Flipboard

JULY 10, 2023

Home Table of Contents Introduction to Autoencoders What Are Autoencoders? Revisiting the Story Types of Autoencoder Vanilla Autoencoder Convolutional Autoencoder (CAE) Denoising Autoencoder Sparse Autoencoder Variational Autoencoder (VAE) Sequence-to-Sequence Autoencoder What Are the Applications of Autoencoders?

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Mlearning.ai

MARCH 6, 2023

This phenomenon occurs because many machine learning models are trained on a limited amount of data, which makes them susceptible to overfitting. GANs are a type of deep learning architecture comprising two neural networks: a generator and a discriminator. In the end, all we can do is imitate nature and its creations.

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Neural Network Convolutional Neural Networks Machine Learning Natural Language Processing 52

Becoming Human

MAY 15, 2023

If you are a student or a fresher who wants to be a part of the data science domain but is a little bit confused about What to learn? If you are a student or a fresher who wants to be a part of the data science domain but is a little bit confused about What to learn? How much to learn? What to do next?

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PyImageSearch

AUGUST 28, 2023

Introduction: Augmentations But Wait, What Is KerasCV? So, What Is AugMix Again? AugMix Breakdown (Part 1): Introduction to AugMix with KerasCV Welcome to an exploration of AugMix, a sophisticated technique that revolutionizes how we approach data augmentation in Machine Learning. Let’s dive in!

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PyImageSearch

JULY 24, 2023

Home Table of Contents What Is Keras Core? In this tutorial, you will learn about Keras Core , the new Keras Team repository that allows switching from the Keras backend to TensorFlow , PyTorch , and JAX. To learn how to navigate the Keras Core library, just keep reading. What Is Keras Core? What Is Keras Core?

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PyImageSearch

SEPTEMBER 25, 2023

In this lesson, we will answer this question by explaining the machine learning behind YouTube video recommendations. Highly specialized distributed learning algorithms and efficient serving mechanisms are required to process and serve such massive information in the user base and video corpus. RecSys’16 ).

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PyImageSearch

DECEMBER 25, 2023

Google and Generative AI What’s the Buzz? What Is Generative AI? In this tutorial, you will learn how to start with Generative AI Studio inside Google Cloud. To learn how to get started with the Generative AI studio inside Google Cloud Console, just keep reading. What Is Generative AI?

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PyImageSearch

NOVEMBER 13, 2023

Home Table of Contents Faster R-CNNs Object Detection and Deep Learning Measuring Object Detector Performance From Where Do the Ground-Truth Examples Come? One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al.

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PyImageSearch

NOVEMBER 20, 2023

Tools and Methodologies for Studying Causal Effects Welcome back to Part 3 of the 5-part series on Causality in Machine Learning. Picking up where we left off, let us revise what we learned in Part 1. Randomization, natural experiments, and conditioning, what are they? What do I mean by that?

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Heartbeat

JULY 17, 2023

[link] Transfer learning using pre-trained computer vision models has become essential in modern computer vision applications. Comet, a cloud-based machine learning platform, offers a powerful solution for tracking, comparing, and benchmarking fine-tuned models, allowing users to easily analyze and visualize their performance.

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Mlearning.ai

MARCH 2, 2023

Pre-training of Deep Bidirectional Transformers for Language Understanding BERT is a language model that can be fine-tuned for various NLP tasks and at the time of publication achieved several state-of-the-art results. Preliminaries: Transformers and Unsupervised Transfer Learning II.1 Importance of Understanding BERT Today II.

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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 26, 2024

This lesson is the 1st of a 3-part series on Understanding Tasks in Diffusers : Understanding Tasks in Diffusers: Part 1 (this tutorial) Understanding Tasks in Diffusers: Part 2 Understanding Tasks in Diffusers: Part 3 To learn how to make the most of your diffusion pipeline and work with the latest, just keep reading. What will we cover?

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PyImageSearch

MAY 22, 2023

Home Table of Contents DETR Breakdown Part 1: Introduction to DEtection TRansformers Why DETR and What’s So Special? ? What Is Object Detection? ? So What’s New in DETR? ? But, for now, let us focus on the topics at hand: why DETR where it came from what’s the big deal about it Why DETR and What’s So Special? ?

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PyImageSearch

AUGUST 7, 2023

This lesson is the last in a 3-part series on Deep Dive into Popular Recommendation Engines 101 : Fundamentals of Recommendation Systems Netflix Movies and Series Recommendation Systems LinkedIn Jobs Recommendation Systems (this tutorial) To learn how LinkedIn recommendations work, just keep reading.

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Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). What happened?   By framing different tasks in the paradigm of language modelling, models have had great success also in other domains such as reinforcement learning [13] and protein structure prediction [14].

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Sebastian Ruder

NOVEMBER 14, 2022

This post is partially based on a keynote I gave at the Deep Learning Indaba 2022. Current state-of-the-art models in many ML domains are mainly based on two ingredients: 1) large, scalable architectures (often based on the Transformer [5] ) and 2) transfer learning [6]. 10 years on, little thus seems to have changed.

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PyImageSearch

JULY 3, 2023

And, thanks to Netflix recommendations, we don’t have to worry about what to watch. In this blog post, we will dive deeper into the Netflix movies and series recommendation systems ( Figure 1 ). Figure 1: Netflix Recommendation System (source: “Netflix Film Recommendation Algorithm,” Pinterest ).

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PyImageSearch

JUNE 19, 2023

Home Table of Contents Fundamentals of Recommendation Systems Recommendation Engines and Their Types What Are Recommendation Engines? We will start by learning the basics of these systems and then delve into some of the most popular ones in detail. machine learning, statistics, probability, and algebra) are used to achieve this.

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PyImageSearch

JANUARY 22, 2024

Setup and Imports Diffusers But What Is AutoPipeline ? What Are Some Other Pipelines and Models? To learn how to get started with using diffusers, just keep reading. After training, we can use the Diffusion Model to generate data by simply passing randomly sampled noise through the learned denoising process.

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AWS Machine Learning Blog

MARCH 6, 2023

LLMs’ generative abilities make them popular for text synthesis, summarization, machine translation, and more. These factors require training an LLM over large clusters of accelerated machine learning (ML) instances. Networking – Make sure EFA and NVIDIA GPUDirectRDMA are enabled, for fast inter-machine communication.

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AWS Machine Learning Blog

MAY 2, 2023

In this post, we dive deep to see how Amazon SageMaker can serve these models using NVIDIA Triton Inference Server. SageMaker provides single model endpoints , which allow you to deploy a single machine learning (ML) model against a logical endpoint. One of the most popular models available today is XGBoost.

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PyImageSearch

JANUARY 29, 2024

Home Table of Contents Adversarial Learning with Keras and TensorFlow (Part 3): Exploring Adversarial Attacks Using Neural Structured Learning (NSL) Introduction to Advanced Adversarial Techniques in Machine Learning Harnessing NSL for Robust Model Training: Insights from Part 2 Deep Dive into Adversarial Attack Formulations: PGD and FGSM Explored (..)

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Computer Vision Deep Learning Neural Network Machine Learning 56

AWS Machine Learning Blog

NOVEMBER 30, 2023

Research shows that not only do risks for bias and toxicity transfer from pre-trained foundation models (FM) to task-specific generative AI services, but that tuning an FM for specific tasks, on incremental datasets, introduces new and possibly greater risks. What is FMEval? How can you get started?

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PyImageSearch

OCTOBER 2, 2023

Home Table of Contents A Deep Dive into Variational Autoencoder with PyTorch Introduction Comparison with Convolutional Autoencoder Architecture Latent Space Loss Function Why Does VAE Stand Out? By the conclusion, you’ll have a deep appreciation for VAEs, their capabilities in image generation, and the intricacies of the dataset.

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PyImageSearch

MARCH 11, 2024

Home Table of Contents Understanding Tasks in Diffusers: Part 2 Configuring Your Development Environment What Is Inpainting? Luckily, diffusers is pip-installable: $ pip install diffusers $ pip install accelerate What Is Inpainting? This tutorial is inspired by the beautiful documentation at Hugging Face Diffusers.

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Lexalytics

APRIL 5, 2021

Their neurons looked like this: What this neuron does is fire if both of its excitatory inputs are active—unless the inhibitory input (with the black dot) is active. One of the problems with these threshold logic circuits was that they had to be hand-designed, yet neurons in the brain seemed to learn on their own.

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PyImageSearch

JANUARY 8, 2024

Home Table of Contents Adversarial Learning with Keras and TensorFlow (Part 1): Overview of Adversarial Learning Configuring Your Development Environment Need Help Configuring Your Development Environment?

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PyImageSearch

JANUARY 15, 2024

Home Table of Contents Adversarial Learning with Keras and TensorFlow (Part 2): Implementing the Neural Structured Learning (NSL) Framework and Building a Data Pipeline Adversarial Learning with NSL CIFAR-10 Dataset Configuring Your Development Environment Need Help Configuring Your Development Environment?

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Computer Vision Neural Network Deep Learning Artificial Intelligence 64

The Stanford AI Lab Blog

JANUARY 21, 2022

Deep learning has enabled improvements in the capabilities of robots on a range of problems such as grasping 1 and locomotion 2 in recent years. Indeed, this recipe of massive, diverse datasets combined with scalable offline learning algorithms (e.g. This work was conducted as part of SAIL and CRFM.

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Marktechpost

JUNE 27, 2023

Activation functions for neural networks are an essential part of deep learning since they decide the accuracy and efficiency of the training model used to create or split a large-scale neural network and the output of deep learning models. An artificial neural network contains a large number of linked individual neurons.

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The Stanford AI Lab Blog

DECEMBER 6, 2021

Feel free to reach out to the contact authors and the workshop organizers directly to learn more about the work that’s happening at Stanford! The thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021 is being hosted virtually from Dec 6th - 14th. Campbell, Kiah Hardcastle, Isabel I.C.

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PyImageSearch

FEBRUARY 19, 2024

vs. Gemini Pro for Image Classification Summary and Key Takeaways Citation Information Image Classification with Gemini Pro In this tutorial, you’ll learn how to use the Gemini Pro generative model with the Google AI Python SDK (software development kit) to generate code for image classification in PyTorch. vs. ChatGPT-3.5

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Topbots

JULY 6, 2023

Building on the foundations of Transformer architecture and BERT’s bidirectional upgrade , several groundbreaking language models have emerged in recent years, pushing the boundaries of what machines can understand and generate. What is the goal? What are the results? How is the problem approached?

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Mlearning.ai

JULY 31, 2023

However, what they represent to a computer and how we perceive them in the real world are very different. Things become more complex when we apply this information to Deep Learning (DL) models, where each data type presents unique challenges for capturing its inherent characteristics. So, what is this single format I speak of?

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PyImageSearch

OCTOBER 23, 2023

Learning on your employer’s administratively locked system? Our journey begins with training a VAE on this dataset, setting the stage for a series of captivating experiments. Ready to unravel the intricacies of training and experimenting with Variational Autoencoders on the CelebA dataset using PyTorch? Let’s dive in!

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PyImageSearch

SEPTEMBER 11, 2023

Furthermore, you will learn how SAM can be used for making segmentation predictions in real-time and how you can integrate it with your own computer vision projects. Furthermore, you will learn how SAM can be used for making segmentation predictions in real-time and how you can integrate it with your own computer vision projects.

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