AWS Machine Learning Blog

DECEMBER 4, 2023

Established in 2015, Getir has positioned itself as the trailblazer in the sphere of ultrafast grocery delivery. 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.

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ODSC - Open Data Science

FEBRUARY 20, 2023

As newer fields emerge within data science and the research is still hard to grasp, sometimes it’s best to talk to the experts and pioneers of the field. Rumelhart Prize in 2015, and the ACM/AAAI Allen Newell Award in 2009. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Meesho was founded in 2015 and today focuses on buyers and sellers across India. We used AWS machine learning (ML) services like Amazon SageMaker to develop a powerful generalized feed ranker (GFR). SageMaker offered ease of deployment with support for various ML frameworks, allowing models to be served with low latency.

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AWS Machine Learning Blog

DECEMBER 7, 2023

Getir was founded in 2015 and operates in Turkey, the UK, the Netherlands, Germany, and the United States. Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Initially, daily forecasts for each country are formulated through ML models.

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ODSC - Open Data Science

MARCH 13, 2025

Just Do Something with AI: Bridging the Business Communication Gap forML This blog explores how ML practitioners can navigate AI business communication, ensuring AI initiatives align with real businessvalue. Looking back at almost 5000 conference sessions, how has the industrychanged? Learn more and apply to be a part of the eventhere.

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IBM Journey to AI blog

NOVEMBER 13, 2023

But Docker lacked an automated “orchestration” tool, which made it time-consuming and complex for data science teams to scale applications. Deploying machine learning on Kubernetes makes it easier for organizations to automate the management and scaling of ML lifecycles and reduces the need for manual intervention.

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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. It enables them to unlock the value of their data, identify trends, patterns, and predictions, and differentiate themselves from their competitors.

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AWS Machine Learning Blog

MAY 15, 2023

Getir was founded in 2015 and operates in Turkey, the UK, the Netherlands, Germany, France, Spain, Italy, Portugal, and the United States. Solution overview Six people from Getir’s data science team and infrastructure team worked together on this project. Getir is the pioneer of ultrafast grocery delivery.

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The MLOps Blog

NOVEMBER 30, 2022

These days enterprises are sitting on a pool of data and increasingly employing machine learning and deep learning algorithms to forecast sales, predict customer churn and fraud detection, etc., Data science practitioners experiment with algorithms, data, and hyperparameters to develop a model that generates business insights.

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Mlearning.ai

MAY 15, 2023

Photo by Andrew Neel on Unsplash Introduction If you are working or have worked on any data science task then you definitely used pandas. So, pandas is a library which helps with performing data ingestion and transformations. apply(lambda x: x.year) df.groupby('year')['Sales'].mean() Latest order date.

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phData

SEPTEMBER 20, 2023

On the client side, Snowpark consists of libraries, including the DataFrame API and native Snowpark machine learning (ML) APIs for model development (public preview) and deployment (private preview). phData has been working in data engineering since the inception of the company back in 2015. Why is Snowpark Exciting to us?

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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. Import the data loader into the training script.

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Iguazio

SEPTEMBER 20, 2023

The data file format comprises the Tweet’s polarity, IT, date, query, user and text. Twitter US Airline Sentiment Polarized Tweets from February 2015 about the large US airlines. Data is provided in a CSV file and SQLite database. Get the dataset here. Get the dataset here. Synonyms 12. Long-Form Content 14.

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Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Patil served as the first U.S.

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Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Patil served as the first U.S.

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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. He currently is working on Generative AI for data integration. Clay Elmore is an AI/ML Specialist Solutions Architect at AWS. He is the author of the upcoming book “What’s Your Problem?”

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Iguazio

MARCH 1, 2024

The manufacturing industry can benefit from AI, data and machine learning to advance manufacturing quality and productivity, minimize waste and reduce costs. With ML, manufacturers can modernize their businesses through use cases like forecasting demand, optimizing scheduling, preventing malfunctioning and managing quality.

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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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Snorkel AI

JANUARY 25, 2024

Insurance data is typically highly inaccessible: reports suggest that 80% of insurance data is unstructured, unlabelled, and not ready for AI model training. This means that an insurer’s ability to select, adopt and customise ML and Generative AI at scale will be a key competitive battleground.

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Snorkel AI

JANUARY 25, 2024

Insurance data is typically highly inaccessible: reports suggest that 80% of insurance data is unstructured, unlabelled, and not ready for AI model training. This means that an insurer’s ability to select, adopt and customise ML and Generative AI at scale will be a key competitive battleground.

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Heartbeat

JULY 24, 2023

Koltun, “Multi-scale context aggregation by dilated convolutions,” arXiv preprint arXiv:1511.07122, 2015. [4] 4] Data source: [link] Editor’s Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners.

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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. Developed by François Chollet, it was released in 2015 to simplify the creation of deep learning models.

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Women in Big Data

MAY 21, 2024

We provided a quick overview of Women in Big Data (WiBD). Launched in 2015 and becoming a nonprofit organization in 2020, WiBD is a grassroots initiative dedicated to inspiring, connecting, and advancing women in data fields. Currently, there is an ML Engineer Track, but no certification is available yet.

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Heartbeat

DECEMBER 20, 2023

Andrew Jones of Data Science Infinity Imagine that you train a network to recognize pictures of a statue. Andrew Jones of Data Science Infinity This operation is repeated for every section of the image that a filter strides over. You then repeat that loop for each layer in your network.

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Heartbeat

APRIL 23, 2023

SpaCy is a popular open-source NLP library developed in 2015 by Matthew Honnibal and Ines Montani, the founders of the software company Explosion. It provides a range of features for processing and analyzing text data. Developing a chatbot can be a complex task, but with the help of SpaCy, it can be made easier. What is SpaCy?

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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

AUGUST 21, 2023

ResNet is a deep CNN architecture developed by Kaiming He and his colleagues at Microsoft Research in 2015. Editor’s Note: Heartbeat is a contributor-driven online publication and community dedicated to providing premier educational resources for data science, machine learning, and deep learning practitioners.

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Mlearning.ai

APRIL 25, 2023

The plot shows that there has been a steady increase in the number of titles added each year, with a notable jump in 2015. Further Analysis From the first plot, we can see the frequency of content added by Netflix from 2008 to 2021. From the second plot, we can see the top 20 genres that have been added by Netflix from 2008 to 2021.

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Mlearning.ai

JULY 2, 2023

The Art of Forecasting in the Retail Industry Part I : Exploratory Data Analysis & Time Series Analysis In this article, I will conduct exploratory data analysis and time series analysis using a dataset consisting of product sales in different categories from a store in the US between 2015 and 2018.

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Snorkel AI

FEBRUARY 13, 2023

In addition, we are also responsible for the Experimentation Platforms at Comcast and the products, the data platforms that kind of underlie all these AI and machine-learning applications, as well as our product analytics platforms that make it easier to train, develop, and manage models. The voice remote was launched for Comcast in 2015.

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Snorkel AI

FEBRUARY 13, 2023

In addition, we are also responsible for the Experimentation Platforms at Comcast and the products, the data platforms that kind of underlie all these AI and machine-learning applications, as well as our product analytics platforms that make it easier to train, develop, and manage models. The voice remote was launched for Comcast in 2015.

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DrivenData Labs

SEPTEMBER 10, 2024

Winning teams included individuals with expertise in computer science, engineering, biomedical informatics, neuroscience, psychology, data science, sociology, and various clinical specialties. Many teams combined technical skills in AI/ML with domain knowledge in neuroscience, aging, or healthcare.

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