PyImageSearch

JANUARY 30, 2023

This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. To learn about Computer Vision and Deep Learning for Education, just keep reading. This series is about CV and DL for Industrial and Big Business Applications.

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ODSC - Open Data Science

APRIL 20, 2023

Deep Learning Approaches to Sentiment Analysis (with spaCy!) In this post, we’ll be demonstrating two deep learning approaches to sentiment analysis, specifically using spaCy. Is Machine Learning Necessary to Solve Problems in Biology? Here’s how. Register by Friday to save 30%.

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Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].”

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Pickl AI

JUNE 5, 2023

The world of AI, ML and Deep learning continues to evolve and expand. With the significant rise in its application of Deep Learning and allied technologies, across the business spectrum, it has laid the foundation stone for a new future. between 2023 to 2030. What is Deep Learning ?

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Heartbeat

NOVEMBER 21, 2023

Computer vision, the field dedicated to enabling machines to perceive and understand visual data, has witnessed a monumental shift in recent years with the advent of deep learning. Photo by charlesdeluvio on Unsplash Welcome to a journey through the advancements and applications of deep learning in computer vision.

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The MLOps Blog

JUNE 27, 2023

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. Open-source tools have gained significant traction due to their flexibility, community support, and adaptability to various workflows.

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Google Research AI blog

APRIL 21, 2023

However, developing and iterating on these ML-based multimedia prototypes can be challenging and costly. It usually involves a cross-functional team of ML practitioners who fine-tune the models, evaluate robustness, characterize strengths and weaknesses, inspect performance in the end-use context, and develop the applications.

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ODSC - Open Data Science

MARCH 17, 2023

How to Deploy a Deep Learning Model with Jina, Announcing GPT-4, and Multimodal Visual Question Answering How to Deploy a Deep Learning Model with Jina (and Design a Kitten Along the Way) Learn how to build and deploy an Executor that uses Stable Diffusion to generate images.

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PyImageSearch

JANUARY 2, 2023

This blog will cover the benefits, applications, challenges, and tradeoffs of using deep learning in healthcare. Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research The volume of healthcare-related data is increasing at an exponential rate.

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Dataversity

DECEMBER 16, 2022

2022 was a big year for AI, and we’ve seen significant advancements in various areas – including natural language processing (NLP), machine learning (ML), and deep learning. Unsupervised and self-supervised learning are making ML more accessible by lowering the training data requirements.

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Google Research AI blog

MAY 19, 2023

Posted by Natalia Ponomareva and Alex Kurakin, Staff Software Engineers, Google Research Large machine learning (ML) models are ubiquitous in modern applications: from spam filters to recommender systems and virtual assistants. Therefore, protecting the privacy of the training data is critical to practical, applied ML.

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Google Research AI blog

APRIL 30, 2023

Posted by Catherine Armato, Program Manager, Google The Eleventh International Conference on Learning Representations (ICLR 2023) is being held this week as a hybrid event in Kigali, Rwanda. We are proud to be a Diamond Sponsor of ICLR 2023, a premier conference on deep learning, where Google researchers contribute at all levels.

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PyImageSearch

FEBRUARY 20, 2023

Table of Contents Learning JAX in 2023: Part 1 — The Ultimate Guide to Accelerating Numerical Computation and Machine Learning ?? Jump Right To The Downloads Section Learning JAX in 2023: Part 1 — The Ultimate Guide to Accelerating Numerical Computation and Machine Learning ?? What Is JAX? autograd XLA ?

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Towards AI

AUGUST 27, 2023

Last Updated on August 28, 2023 by Editorial Team Author(s): Marcello Politi Originally published on Towards AI. Learn how to prevent users and LLMs mistakes in your code Photo by Bradley Ziffer on Unsplash This member-only story is on us. Upgrade to access all of Medium. Join thousands of data leaders on the AI newsletter.

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Google Research AI blog

JUNE 18, 2023

Posted by Shaina Mehta, Program Manager, Google This week marks the beginning of the premier annual Computer Vision and Pattern Recognition conference (CVPR 2023), held in-person in Vancouver, BC (with additional virtual content).

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AWS Machine Learning Blog

MAY 10, 2023

Project Jupyter is a multi-stakeholder, open-source project that builds applications, open standards, and tools for data science, machine learning (ML), and computational science. Given the importance of Jupyter to data scientists and ML developers, AWS is an active sponsor and contributor to Project Jupyter.

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Google Research AI blog

FEBRUARY 2, 2023

Great machine learning (ML) research requires great systems. In this post, we provide an overview of the numerous advances made across Google this past year in systems for ML that enable us to support the serving and training of complex models while easing the complexity of implementation for end users.

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Data Science Dojo

AUGUST 28, 2023

It also applies to customizing other machine learning models like natural language processing (NLP) or deep learning models. Adapting Existing Models for Specific Tasks: Tailor pre-trained models for specific tasks, as this approach is cost-effective.

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Towards AI

APRIL 6, 2023

Last Updated on April 11, 2023 by Editorial Team Author(s): Adrienne Kline Originally published on Towards AI. Coined after the viral phrase, ‘you only live once’ (YOLO), the machine learning (ML) world first coined this acronym and repurposed it to You Only Look Once — YOLO. Join thousands of data leaders on the AI newsletter.

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Towards AI

JUNE 6, 2023

Last Updated on June 14, 2023 by Editorial Team Author(s): Jan Marcel Kezmann Originally published on Towards AI. Data is the lifeblood of ML and DL models, serving as the foundation upon which they learn and make predictions. In this blog post,… Read the full blog for free on Medium.

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Flipboard

APRIL 17, 2023

Home Table of Contents Learning JAX in 2023: Part 3 — A Step-by-Step Guide to Training Your First Machine Learning Model with JAX Configuring Your Development Environment Having Problems Configuring Your Development Environment? ? Looking for the source code to this post? Or has to involve complex mathematics and equations?

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Google Research AI blog

MAY 25, 2023

It builds on advances in deep learning efficiency and leverages reinforcement learning from human feedback to provide more relevant responses and increase the model’s ability to follow instructions. We use deep learning technology to achieve voice preservation and lip matching and enable high-quality video translation.

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Becoming Human

MAY 15, 2023

First learn the basics of Feature Engineering, and EDA then take some different-different data sheets (data frames) and apply all the techniques you have learned to date. Because this is the only effective way to learn Data Analysis. Some popular libraries used for deep learning are Keras , PyTorch , and TensorFlow.

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ODSC - Open Data Science

MARCH 6, 2023

In an effort to learn more about our community, we recently shared a survey about machine learning topics, including what platforms you’re using, in what industries, and what problems you’re facing. In the first blog, we’re going to discuss the technical side of things, such as what languages and platforms people are using.

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Mlearning.ai

JUNE 6, 2023

In today’s blog, we will see some very interesting Python Machine Learning projects with source code. This list will consist of Machine learning projects, Deep Learning Projects, Computer Vision Projects , and all other types of interesting projects with source codes also provided.

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Flipboard

SEPTEMBER 4, 2023

This lesson is the 1st of a 3-part series on Docker for Machine Learning : Getting Started with Docker for Machine Learning (this tutorial) Lesson 2 Lesson 3 Overview: Why the Need? Envision yourself as an ML Engineer at one of the world’s largest companies. How Do Containers Differ from Virtual Machines? That’s not the case.

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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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The MLOps Blog

JANUARY 26, 2024

Luckily, we have tried and trusted tools and architectural patterns that provide a blueprint for reliable ML systems. In this article, I’ll introduce you to a unified architecture for ML systems built around the idea of FTI pipelines and a feature store as the central component. But what is an ML pipeline?

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Heartbeat

JANUARY 25, 2023

Dear Heartbeat Readers, 2023 is off to a great start with some fantastic articles and series! With our new focus areas, we’re diving into Computer Vision and NLP projects as well as spending more time on deep learning projects and seeing how you, the community, use Comet and Kangas.

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Heartbeat

AUGUST 10, 2023

And the Comet Machine Learning (ML) platform will help you get up to speed by letting you quickly train, test, and manage ML models in production. The tool allows businesses to easily leverage ML’s power and boost productivity through its experiment-tracking features, interactive visualizations, and monitoring capabilities.

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Heartbeat

DECEMBER 14, 2023

LeCun received the 2018 Turing Award (often referred to as the "Nobel Prize of Computing"), together with Yoshua Bengio and Geoffrey Hinton, for their work on deep learning. Hinton is viewed as a leading figure in the deep learning community. > Finished chain. ") > Entering new AgentExecutor chain.

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The MLOps Blog

AUGUST 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. Stefan: Yeah.

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Flipboard

JULY 10, 2023

Figure 3: Latent space visualization of the closet (source: Kumar, “Autoencoder vs Variational Autoencoder (VAE): Differences,” Data Analytics , 2023 ). Figure 4: Architecture of fully connected autoencoders (source: Amor, “Comprehensive introduction to Autoencoders,” ML Cheat Sheet , 2021 ).

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Towards AI

JULY 20, 2023

Last Updated on July 20, 2023 by Editorial Team Author(s): Jesus Rodriguez Originally published on Towards AI. TheSequence is a no-BS (meaning no hype, no news etc) ML-oriented newsletter that takes 5 minutes to read. TheSequence is a no-BS (meaning no hype, no news etc) ML-oriented newsletter that takes 5 minutes to read.

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ODSC - Open Data Science

SEPTEMBER 5, 2023

There’s not enough space in this blog to talk about them all, but we’ve highlighted a few below. During this tutorial, you’ll learn about the practical tools and best practices for evaluating and choosing LLMs. ODSC West is just a few months away and we couldn’t be more excited to announce our first 50 sessions!

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Google Research AI blog

JUNE 15, 2023

On-device ML inference in mobile environments requires meticulous performance optimization and consideration of trade-offs due to resource constraints. As discussed in our previous blog post , GPU-accelerated ML inference is often limited by memory performance, and execution of LDMs is no exception.

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AWS Machine Learning Blog

AUGUST 2, 2023

SageMaker Distribution is a pre-built Docker image containing many popular packages for machine learning (ML), data science, and data visualization. This includes deep learning frameworks like PyTorch, TensorFlow, and Keras; popular Python packages like NumPy, scikit-learn, and pandas; and IDEs like JupyterLab.

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