine Learning Machine Learning ML 134

Towards AI

FEBRUARY 15, 2024

AI Engineers: Your Definitive Career Roadmap Become a professional certified AI engineer by enrolling in the best AI ML Engineer certifications that help you earn skills to get the highest-paying job. Soft skills are important in computer science careers as well. Author(s): Jennifer Wales Originally published on Towards AI.

Artificial Intelligence 110

Artificial Intelligence Artificial Intelligence AI AI 110

AWS Machine Learning Blog

MARCH 3, 2025

This design simplifies the complexity of distributed training while maintaining the flexibility needed for diverse machine learning (ML) workloads, making it an ideal solution for enterprise AI development. The AWS AI/ML community offers extensive resources, including workshops and technical guidance, to support your implementation journey.

Clustering 93

Clustering AWS ML ML 93

AWS Machine Learning Blog

SEPTEMBER 18, 2023

Machine learning (ML) is becoming increasingly complex as customers try to solve more and more challenging problems. This complexity often leads to the need for distributed ML, where multiple machines are used to train a single model. SageMaker is a fully managed service for building, training, and deploying ML models.

Machine Learning 131

Machine Learning Machine Learning ML ML 131

Flipboard

MAY 12, 2023

In recent years, AI and ML have gradually evolved in a way that now every … The domain of Artificial Intelligence is blooming at a great pace.

Artificial Intelligence 123

Artificial Intelligence Artificial Intelligence ML ML 123

AWS Machine Learning Blog

SEPTEMBER 19, 2023

Technical challenges with multi-modal data further include the complexity of integrating and modeling different data types, the difficulty of combining data from multiple modalities (text, images, audio, video), and the need for advanced computer science skills and sophisticated analysis tools.

AWS 133

AWS AI AI ML 133

AWS Machine Learning Blog

APRIL 26, 2024

You can try out this model with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms and models so you can quickly get started with ML. It provides a collection of pre-trained models that you can deploy quickly and with ease, accelerating the development and deployment of ML applications.

ML 131

ML ML AWS Python 131

AWS Machine Learning Blog

JUNE 21, 2024

Amazon SageMaker JumpStart is a machine learning (ML) hub offering pre-trained models and pre-built solutions. Then we show how users can access and consume allowlisted models in the private hub using SageMaker Studio and the SageMaker Python SDK. For a list of filters you can apply, refer to SageMaker Python SDK.

AWS 119

AWS Python Machine Learning Machine Learning 119

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 153

Machine Learning Machine Learning Deep Learning Deep Learning 153