AWS Machine Learning Blog

MARCH 29, 2023

there is enormous potential to use machine learning (ML) for quality prediction. ML-based predictive quality in HAYAT HOLDING HAYAT is the world’s fourth-largest branded baby diapers manufacturer and the largest paper tissue manufacturer of the EMEA. After the data preparation phase, a two-stage approach is used to build the ML models.

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The MLOps Blog

MARCH 14, 2023

When working on real-world ML projects , you come face-to-face with a series of obstacles. The ml model reproducibility problem is one of them. This is indeed an erroneous thing to do when working on ML projects at scale. To back this up, here is the Nature survey conducted in 2016.

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Dataconomy

APRIL 18, 2023

Additionally, it is crucial to comprehend the fundamental concepts that underlie AI, including neural networks, algorithms, and data structures. AI systems use a combination of algorithms, machine learning techniques, and data analytics to simulate human intelligence. What is artificial intelligence?

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AWS Machine Learning Blog

FEBRUARY 28, 2023

In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. For example, in the healthcare industry, ML-driven analytics can be used for diagnostic assistance and personalized medicine, while in health insurance, it can be used for predictive care management.

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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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AWS Machine Learning Blog

JULY 15, 2024

In our pipeline, we used Amazon Bedrock to develop a sentence shortening algorithm for automatic time scaling. Here’s the shortened sentence using the sentence shortening algorithm. She specializes in leveraging AI and ML to drive innovation and develop solutions on AWS. Partner Solutions Architect at AWS, specializing in AI/ML.

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How to Learn Machine Learning

OCTOBER 10, 2024

The quality of your training data in Machine Learning (ML) can make or break your entire project. Machine learning algorithms rely heavily on the data they are trained on. Unfortunately, the algorithm was trained on resumes predominantly submitted by men over 10 years. Why Does Data Quality Matter? Sounds great, right?

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AWS Machine Learning Blog

JANUARY 17, 2024

SageMaker Studio is an integrated development environment (IDE) that provides a single web-based visual interface where you can access purpose-built tools to perform all machine learning (ML) development steps, from preparing data to building, training, and deploying your ML models. He retired from EPFL in December 2016.nnIn

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O'Reilly Media

APRIL 5, 2023

That’s because AI algorithms are trained on data. And it’s safe to say that most AI algorithms are trained on datasets that are significantly older. In 2016, Microsoft’s Tay chatbot was shut down after making racist and sexist comments. By its very nature, data is an artifact of something that happened in the past.

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ODSC - Open Data Science

OCTOBER 4, 2024

His research includes developing algorithms for end-to-end training of deep neural network policies that combine perception and control, scalable algorithms for inverse reinforcement learning, and deep reinforcement learning algorithms. His career has spanned both technology and government.

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AWS Machine Learning Blog

JULY 13, 2023

Another way can be to use an AllReduce algorithm. For example, in the ring-allreduce algorithm, each node communicates with only two of its neighboring nodes, thereby reducing the overall data transfers. Train a binary classification model using the SageMaker built-in XGBoost algorithm. arXiv preprint arXiv:1609.04836 (2016). [3]

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AWS Machine Learning Blog

APRIL 18, 2023

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

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Dataconomy

JUNE 6, 2024

NEAR Protocol incorporates AI and ML into platform systems, where smart contract deployment, network optimization, and security monitoring are performed automatically. It applies high-standard sharding technology to achieve massive trouble-free transaction throughput and low fees, which also tackles the general problems in other blockchains.

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Smart Data Collective

DECEMBER 19, 2019

In 2016, A Facebook bot tricked more than 10,000 Facebook users. Once the hackers can spot any vulnerability in the machine learning workflow, leveraging the power of AI, they can bemuse the ML models. AI algorithm learns from data pool – we already know that. Lack of understanding the algorithm limitations.

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ODSC - Open Data Science

AUGUST 16, 2024

In 2016, he was named the “most influential computer scientist” worldwide in Science magazine. Michael, currently a Distinguished Professor at the University of California, Berkeley, has made significant contributions to the field of AI throughout his extensive career.

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DagsHub

JULY 25, 2024

This guarantees businesses can fully utilize deep learning in their AI and ML initiatives. You can make more informed judgments about your AI and ML initiatives if you know these platforms' features, applications, and use cases. In finance, it's applied for fraud detection and algorithmic trading.

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Dataconomy

AUGUST 2, 2024

NEAR Protocol incorporates AI and ML into platform systems, where smart contract deployment, network optimization, and security monitoring are performed automatically. It applies high-standard sharding technology to achieve massive trouble-free transaction throughput and low fees, which also tackles the general problems in other blockchains.

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AWS Machine Learning Blog

MARCH 28, 2024

News CommonCrawl is a dataset released by CommonCrawl in 2016. News CommonCrawl SEC Filing Coverage 2016-2022 1993-2022 Size 25.8 billion words The authors go through a few extra preprocessing steps before the data is fed into a training algorithm. Publicly listed companies are required to file various documents regularly.

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DagsHub

APRIL 7, 2024

Image generated with Midjourney In today’s fast-paced world of data science, building impactful machine learning models relies on much more than selecting the best algorithm for the job. These pipelines cover the entire lifecycle of an ML project, from data ingestion and preprocessing, to model training, evaluation, and deployment.

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Mlearning.ai

APRIL 10, 2023

3 feature visual representation of a K-means Algorithm. Essentially, the clustering algorithm is grouping data points together without any prior knowledge or guidance to discover hidden patterns or unusual data groupings without the need for human interference.

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Mlearning.ai

MARCH 15, 2023

The ML model is then used by the user through an API by sending a request to access a specific feature. Federated Learning On the other hand, the FL architecture is different because machine learning is done across multiple edge devices (clients) that collaborate in the training of the ML model.

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ML Review

JUNE 4, 2018

Finally, one can use a sentence similarity evaluation metric to evaluate the algorithm. One such evaluation metric is the Bilingual Evaluation Understudy algorithm, or BLEU score. Source : Britz (2016)[ 62 ] CNNs can encode abstract features from images. 2016)[ 91 ] You et al.

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DrivenData Labs

MARCH 30, 2023

Modeling ¶ Most teams experimented with a variety of modeling algorithms, and many noted that the privacy techniques in their solutions could be paired with more than one family of machine learning models. We are excited to take on this challenge and continue pushing the boundaries of machine learning research.

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Heartbeat

AUGUST 23, 2023

Consider a scenario where legal practitioners are armed with clever algorithms capable of analyzing, comprehending, and extracting key insights from massive collections of legal papers. Algorithms can automatically detect and extract key items. But what if there was a technique to quickly and accurately solve this language puzzle?

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Ocean Protocol

MAY 24, 2024

The challenge required a detailed analysis of Google Trends data, integration of additional data sources, and the application of advanced ML methods to predict market behaviors. Participants demonstrated outstanding abilities in utilizing ML and data analysis to probe and predict movements within the cryptocurrency market.

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Google Research AI blog

JANUARY 18, 2023

Over the next several weeks, we will discuss novel developments in research topics ranging from responsible AI to algorithms and computer systems to science, health and robotics. A key research question is whether ML models can learn to solve complex problems using multi-step reasoning. Let’s get started!

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ML Review

MAY 3, 2018

2016) — “ LipNet: End-to-End Sentence-level Lipreading.” [17] 17] “ LipNet ” introduces the first approach for an end-to-end lip reading algorithm at sentence level. 27] LipNet also makes use of an additional algorithm typically used in speech recognition systems — a Connectionist Temporal Classification (CTC) output.

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Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., Understanding the robustness of image segmentation algorithms to adversarial attacks is critical for ensuring their reliability and security in practical applications.

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Heartbeat

FEBRUARY 2, 2024

The significance of VQA extends beyond traditional computer vision tasks, requiring algorithms to exhibit a broader understanding of context, semantics, and reasoning. It's remarkable diversity and scale position it as a cornerstone for evaluating and benchmarking VQA algorithms.

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IBM Journey to AI blog

SEPTEMBER 11, 2023

It leverages machine learning algorithms to continuously learn and adapt to workload patterns, delivering superior performance and reducing administrative efforts. How Db2, AI and hybrid cloud work together AI- i nfused intelligence in IBM Db2 v11.5

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How to Learn Machine Learning

DECEMBER 4, 2022

Numerous techniques, such as but not limited to rule-based systems, decision trees, genetic algorithms, artificial neural networks, and fuzzy logic systems, can be used to do this. In 2016, Google released an open-source software called AutoML. Finally, machine learning (ML) is also being used to write code.

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Mlearning.ai

FEBRUARY 15, 2023

Figure 4 Data Cleaning Conventional algorithms are often biased towards the dominant class, ignoring the data distribution. Figure 11 Model Architecture The algorithms and models used for the first three classifiers are essentially the same. K-Nearest Neighbou r: The k-Nearest Neighbor algorithm has a simple concept behind it.

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AWS Machine Learning Blog

APRIL 18, 2023

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

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Heartbeat

SEPTEMBER 13, 2023

Algorithmic Accountability: Explainability ensures accountability in machine learning and AI systems. It provides insights into model refinement, feature engineering, or algorithmic modifications. Alibi Alibi is an open-source Python library for algorithmic transparency and interpretability. Russell, C. & & Watcher, S.

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Heartbeat

MAY 11, 2023

The first version of YOLO was introduced in 2016 and changed how object detection was performed by treating object detection as a single regression problem. ✨ The algorithm for selecting layers in the model quantizes certain parts to minimize loss of information while ensuring a balance between latency and accuracy. Introducing ?️YOLO-NAS:

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Snorkel AI

MARCH 1, 2023

This model debuted in June 2020, but remained a tool for researchers and ML practitioners until its creator, OpenAI, debuted a consumer-friendly chat interface in November 2022. It is based on GPT and uses machine learning algorithms to generate code suggestions as developers write. Attention Is All You Need Vaswani et al.

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Snorkel AI

FEBRUARY 17, 2023

I share this because it shows where things were in 2016; it was exciting to find one label error. At the time, back in 2016, the MNIST dataset had been cited 30,000 times. How do you train machine learning algorithms generally for any data set? At this time, that was a big deal. And so I was like, hang on a minute.

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