AWS Machine Learning Blog

NOVEMBER 29, 2024

About the Authors Shreyas Subramanian is a Principal Data Scientist and helps customers by using generative AI and deep learning to solve their business challenges using AWS services. Shreyas has a background in large-scale optimization and ML and in the use of ML and reinforcement learning for accelerating optimization tasks.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

You marked your calendars, you booked your hotel, and you even purchased the airfare. Now all you need is some guidance on generative AI and machine learning (ML) sessions to attend at this twelfth edition of re:Invent. This year, learn about LLMOps, not just MLOps!

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Flipboard

DECEMBER 2, 2024

This long-awaited capability is a game changer for our customers using the power of AI and machine learning (ML) inference in the cloud. The scale down to zero feature presents new opportunities for how businesses can approach their cloud-based ML operations.

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AWS Machine Learning Blog

OCTOBER 30, 2024

This will deploy a Lambda function (book-hotel-lambda) and a CloudWatch log group ( /lex/book-hotel-bot ) in the us-east-1 Region. This will deploy a Lambda function (book-hotel-lambda) and a CloudWatch log group ( /lex/book-hotel-bot ) in the us-west-2 Region. In the Languages section, choose English (US).

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Flipboard

APRIL 23, 2025

About the authors Praveen Chamarthi brings exceptional expertise to his role as a Senior AI/ML Specialist at Amazon Web Services, with over two decades in the industry. When hes not advancing ML workloads, Praveen can be found immersed in books or enjoying science fiction films.

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How to Learn Machine Learning

MAY 2, 2025

This is where Azure Machine Learning shines by democratizing access to advanced AI capabilities. Azure Machine Learning is Microsoft’s enterprise-grade service that provides a comprehensive environment for data scientists and ML engineers to build, train, deploy, and manage machine learning models at scale.

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Mlearning.ai

APRIL 4, 2023

Unlock the Power of Deep Learning in Finance with These Essential Reads Continue reading on MLearning.ai »

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Dataconomy

MAY 2, 2023

The machine learning systems developed by Machine Learning Engineers are crucial components used across various big data jobs in the data processing pipeline. Additionally, Machine Learning Engineers are proficient in implementing AI or ML algorithms. Is ML engineering a stressful job?

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AWS Machine Learning Blog

APRIL 4, 2025

For Source name , enter a name that is the same as the modelIdentifier in your prompt and inference response dataset. { "prompt": "If books cost $10.21 Calculate the total cost of the books before the discount.n2. nnThe cost of one book is $10.21. Original price: $153.15 Original price: $153.15 Determine the discount amount.n3.

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AWS Machine Learning Blog

MARCH 18, 2024

He is passionate about working with customers and is motivated by the goal of democratizing machine learning. He focuses on core challenges related to deploying complex ML applications, multi-tenant ML models, cost optimizations, and making deployment of deep learning models more accessible.

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PyImageSearch

JANUARY 13, 2025

Figure 13: Multi-Object Tracking for Pose Estimation (source: output video generated by running the above code) How to Train with YOLO11 Training a deep learning model is a crucial step in building a solution for tasks like object detection. When exporting, we can choose from formats like ONNX, TensorRT, Core ML, and more.

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Heartbeat

OCTOBER 18, 2023

Whether finding the perfect movie to watch , discovering a new book, or uncovering hidden gems in a vast online store, recommender systems are pivotal in delivering tailored user experiences. In this article, we embark on a journey to explore the transformative potential of deep learning in revolutionizing recommender systems.

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Data Science Dojo

JUNE 14, 2023

Learn how the synergy of AI and ML algorithms in paraphrasing tools is redefining communication through intelligent algorithms that enhance language expression. The most revolutionary technology that enables this is called machine learning. Paraphrasing tools in AI and ML algorithms Machine learning is a subset of AI.

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Data Science Dojo

JUNE 14, 2023

Learn how the synergy of AI and ML algorithms in paraphrasing tools is redefining communication through intelligent algorithms that enhance language expression. The most revolutionary technology that enables this is called machine learning. Paraphrasing tools in AI and ML algorithms Machine learning is a subset of AI.

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Towards AI

MAY 30, 2024

If you’ve enjoyed the list of courses at Gen AI 360, wait for this… Today, I am super excited to finally announce that we at towards_AI have released our first book: Building LLMs for Production. This 470-page book is all about LLMs and how to work with them. Good morning, fellow learners. Get your copy now! Our must-read articles 1.

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Mlearning.ai

FEBRUARY 24, 2023

Dive Into Deep Learning — Part1 In this series, I will be sharing with you my summarization of the Dive into deep learning book, I started reading it as a review of what I know about DL and also to explore new concepts I might have missed. The book walks us through an example of predicting house prices.

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ODSC - Open Data Science

SEPTEMBER 21, 2023

The following is an extract from Andrew McMahon’s book , Machine Learning Engineering with Python, Second Edition. Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business. First of all, the ultimate goal of your work is to generate value.

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ODSC - Open Data Science

MARCH 17, 2023

How to Deploy a Deep Learning Model with Jina, Announcing GPT-4, and Multimodal Visual Question Answering How to Deploy a Deep Learning Model with Jina (and Design a Kitten Along the Way) Learn how to build and deploy an Executor that uses Stable Diffusion to generate images.

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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?

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ODSC - Open Data Science

MARCH 13, 2023

They are experts in machine learning, NLP, deep learning, data engineering, MLOps, and data visualization. Learn more about a few of our ODSC East 2023 instructors, their backgrounds in education, and why they’re fit for imparting their knowledge. He also teaches AI and ML courses at Cornell, NY and Queens University, CA.

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Applied Data Science

OCTOBER 25, 2021

Solid theoretical background in statistics and machine learning, experience with state-of-the-art deep learning algorithms, expert command of tools for data pre-processing, database management and visualisation, creativity and story-telling abilities, communication and team-building skills, familiarity with the industry.

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Towards AI

JULY 11, 2024

It offers exclusive live training, interactive learning experiences, certification programs, books, videos, and more. If you are a subscriber of the platform, you can read it directly on the O’Reilly learning platform or sign up for a 10-day free trial to access the book. Share your feedback in the Discord thread!

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Heartbeat

MARCH 14, 2023

Some of the methods used for scene interpretation include Convolutional Neural Networks (CNNs) , a deep learning-based methodology, and more conventional computer vision-based techniques like SIFT and SURF. A combination of simulated and real-world data was used to train the system, enabling it to generalize to new objects and tasks.

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Towards AI

APRIL 7, 2024

Additionally, the elimination of human loop processes has made it possible for AI/ML to construct training data for data annotation and labeling, which has a major influence on geospatial data. This function can be improved by AI and ML, which allow GIS to produce insights, automate procedures, and learn from data.

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Mlearning.ai

FEBRUARY 26, 2023

Dive Into Deep Learning — Part 2 This is part 2 of my summary of the chapters I read from the dive into deep learning book. Dive Into Deep Learning — Part1 The following sections of the analytic solution talk about optimizing the model and how to calculate the gradients. BECOME a WRITER at MLearning.ai

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AWS Machine Learning Blog

JANUARY 31, 2024

Embeddings play a key role in natural language processing (NLP) and machine learning (ML). These models are based on deep learning architectures such as Transformers, which can capture the contextual information and relationships between words in a sentence more effectively. Why do we need an embeddings model?

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AWS Machine Learning Blog

APRIL 29, 2024

For AWS and Outerbounds customers, the goal is to build a differentiated machine learning and artificial intelligence (ML/AI) system and reliably improve it over time. Second, open source Metaflow provides the necessary software infrastructure to build production-grade ML/AI systems in a developer-friendly manner.

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AWS Machine Learning Blog

MAY 7, 2024

Hugging Face is an open-source machine learning (ML) platform that provides tools and resources for the development of AI projects. In his current role, he has helped customers achieve their business goals on a variety of ML use cases, ranging from setting up MLOps inference pipelines to developing a fraud detection application.

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ODSC - Open Data Science

SEPTEMBER 13, 2024

Each day we had at least one book signing where attendees could meet some of their favorite data science book authors and get their questions answered — and those who showed up early enough, even got their book signed. What’s next? We still have one more big event this year — ODSC West 2024!

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AWS Machine Learning Blog

JUNE 15, 2023

Dive into Deep Learning ( D2L.ai ) is an open-source textbook that makes deep learning accessible to everyone. It is a challenging endeavor to have an online book that is continuously kept up to date, written by multiple authors, and available in multiple languages. In this post, we present a solution that D2L.ai

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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Mlearning.ai

FEBRUARY 16, 2023

How to effectively safeguard your ML experiments Photo by Clément Hélardot on Unsplash Many years ago… I was staring at my screen, scrutinizing every little wiggle on my Tensorboard. Planning machine learning experiments within a fixed timeframe is a logistical nightmare. Your ML experiment will perish in 7 days.

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PyImageSearch

FEBRUARY 20, 2023

Jump Right To The Downloads Section Learning JAX in 2023: Part 1 — The Ultimate Guide to Accelerating Numerical Computation and Machine Learning ?? Introduction As deep learning practitioners, it can be tough to keep up with all the new developments. Automatic Differentiation is at the very heart of Deep Learning.

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Towards AI

DECEMBER 19, 2023

Source: interpretable-ml-book The field of deep learning has grown exponentially and the recent craze about ChatGPT is proof of the same. For example, a deep neural net used for a loan application scorecard might deny a customer, and we will not be able to explain why.

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AWS Machine Learning Blog

SEPTEMBER 12, 2023

The machine learning (ML) model classifies new incoming customer requests as soon as they arrive and redirects them to predefined queues, which allows our dedicated client success agents to focus on the contents of the emails according to their skills and provide appropriate responses. Use Version 2.x

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AWS Machine Learning Blog

JANUARY 9, 2024

To implement the solution, we use SageMaker, a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. G5 instances are a high-performance GPU-based instances for graphics-intensive applications and ML inference.

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Flipboard

APRIL 17, 2023

Throughout the series, we have covered the theoretical concepts of JAX, and in this post, we will apply those concepts to train a machine learning model. By the end of this tutorial, you will have a solid understanding of how to train a machine learning model using JAX and will be able to apply this knowledge to other ML problems.

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