AWS Machine Learning Blog

NOVEMBER 7, 2024

The markdown pricing algorithmic solution Zalando relies on is a forecast-then-optimize approach (Kunz et al. Operating such large-scale forecasting requires resilient, reusable, reproducible, and automated machine learning (ML) workflows with fast experimentation and continuous improvements. 2023 and Streeck et al.

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Flipboard

NOVEMBER 6, 2024

The model is trained on abdominal scans from Far Eastern Memorial Hospital (January 2012–December 2021) and evaluated using a simulated test set (14,039 scans) and a prospective test set (6351 scans) collected from the same center between December 2022 and May 2023. Overall, the model achieves a sensitivity of 0.81–0.83

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Dataconomy

AUGUST 22, 2024

Aleksandr Timashov is an ML Engineer with over a decade of experience in AI and Machine Learning. I led several projects that dramatically advanced the company’s technological capabilities: Real-time Video Analytics for Security: We developed an advanced system integrating deep learning algorithms with existing CCTV infrastructure.

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ML ML Machine Learning Machine Learning 91

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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Google Research AI blog

FEBRUARY 21, 2023

With the amazing advances in machine learning (ML) and quantum computing, we now have powerful new tools that enable us to act on our curiosity, collaborate in new ways, and radically accelerate progress toward breakthrough scientific discoveries. You can find other posts in the series here.)

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Pickl AI

JANUARY 29, 2024

Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. Key takeaways Data Science lays the groundwork for Machine Learning, providing curated datasets for ML algorithms to learn and make predictions. Data Science enhances ML accuracy through preprocessing and feature engineering expertise.

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Mlearning.ai

AUGUST 11, 2023

ML Implementation — 00 I do not know how I will be proceeding with this project(s) but I plan to document it to some extent. I gained a couple of badges and a lot of skills while doing these, but still, the goal was to have a proper implementation of the Machine Learning Algorithm. Part 01 of ML Implementation. Until net time.

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ML ML Machine Learning Machine Learning 52

Towards AI

APRIL 4, 2023

Last Updated on April 4, 2023 by Editorial Team Introducing a Python SDK that allows enterprises to effortlessly optimize their ML models for edge devices. With their groundbreaking web-based Studio platform, engineers have been able to collect data, develop and tune ML models, and deploy them to devices. on Tuesday, April 4, 2022

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ML ML Python Machine Learning 94

Google Research AI blog

FEBRUARY 14, 2023

In this blog post, we’ll review key learnings and themes from our explorations in 2022. We’re also progressing towards making our learning algorithms more data efficient so that we’re not relying only on scaling data collection.

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Algorithm System Architecture Deep Learning Deep Learning 139

AWS Machine Learning Blog

MAY 8, 2024

In 2022, Dialog Axiata made significant progress in their digital transformation efforts, with AWS playing a key role in this journey. This strategic use of AWS services delivers efficiency and scalability of their operations, as well as the implementation of advanced AI/ML applications.

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Google Research AI blog

FEBRUARY 28, 2023

Adherence to such public health programs is a prevalent challenge, so researchers from Google Research and the Indian Institute of Technology, Madras worked with ARMMAN to design an ML system that alerts healthcare providers about participants at risk of dropping out of the health information program. certainty when used correctly.

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ML ML Deep Learning Deep Learning 72

PyImageSearch

DECEMBER 11, 2023

Kicking Off with a Keynote The second day of the Google Machine Learning Community Summit began with an inspiring keynote session by Soonson Kwon, the ML Community Lead at Google. The focus of his presentation was clear and forward-thinking: Accelerate AI/ML research and application.

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IBM Journey to AI blog

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

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Dataconomy

SEPTEMBER 13, 2023

According to Gartner, a renowned research firm, by 2022, an astounding 70% of customer interactions are expected to flow through technologies like machine learning applications, chatbots, and mobile messaging. These tasks are indispensable, as algorithms heavily rely on pattern recognition to make informed decisions.

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Data Science Dojo

JANUARY 18, 2023

Despite major layoffs in 2022, there are many optimistic fintech trends to look out for in 2023. Fintech trends for 2023 not only reveal the path forward for companies big and small but rather, they also show us how changing circumstances in 2022 call for innovative solutions. Every crisis bespells new opportunities.

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Google Research AI blog

JANUARY 18, 2023

Please keep your eye on this space and look for the title “Google Research, 2022 & Beyond” for more articles in the series. With this post, I am kicking off a series in which researchers across Google will highlight some exciting progress we've made in 2022 and present our vision for 2023 and beyond.

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Towards AI

AUGUST 25, 2023

As a reminder, I highly recommend that you refer to more than one resource (other than documentation) when learning ML, preferably a textbook geared toward your learning level (beginner/intermediate / advanced). In ML, there are a variety of algorithms that can help solve problems.

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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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Supervised Learning Machine Learning Machine Learning AWS 82

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.

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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.

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AWS Machine Learning Blog

JUNE 22, 2023

Light & Wonder teamed up with the Amazon ML Solutions Lab to use events data streamed from LnW Connect to enable machine learning (ML)-powered predictive maintenance for slot machines. Predictive maintenance is a common ML use case for businesses with physical equipment or machinery assets.

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AWS Machine Learning Blog

DECEMBER 7, 2023

Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Calculating courier requirements The first step is to estimate hourly demand for each warehouse, as explained in the Algorithm selection section.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Machine learning (ML) helps organizations to increase revenue, drive business growth, and reduce costs by optimizing core business functions such as supply and demand forecasting, customer churn prediction, credit risk scoring, pricing, predicting late shipments, and many others. Let’s learn about the services we will use to make this happen.

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Data Warehouse Machine Learning Machine Learning Cloud Data 106

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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Machine Learning Machine Learning ML ML 98

Dataconomy

FEBRUARY 26, 2024

GPUs: The versatile powerhouses Graphics Processing Units, or GPUs, have transcended their initial design purpose of rendering video game graphics to become key elements of Artificial Intelligence (AI) and Machine Learning (ML) efforts.

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Towards AI

JULY 22, 2024

TheSequence is a no-BS (meaning no hype, no news, etc) ML-oriented newsletter that takes 5 minutes to read. Decoding Algorithm: They developed a novel decoding algorithm for tool-integrated reasoning (TIR) that incorporated code execution feedback, enabling the generation of solution candidates during inference.

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The MLOps Blog

DECEMBER 7, 2022

2022 will be remembered as a defining year for the crypto ecosystem. Given that the whole theory of machine learning assumes today will behave at least somewhat like yesterday, what can algorithms and models do for you in such a chaotic context ? There’s an old saying in Argentina that goes: “A río revuelto, ganancia de pescadores”.

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Google Research AI blog

APRIL 18, 2023

Posted by Badih Ghazi, Staff Research Scientist, and Nachiappan Valliappan, Staff Software Engineer, Google Research Recently, differential privacy (DP) has emerged as a mathematically robust notion of user privacy for data aggregation and machine learning (ML), with practical deployments including the 2022 US Census and in industry.

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Algorithm ML ML Machine Learning 98

Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

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IBM Journey to AI blog

OCTOBER 24, 2024

A future cryptographically relevant quantum computer (CRQC) might break globally used asymmetric cryptography algorithms that currently help ensure the confidentiality and integrity of data and the authenticity of systems access. The good news is that these algorithms are at our disposal to protect against the quantum risk.

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Algorithm ML ML Data Analysis 75

Towards AI

SEPTEMBER 10, 2023

I’ve passed many ML courses before, so that I can compare. The course covers the basics of Deep Learning and Neural Networks and also explains Decision Tree algorithms. The current version is from 2022, so I suppose the content has changed since previous reviews on TDS. You start with the working ML model.

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Deep Learning Deep Learning ML ML 106

AWS Machine Learning Blog

JANUARY 13, 2023

Machine learning (ML) presents an opportunity to address some of these concerns and is being adopted to advance data analytics and derive meaningful insights from diverse HCLS data for use cases like care delivery, clinical decision support, precision medicine, triage and diagnosis, and chronic care management.

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Applied Data Science

AUGUST 2, 2021

Big Ideas What to look out for in 2022 1. Machine Learning In this section, we look beyond ‘standard’ ML practices and explore the 6 ML trends that will set you apart from the pack in 2021. This allows for a much richer interpretation of predictions, without sacrificing the algorithm’s power.

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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. I train a decision tree model using GROW_DECTREE SP.

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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?

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Snorkel AI

APRIL 28, 2023

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. Often, it requires you to co-design the algorithm and also the system set.

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ML ML Machine Learning Machine Learning 52

Snorkel AI

APRIL 28, 2023

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. Often, it requires you to co-design the algorithm and also the system set.

ML 52

ML ML Machine Learning Machine Learning 52