AWS Machine Learning Blog

SEPTEMBER 19, 2023

Amazon SageMaker Feature Store provides an end-to-end solution to automate feature engineering for machine learning (ML). For many ML use cases, raw data like log files, sensor readings, or transaction records need to be transformed into meaningful features that are optimized for model training. SageMaker Studio set up.

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Data Science 101

SEPTEMBER 24, 2019

Is the list missing a project released in 2019? If so, please leave a comment.

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Towards AI

NOVEMBER 16, 2024

Song and Ermon (2019) [13] proposed score-based generative modelling methods where samples are produced via Langevin dynamics using gradients of the data distribution estimated with Stein score-matching. As T → ∞, ϵ → 0, and x_T converges to the true probability density p(x).

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Machine Learning (Theory)

JULY 19, 2021

In 2019, she received a Nobel Prize in Economic Sciences “for their experimental approach to alleviating global poverty”. She researches strategies to study complex biophysical processes on long timescales, and she is an expert in the simulation of biomolecules using large-scale ML.

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KDnuggets

DECEMBER 16, 2019

It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different. Gain an understanding of the important developments of the past year, as well as insights into what expect in 2020.

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AWS Machine Learning Blog

SEPTEMBER 17, 2024

AWS DeepComposer was first introduced during AWS re:Invent 2019 as a fun way for developers to compose music by using generative AI. AWS DeepComposer was the world’s first machine learning (ML)-enabled keyboard for developers to get hands-on—literally—with a musical keyboard and the latest ML techniques to compose their own music.

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Data Science 101

APRIL 29, 2019

Here is the latest data science news for the week of April 29, 2019. From Data Science 101. The Go Programming Language for Data Science Quick Video Tutorial for Find Updates in Azure Two-Minute Papers, One Pixel attack on NN. General Data Science.

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The MLOps Blog

MARCH 20, 2023

Long-term ML project involves developing and sustaining applications or systems that leverage machine learning models, algorithms, and techniques. An example of a long-term ML project will be a bank fraud detection system powered by ML models and algorithms for pattern recognition. 2 Ensuring and maintaining high-quality data.

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Data Science 101

MARCH 16, 2019

Recently updated, is the March 2019 Machine Learning Study Path. It contains links and resources to learn Tensorflow and Scikit-Learn. If you are interested in details on the study path and how to best use the resources. There is a livestream on Facebook, Sunday March 17 on the Math for Data Science Facebook page.

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KDnuggets

DECEMBER 11, 2019

We asked top experts: What were the main developments in AI, Data Science, Deep Learning, and Machine Learning Research in 2019, and what key trends do you expect in 2020? Read their answers, and also check 10 Free Top Notch Machine Learning Courses; 4 Hottest Trends in Data Science; The Essential Toolbox for Data Cleaning, and more.

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AWS Machine Learning Blog

APRIL 9, 2024

The correct response for this query is “Amazon’s annual revenue increased from $245B in 2019 to $434B in 2022,” based on the documents in the knowledge base. The generated response is “Amazon’s annual revenue increase from $245B in 2019 to $434B in 2022.” We ask “What was the Amazon’s revenue in 2019 and 2021?”

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KDnuggets

NOVEMBER 20, 2019

Read tips and tricks that helped one Data Scientist to get better at Machine Learning; Learn how to make ML project cost-effective; Consider submitting a blog to KDnuggets - you can be profiled here; and study how to manipulate Python lists.

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KDnuggets

JULY 30, 2019

This technical webinar on Aug 14 discusses traditional and modern approaches for interpreting black box models. Additionally, we will review cutting edge research coming out of UCSF, CMU, and industry.

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KDnuggets

SEPTEMBER 9, 2019

I am really interested in creating a tight, clean pipeline for disaster relief applications, where we can use something like crowd sourced building polygons from OSM to train a supervised object detector to discover buildings in an unmapped location.

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KDnuggets

AUGUST 30, 2019

Implement some of the core OOP principles in a machine learning context by building your own Scikit-learn-like estimator, and making it better.

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AWS Machine Learning Blog

DECEMBER 1, 2023

Launched in 2019, Amazon SageMaker Studio provides one place for all end-to-end machine learning (ML) workflows, from data preparation, building and experimentation, training, hosting, and monitoring. About the Authors Mair Hasco is an AI/ML Specialist for Amazon SageMaker Studio. Get started on SageMaker Studio here.

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ML Review

DECEMBER 16, 2019

Let’s check out the goodies brought by NeurIPS 2019 and co-located events! In this (by no means exhaustive) post we will discuss general trends in ML on graphs as well as touch upon Knowledge Graphs (KGs) as it is what we are doing at Fraunhofer IAIS (end of shameless self-promotion ?). Graphs were well represented at the conference.

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AWS Machine Learning Blog

APRIL 19, 2023

Since 2018, our team has been developing a variety of ML models to enable betting products for NFL and NCAA football. These models are then pushed to an Amazon Simple Storage Service (Amazon S3) bucket using DVC, a version control tool for ML models. The DJL was created at Amazon and open-sourced in 2019.

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Dataconomy

JULY 4, 2023

Hyper automation, which uses cutting-edge technologies like AI and ML, can help you automate even the most complex tasks. It’s also about using AI and ML to gain insights into your data and make better decisions. ML algorithms enable systems to identify patterns, make predictions, and take autonomous actions.

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The MLOps Blog

AUGUST 3, 2023

This article was originally an episode of the ML Platform Podcast , a show where Piotr Niedźwiedź and Aurimas Griciūnas, together with ML platform professionals, discuss design choices, best practices, example tool stacks, and real-world learnings from some of the best ML platform professionals. Stefan: Back in 2019.

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DataRobot Blog

OCTOBER 11, 2022

Want to learn how AI/ML can be so effective in this space? So how can AI/ML help McLaren Formula 1 Team, one of the sports oldest and most successful teams, in this space? Lastly, for modeling purposes, I leveraged about 1140 races across 2019-2021. For now, I’ve built my model for 2019-2021 races. Let’s begin!

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ML @ CMU

NOVEMBER 7, 2024

We address the challenges of landmine risk estimation by enhancing existing datasets with rich relevant features, constructing a novel, robust, and interpretable ML model that outperforms standard and new baselines, and identifying cohesive hazard clusters under geographic and budgetary constraints.

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ODSC - Open Data Science

SEPTEMBER 21, 2023

Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business. Some typical examples are given in the following table, along with some discussion as to whether or not ML would be an appropriate tool for solving the problem: Figure 1.1:

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DataRobot Blog

MARCH 30, 2022

For those who haven’t read the prior blogs ( 2019 , 2020 , 2021 ), the idea behind this task is to leverage various sources of data for each track (betting odds, audio analysis , lyric sentiment) to rank which ones are most likely to win the aforementioned awards. Composable ML. See DataRobot Composable ML in Action.

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Smart Data Collective

MARCH 26, 2021

Machine learning (ML) is an innovative tool that advances technology in every industry around the world. This form of learning is everywhere, in places you may not even know, which is part of what makes ML so integral to a range of professions and everyday tasks. Using ML can potentially reduce this number and prevent injuries, too.

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AWS Machine Learning Blog

APRIL 6, 2023

& AWS Machine Learning Solutions Lab (MLSL) Machine learning (ML) is being used across a wide range of industries to extract actionable insights from data to streamline processes and improve revenue generation. We evaluated the WAPE for all BLs in the auto end market for 2019, 2020, and 2021.

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KDnuggets

AUGUST 16, 2019

Use of Machine Learning (ML) in Medicine is becoming more and more important. One application example can be Cancer Detection and Analysis.

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Data Science 101

NOVEMBER 11, 2019

SQL Server 2019 SQL Server 2019 went Generally Available. Data Science Announcements from Microsoft Ignite Many other services were announced such as: Azure Quantum, Project Silica, R support in Azure ML, and Visual Studio Online. Amazon Web Services.

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IBM Journey to AI blog

APRIL 13, 2023

Building ML infrastructure and integrating ML models with the larger business are major bottlenecks to AI adoption [1,2,3]. IBM Db2 can help solve these problems with its built-in ML infrastructure. Db2 Warehouse on cloud also supports these ML features. In the enterprise, SQL is a more common skill than ML.

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Google Research AI blog

FEBRUARY 23, 2023

Commensurate with our mission to demonstrate these societal benefits , Google Research’s programs in applied machine learning (ML) have helped place Alphabet among the top five most impactful corporate research institutions in the health and life sciences publications on the Nature Impact Index in every year from 2019 through 2022.

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Data Science 101

NOVEMBER 22, 2019

AWS Storage Day On November 20, 2019, Amazon held AWS Storage Day. Much of this is in anticipation of AWS re:Invent, coming in early December 2019. PyTorch on Azure with streamlined ML lifecycle Microsoft Azure supports the latest version of PyTorch. Many announcements came out regarding storage of all types at AWS.

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ML @ CMU

SEPTEMBER 13, 2024

2019 , 2023; Nasr et al., In 28th USENIX security symposium (USENIX security 19) , pages 267–284, 2019. Our approach provides a simple and practical perspective on what memorization can mean, providing a useful tool for functional and legal analysis of LLMs. Carlini et al., 2023; Zhang et al., arXiv preprint arXiv:2112.03570 , 2021.

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AWS Machine Learning Blog

DECEMBER 4, 2023

We capitalized on the powerful tools provided by AWS to tackle this challenge and effectively navigate the complex field of machine learning (ML) and predictive analytics. SageMaker is a fully managed ML service. This was a crucial aspect in achieving agility in our operations and a seamless integration of our ML efforts.

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Smart Data Collective

JANUARY 27, 2022

In an interview with Hyperight, the tech leader at Uber, Ritesh Agrawal, explained how ML helps improve the overall riding experience. Well, it uses NLP and ML to accurately anticipate responses to regular riders’ questions. AI-driven plagiarism detectors are useful for people vetting websites before buying them.

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KDnuggets

AUGUST 1, 2019

Learn how Interpretable and Explainable ML technologies can help while developing your model. A machine learning model that predicts some outcome provides value. One that explains why it made the prediction creates even more value for your stakeholders.

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AWS Machine Learning Blog

SEPTEMBER 10, 2024

As part of its goal to help people live longer, healthier lives, Genomics England is interested in facilitating more accurate identification of cancer subtypes and severity, using machine learning (ML). We provide insights on interpretability, robustness, and best practices of architecting complex ML workflows on AWS with Amazon SageMaker.

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AWS Machine Learning Blog

FEBRUARY 5, 2024

According to health organizations such as the Centers for Disease Control and Prevention ( CDC ) and the World Health Organization ( WHO ), a spillover event at a wet market in Wuhan, China most likely caused the coronavirus disease 2019 (COVID-19). fillna(0) df1['totalpixels'] = df1.sum(axis=1)

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