Women in Big Data

DECEMBER 13, 2023

Dr Sonal Khosla (Speaker) holds a PhD in Computer Science with a specialization in Natural Language Processing from Symbiosis International University, India with publications in peer reviewed Indexed journals. Computational Linguistics is rule based modeling of natural languages.

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Mlearning.ai

MAY 23, 2023

Here are a few courses you can check out — AI for Medicine Specialization Natural Language Processing Specialization Generative Adversarial Networks (GANs) Specialization Educational Background A Bachelor’s degree in a quantitative field like computer science, mathematics, statistics, or engineering is often the minimum requirement.

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Mlearning.ai

APRIL 24, 2023

Learning about the framework of a service cloud platform is time consuming and frustrating because there is a lot of new information from many different computing fields (computer science/database, software engineering/developers, data science/scientific engineering & computing/research).

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Pickl AI

MAY 10, 2023

Machine Learning is a subset of Artificial Intelligence and Computer Science that makes use of data and algorithms to imitate human learning and improving accuracy. Being an important component of Data Science, the use of statistical methods are crucial in training algorithms in order to make classification.

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The MLOps Blog

OCTOBER 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. How do I develop my body of work?

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Heartbeat

OCTOBER 25, 2023

Empowering Data Scientists and Machine Learning Engineers in Advancing Biological Research Image from European Bioinformatics Institute Introduction: In biological research, the fusion of biology, computer science, and statistics has given birth to an exciting field called bioinformatics. We pay our contributors, and we don’t sell ads.

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Flipboard

AUGUST 17, 2023

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

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Dataconomy

JULY 24, 2023

To put it another way, a data scientist turns raw data into meaningful information using various techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. Machine learning Machine learning is a key part of data science.

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Mlearning.ai

JUNE 27, 2023

Hierarchical Clustering. Hierarchical Clustering: Since, we have already learnt “ K- Means” as a popular clustering algorithm. The other popular clustering algorithm is “Hierarchical clustering”. remember we have two types of “Hierarchical Clustering”. Divisive Hierarchical clustering. They are : 1.Agglomerative

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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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Snorkel AI

JANUARY 26, 2023

I am a PhD student in the computer science department at Stanford, advised by Chris Ré working on some broad themes of understanding data-centric AI, weak supervision and theoretical machine learning. If I could try to read it back to you quickly: take a canonical ML problem. Mayee Chen: Okay. Hi everyone.

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Snorkel AI

JANUARY 26, 2023

I am a PhD student in the computer science department at Stanford, advised by Chris Ré working on some broad themes of understanding data-centric AI, weak supervision and theoretical machine learning. If I could try to read it back to you quickly: take a canonical ML problem. Mayee Chen: Okay. Hi everyone.

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IBM Journey to AI blog

APRIL 18, 2024

Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles. Building an in-house team with AI, deep learning , machine learning (ML) and data science skills is a strategic move.

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NYU Center for Data Science

NOVEMBER 15, 2023

Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce Harrop, Benjamin Hillman, Andrea Jenney, Savannah L.

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Heartbeat

AUGUST 23, 2023

NLP is fundamentally an interdisciplinary field that blends linguistics, computer science, and artificial intelligence to provide robots with the capacity to comprehend and analyze human language. But exactly what is NLP , and how can it facilitate legal discovery? We pay our contributors, and we don’t sell ads.

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AWS Machine Learning Blog

SEPTEMBER 18, 2023

Machine learning (ML) is becoming increasingly complex as customers try to solve more and more challenging problems. This complexity often leads to the need for distributed ML, where multiple machines are used to train a single model. SageMaker is a fully managed service for building, training, and deploying ML models.

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AWS Machine Learning Blog

MAY 1, 2024

Using the Neuron Distributed library with SageMaker SageMaker is a fully managed service that provides developers, data scientists, and practitioners the ability to build, train, and deploy machine learning (ML) models at scale. Cluster update is currently enabled for the TRN1 instance family as well as P and G GPU-based instance types.

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AWS Machine Learning Blog

MARCH 15, 2024

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities.

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Towards AI

APRIL 4, 2024

Machine learning (ML) has proven that it is here with us for the long haul, everyone who had their doubts by calling it a phase should by now realize how wrong they are, ML has being used in various sector’s of society such as medicine, geospatial data, finance, statistics and robotics.

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Dataconomy

MARCH 13, 2023

Scikit-learn:  Scikit-learn is an open-source library that provides a range of tools for building and training machine learning models, including classification, regression, and clustering. Model selection Model selection involves choosing the right algorithm, architecture, and hyperparameters for the AI model.

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AWS Machine Learning Blog

AUGUST 22, 2023

Machine learning (ML) is revolutionizing solutions across industries and driving new forms of insights and intelligence from data. Many ML algorithms train over large datasets, generalizing patterns it finds in the data and inferring results from those patterns as new unseen records are processed. What is federated learning?

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AWS Machine Learning Blog

JUNE 7, 2023

Training setup We provisioned a managed compute cluster comprised of 16 dl1.24xlarge instances using AWS Batch. We developed an AWS Batch workshop that illustrates the steps to set up the distributed training cluster with AWS Batch. More specifically, a fully managed AWS Batch compute environment is created with DL1 instances.

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O'Reilly Media

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. What does a modern technology stack for streamlined ML processes look like?

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IBM Journey to AI blog

JULY 6, 2023

These computer science terms are often used interchangeably, but what differences make each a unique technology? While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences.

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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. In this post, we deep dive into the technical details of this ML model.

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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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PyImageSearch

JULY 3, 2023

Machine learning (ML) approaches can be used to learn utility functions by training it on historical data of which home pages have been created for members (i.e., Users are grouped into small clusters based on their viewing history to obtain context-only features. what they see, how they interact, and what they play).

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Mlearning.ai

JUNE 25, 2023

Overview of Quantum Error Mitigation in NISQ through QML This article is part of our research under the guidance of Professor N.Geethanjali, Department of Computer Science & Technology, Sri Krishnadevaraya University, Andhra Pradesh State , INDIA. The below diagram gives a clear distinction between these two.

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AWS Machine Learning Blog

JANUARY 13, 2023

It involves training a global machine learning (ML) model from distributed health data held locally at different sites. The eICU data is ideal for developing ML algorithms, decision support tools, and advancing clinical research. We tested a single account-based distributed computing setup with one server and two client nodes.

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Mlearning.ai

MAY 23, 2023

Read the full article here —  [link] For final-year students pursuing a degree in computer science or related disciplines, engaging in machine learning projects can be an excellent way to consolidate theoretical knowledge, gain practical experience, and showcase their skills to potential employers. Working Video of our App [link] 20.

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AWS Machine Learning Blog

MAY 24, 2023

As an alternative, you can use FAISS , an open-source vector clustering solution for storing vectors. About the authors Alfred Shen is a Senior AI/ML Specialist at AWS. He is a dedicated applied AI/ML researcher, concentrating on CV, NLP, and multimodality. Dr. Changsha Ma is an AI/ML Specialist at AWS.

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DrivenData Labs

DECEMBER 7, 2023

Solvers submitted a wide range of methodologies to this end, including using open-source and third party LLMs (GPT, LLaMA), clustering (DBSCAN, K-Means), dimensionality reduction (PCA), topic modeling (LDA, BERT), sentence transformers, semantic search, named entity recognition, and more. and DistilBERT.

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AWS Machine Learning Blog

JANUARY 20, 2023

As the company continues to evolve to integrate AI into its existing and new product catalog, this requires sophisticated approaches to train and deploy multi-modal machine learning (ML) ensemble models for solving complex business needs. Christopher earned his Bachelor of Science in Computer Science from Northeastern Illinois University.

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Pickl AI

MAY 16, 2023

Python, Data Mining, Analytics and ML are one of the most preferred skills for a Data Scientist. Skilled in programming languages such as Python, R, and SQL, and have worked on various projects involving predictive modeling, clustering, and classification. In fact, these industries majorly employ Data Scientists.

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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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Flipboard

JULY 10, 2023

Figure 4: Architecture of fully connected autoencoders (source: Amor, “Comprehensive introduction to Autoencoders,” ML Cheat Sheet , 2021 ). Feature Learning Autoencoders can learn meaningful features from input data, which can be used for downstream machine learning tasks like classification, clustering, or regression.

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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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