Mlearning.ai

APRIL 8, 2023

SOTA (state-of-the-art) in machine learning refers to the best performance achieved by a model or system on a given benchmark dataset or task at a specific point in time. The earlier models that were SOTA for NLP mainly fell under the traditional machine learning algorithms. Citation: Article from IBM archives 2.

Natural Language Processing 98

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AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. Journal of machine learning research 9, no.

ML 84

ML ML Machine Learning Machine Learning 84

Flipboard

JULY 10, 2023

By using our mathematical notation, the entire training process of the autoencoder can be written as follows: Figure 2 demonstrates the basic architecture of an autoencoder: Figure 2: Architecture of Autoencoder (inspired by Hubens, “Deep Inside: Autoencoders,” Towards Data Science , 2018 ). How Are Autoencoders Different from GANs?

Deep Learning 132

Deep Learning Deep Learning Machine Learning Machine Learning 132

Tableau

DECEMBER 1, 2021

Even modern machine learning applications should use visual encoding to explain data to people. Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. April 2018), which focused on users who do understand joins and curating federated data sources. Connectivity.

Tableau 145

Tableau ML ML Database 145

DrivenData Labs

FEBRUARY 3, 2025

Recently, I became interested in machine learning, so I was enrolled in the Yandex School of Data Analysis and Computer Science Center. Machine learning is my passion and I often participate in competitions. Before I received my master's degree in mathematics from Novosibirsk State University in Russia.

Machine Learning 130

Machine Learning Machine Learning Data Science Natural Language Processing 130

AWS Machine Learning Blog

JANUARY 13, 2023

To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. It involves training a global machine learning (ML) model from distributed health data held locally at different sites. 2018): 1-13. [2] Scientific data 5.1

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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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AWS Python Machine Learning Machine Learning 129

AWS Machine Learning Blog

MAY 2, 2023

JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. There are a few limitations of using off-the-shelf pre-trained LLMs: They’re usually trained offline, making the model agnostic to the latest information (for example, a chatbot trained from 2011–2018 has no information about COVID-19).

Algorithm 95

Algorithm Machine Learning Machine Learning Natural Language Processing 95

Flipboard

APRIL 13, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses.

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Flipboard

NOVEMBER 24, 2023

Iris was designed to use machine learning (ML) algorithms to predict the next steps in building a data pipeline. Since joining SnapLogic in 2010, Greg has helped design and implement several key platform features including cluster processing, big data processing, the cloud architecture, and machine learning.

Database 159

Database AWS ETL SQL 159

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., 2018; Sitawarin et al., 2018; Papernot et al., an image) with the intention of causing a machine learning model to misclassify it (Goodfellow et al.,

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Dataconomy

APRIL 26, 2023

The strategic value of IoT development and data analytics Sierra Wireless Sierra Wireless , a wireless communications equipment designer and service provider, has been honing its focus on IoT software and managed services following its acquisition of M2M Group, a cluster of companies dedicated to IoT connectivity, in 2020.

Internet of Things 156

Internet of Things Azure AWS Cloud Computing 156

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. Then we needed to Dockerize the application, write a deployment YAML file, deploy the gRPC server to our Kubernetes cluster, and make sure it’s reliable and auto scalable. We recently developed four more new models.

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ML ML Deep Learning Deep Learning 93

AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). Learning means identifying and capturing historical patterns from the data, and inference means mapping a current value to the historical pattern.

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AWS ML ML Clustering 103

Pickl AI

MAY 16, 2023

For example, if you are a Data Scientist, then you should add keywords like Python, SQL, Machine Learning, Big Data and others. Skilled in programming languages such as Python, R, and SQL, and have worked on various projects involving predictive modeling, clustering, and classification.

Data Scientist 52

Data Scientist Data Science SQL Python 52

Tableau

DECEMBER 1, 2021

Even modern machine learning applications should use visual encoding to explain data to people. Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. April 2018), which focused on users who do understand joins and curating federated data sources. Connectivity.

Tableau 98

Tableau ML ML Database 98

Pickl AI

DECEMBER 2, 2024

According to a report by Statista, the global data sphere is expected to reach 180 zettabytes by 2025 , a significant increase from 33 zettabytes in 2018. Processing frameworks like Hadoop enable efficient data analysis across clusters. Introduction In today’s digital age, the volume of data generated is staggering.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

According to a report by Statista, the global data sphere is expected to reach 180 zettabytes by 2025 , a significant increase from 33 zettabytes in 2018. Processing frameworks like Hadoop enable efficient data analysis across clusters. Introduction In today’s digital age, the volume of data generated is staggering.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Mlearning.ai

JANUARY 17, 2024

Traditional AI can recognize, classify, and cluster, but not generate the data it is trained on. The foundations for today’s generative language applications were elaborated in the 1990s ( Hochreiter , Schmidhuber ), and the whole field took off around 2018 ( Radford , Devlin , et al.). Let’s play the comparison game.

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AI AI Deep Learning Deep Learning 98

Explosion

MAY 17, 2023

For instance, you could extract a few noisy metrics, such as a general “positivity” sentiment score that you track in a dashboard, while you also produce more nuanced clustering of the posts which are reviewed periodically in more detail. You might want to view the data in a variety of ways. This is where I have high hopes for LLMs.

Supervised Learning 135

Supervised Learning Natural Language Processing Clustering Machine Learning 135

Hacker News

JANUARY 9, 2024

The LLMs Have Landed The machine learning superfunctions Classify and Predict first appeared in Wolfram Language in 2014 ( Version 10 ). but with things like clustering). We’ve had ExternalEvaluate for evaluating Python code since 2018. Spreading the power of the Wolfram Language to more and more people and areas.

Python 181

Python Algorithm Machine Learning Machine Learning 181

Heartbeat

AUGUST 23, 2023

These algorithms help legal professionals swiftly discover essential information, speed up document review, and assure comprehensive case analysis through approaches such as document clustering and topic modeling. Natural language processing and machine learning as practical toolsets for archival processing.

Natural Language Processing 52

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The MLOps Blog

JANUARY 30, 2025

This rules out traditional machine-learning hyperparameter optimization (HPO) methods that rely on systematically exploring the hyperparameter space by training many models with slightly different configurations. Can we use traditional machine learning hyperparameter optimization methods for LLMs?

Machine Learning 64

Machine Learning Machine Learning Deep Learning Deep Learning 64

PyImageSearch

JULY 3, 2023

Figure 3: Netflix personalized home page view (source: “NETFLIX System Design,” Medium , 2018 ). Machine Learning for Page Generation A good utility function that checks the relevance of a row is the core of building a personalized home page. Figure 9: Regret in batch-based machine learning.

Deep Learning 52

Deep Learning Deep Learning Algorithm Machine Learning 52

Snorkel AI

MARCH 21, 2023

In 2018, we did a piece of research where we tried to estimate the value of AI and machine learning across geographies, across use cases, and across sectors. One is compared to our first survey conducted in 2018, we see more enterprises investing in AI capability. Firstly, what is the state of the industry?

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ML ML AI AI 52

Google Research AI blog

FEBRUARY 28, 2023

For example, supporting equitable student persistence in computing research through our Computer Science Research Mentorship Program , where Googlers have mentored over one thousand students since 2018 — 86% of whom identify as part of a historically marginalized group.

ML 72

ML ML Deep Learning Deep Learning 72

Mlearning.ai

FEBRUARY 28, 2023

In 2018–2019, while new car sales were recorded at 3.6 The next step post that would be to cluster different sets of data and see if multiple models should be created for different locations and car types. For this reason, Cars4U was created as a budding tech start-up that aims to find footholds in this market.

Python 52

Python EDA Exploratory Data Analysis Data Analysis 52

ML Review

MARCH 5, 2019

For instance, consider the sentence “ I like machine learning ” and a context window of size 1. Then, the words which give context, or appear in the context window around the word “ machine” , are “ like ” and “ learning ” (the window is considered both on the left and on the right). Bojanowski, P., TACL, 5, 135–146.

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