AWS Machine Learning Blog

DECEMBER 24, 2024

Trainium chips are purpose-built for deep learning training of 100 billion and larger parameter models. Model training on Trainium is supported by the AWS Neuron SDK, which provides compiler, runtime, and profiling tools that unlock high-performance and cost-effective deep learning acceleration. architectures/5.sagemaker-hyperpod/LifecycleScripts/base-config/

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Marktechpost

DECEMBER 16, 2023

The intersection of neuroscience and artificial intelligence has seen remarkable progress, notably through the development of an open-source Python library known as “snnTorch.” Over the past four years, the team’s Python library, “snnTorch,” has gained significant traction, boasting over 100,000 downloads.

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Flipboard

MARCH 24, 2025

Jump Right To The Downloads Section Building on FastAPI Foundations In the previous lesson , we laid the groundwork for understanding and working with FastAPI. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Looking for the source code to this post?

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Marktechpost

NOVEMBER 16, 2023

Thanks to developments in deep learning approaches, the capability of image analysis algorithms has been greatly enhanced. The researchers have made their model available as a pre-trained Python package so anyone can use it. Their dataset is also easily accessible, requiring no special permissions or requests to download it.

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Marktechpost

FEBRUARY 23, 2025

Whether you’re a beginner taking your first steps in Python programming or an experienced data scientist working on complex machine learning models, Google Colab offers an accessible, collaborative environment that’s transforming how we code. Download your notebook To save a copy of your notebook on your local computer.

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PyImageSearch

SEPTEMBER 30, 2024

Home Table of Contents Introduction to GitHub Actions for Python Projects Introduction What Is CICD? For Python projects, CI/CD pipelines ensure that your code is consistently integrated and delivered with high quality and reliability. Git is the most commonly used VCS for Python projects, enabling collaboration and version tracking.

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Marktechpost

FEBRUARY 1, 2025

torch is a deep learning framework commonly used for machine learning tasks, including AI-based text generation. Step 2: Downloading NLP Tokenization Data Copy Code Copied Use a different Browser import nltk nltk.download('punkt_tab') The punkt_tab dataset is downloaded using the above code.

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Analytics Vidhya

APRIL 1, 2023

Introduction The current trend in NLP includes downloading and fine-tuning pre-trained models with millions or even billions of parameters. However, storing and sharing such large trained models is time-consuming, slow, and expensive.

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Marktechpost

NOVEMBER 25, 2023

Addressing this, Jason Eshraghian from UC Santa Cruz developed snnTorch, an open-source Python library implementing spiking neural networks, drawing inspiration from the brain’s remarkable efficiency in processing data. snnTorch , a pandemic-born passion project, has gained traction, surpassing 100,000 downloads.

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PyImageSearch

SEPTEMBER 23, 2024

Home Table of Contents Deploying a Vision Transformer Deep Learning Model with FastAPI in Python What Is FastAPI? You’ll learn how to structure your project for efficient model serving, implement robust testing strategies with PyTest, and manage dependencies to ensure a smooth deployment process. Testing main.py

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Flipboard

MARCH 27, 2023

torch.compile Over the last few years, PyTorch has evolved as a popular and widely used framework for training deep neural networks (DNNs). The success of PyTorch is attributed to its simplicity, first-class Python integration, and imperative style of programming. Jump Right To The Downloads Section What’s New in PyTorch 2.0?

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Marktechpost

NOVEMBER 18, 2024

VirtuDockDL’s user-friendly GUI, based on the Flask framework, supports molecule uploads, task initiation, and result downloads, organizing features into tabs for ease of use. In conclusion, VirtuDockDL is a new Python-based web platform designed to streamline drug discovery using deep learning.

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Deep Learning Neural Network Python Automation 79

The MLOps Blog

MAY 10, 2023

How to save a trained model in Python? In this section, you will see different ways of saving machine learning (ML) as well as deep learning (DL) models. Saving trained model with pickle The pickle module can be used to serialize and deserialize the Python objects. Now let’s see how we can save our model.

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Unite.AI

JUNE 21, 2024

The Rise of CUDA-Accelerated AI Frameworks GPU-accelerated deep learning has been fueled by the development of popular AI frameworks that leverage CUDA for efficient computation. NVIDIA TensorRT , a high-performance deep learning inference optimizer and runtime, plays a vital role in accelerating LLM inference on CUDA-enabled GPUs.

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PyImageSearch

JANUARY 6, 2025

Python or R) to find the critical value from the -distribution for the chosen and degrees of freedom ( ). Performing the Grubbs Test In this section, we will see how to perform the Grubbs test in Python for sample datasets with small sample sizes. Note: We need to use statistical tables ( Table 1 ) or software (e.g., Thakur, eds.,

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Flipboard

OCTOBER 9, 2023

This would include steps related to downloading certain components, performing some commands, and anything that you would do on a simple command line to configure everything from scratch. It allows us to start API development within a few lines of simple Python code. the image). Let’s look at the Dockerfile now and go line by line.

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Machine Learning Computer Vision Deep Learning Python 152

Flipboard

SEPTEMBER 4, 2023

Home Table of Contents Getting Started with Docker for Machine Learning Overview: Why the Need? These images also support interfacing with the GPU, meaning you can leverage it for training your Deep Learning networks written in TensorFlow. What Are Containers? How Do Containers Differ from Virtual Machines? Follow along!

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Machine Learning Computer Vision Deep Learning Python 152

AWS Machine Learning Blog

MAY 9, 2023

In this post, we help you understand the Python backend that is supported by Triton on SageMaker so that you can make an informed decision for your workloads and achieve great results. It dynamically downloads models from Amazon S3 to the instance’s storage volume if the invoked model isn’t available on the instance storage volume.

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AWS Machine Learning Blog

MARCH 8, 2023

This post shows a way to do this using Snowflake as the data source and by downloading the data directly from Snowflake into a SageMaker Training job instance. We create a custom training container that downloads data directly from the Snowflake table into the training instance rather than first downloading the data into an S3 bucket.

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Marktechpost

OCTOBER 25, 2024

It’s built on top of popular deep learning frameworks like PyTorch and TensorFlow, making it accessible to a broad audience of developers and researchers. spaCy is a popular open-source Python library designed for natural language processing (NLP) tasks.

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Dlabs.ai

JUNE 19, 2020

If you Google ‘ what’s needed for deep learning ,’ you’ll find plenty of advice that says vast swathes of labeled data (say, millions of images with annotated sections) are an absolute must. You may well come away thinking, deep learning is for ‘superhumans only’ — superhumans with supercomputers. Sounds interesting?

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Mlearning.ai

JANUARY 27, 2023

Save this blog for comprehensive resources for computer vision Source: appen Working in computer vision and deep learning is fantastic because, after every few months, someone comes up with something crazy that completely changes your perspective on what is feasible. How to read an image in Python using OpenCV — 2023 2.

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Computer Vision Deep Learning Python Neural Network 98

PyImageSearch

FEBRUARY 6, 2023

Furthermore, this tutorial aims to develop an image classification model that can learn to classify one of the 15 vegetables (e.g., If you are a regular PyImageSearch reader and have even basic knowledge of Deep Learning in Computer Vision, then this tutorial should be easy to understand. tomato, brinjal, and bottle gourd).

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PyImageSearch

APRIL 24, 2023

This tutorial is primarily for developers who want to accelerate their deep learning models with PyTorch 2.0. In this series, you will learn about Accelerating Deep Learning Models with PyTorch 2.0. TorchDynamo and TorchInductor (primarily for developers) (this tutorial) To learn what’s behind PyTorch 2.0,

Neural Network 101

Neural Network Deep Learning Computer Vision Python 101

AWS Machine Learning Blog

SEPTEMBER 20, 2023

AWS provides Deep Learning Containers (DLCs) for popular ML frameworks such as PyTorch, TensorFlow, and Apache MXNet, which you can use with SageMaker for training and inference. Finally, we deploy the ONNX model along with a custom inference code written in Python to Azure Functions using the Azure CLI. image and Python 3.0

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ML Python Deep Learning Machine Learning 117

PyImageSearch

FEBRUARY 20, 2023

Jump Right To The Downloads Section Learning JAX in 2023: Part 1 — The Ultimate Guide to Accelerating Numerical Computation and Machine Learning ?? Introduction As deep learning practitioners, it can be tough to keep up with all the new developments. Automatic Differentiation is at the very heart of Deep Learning.

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PyImageSearch

JANUARY 1, 2024

Gemini Pro is now available in Bard through the MakerSuite UI and their Python Software Development Kit (SDK). Gemini Pro Vision API This section demonstrates how to use the Python SDK for the Gemini API, which provides access to Google’s Gemini LLMs. The image is then displayed in the Colab notebook. That’s not the case.

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Computer Vision Deep Learning Python Natural Language Processing 110

AWS Machine Learning Blog

MAY 15, 2024

Optimized GEMM kernels ONNX Runtime supports the Microsoft Linear Algebra Subroutine (MLAS) backend as the default Execution Provider (EP) for deep learning operators. AWS Graviton3-based EC2 instances (c7g, m7g, r7g, c7gn, and Hpc7g instances) support bfloat16 format and MMLA instructions for the deep learning operator acceleration.

NLP 125

NLP BERT Natural Language Processing Python 125

PyImageSearch

DECEMBER 11, 2024

Home Table of Contents PNG Image to STL Converter in Python Why Convert a PNG to STL? To learn how to convert a PNG image to an STL file, keep reading! Jump Right To The Downloads Section Why Convert a PNG to STL? Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated?

Python 52

Python Computer Vision Deep Learning Machine Learning 52

AWS Machine Learning Blog

APRIL 29, 2024

It provides an approachable, robust Python API for the full infrastructure stack of ML/AI, from data and compute to workflows and observability. Now, with today’s announcement, you have another straightforward compute option for workflows that need to train or fine-tune demanding deep learning models: running them on Trainium.

ML 116

ML Python Data Scientist Machine Learning 116

Flipboard

MARCH 6, 2023

Jump Right To The Downloads Section Triplet Loss with Keras and TensorFlow In the first part of this series, we discussed the basic formulation of a contrastive loss and how it can be used to learn a distance measure based on similarity. Looking for the source code to this post? Or has to involve complex mathematics and equations?

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Computer Vision Deep Learning Neural Network Artificial Intelligence 143

Flipboard

FEBRUARY 13, 2023

Jump Right To The Downloads Section Building a Dataset for Triplet Loss with Keras and TensorFlow In the previous tutorial , we looked into the formulation of the simplest form of contrastive loss. We tried to understand how these losses can help us learn a distance measure based on similarity. Looking for the source code to this post?

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AWS Machine Learning Blog

FEBRUARY 20, 2024

Download the model and its components WhisperX is a system that includes multiple models for transcription, forced alignment, and diarization. For smooth SageMaker operation without the need to fetch model artifacts during inference, it’s essential to pre-download all model artifacts. __dict__[WAV2VEC2_MODEL].get_model(dl_kwargs={"model_dir":

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Metadata Auto-complete Machine Learning Deep Learning 113

Heartbeat

JULY 25, 2023

Introduction When it comes to practicing deep learning at home vs. industry, there’s a huge disconnect. TensorFlow itself comes with the Dataset API that allows you to simply download and train data with just a couple of lines of code. Yes, even in python (we will see this later). Learn how Comet can help you do this.

Deep Learning 52

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AWS Machine Learning Blog

OCTOBER 5, 2023

First, download the Llama 2 model and training datasets and preprocess them using the Llama 2 tokenizer. For example, to use the RedPajama dataset, use the following command: wget [link] python nemo/scripts/nlp_language_modeling/preprocess_data_for_megatron.py He focuses on developing scalable machine learning algorithms.

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AWS Machine Learning Blog

OCTOBER 19, 2023

Customers increasingly want to use deep learning approaches such as large language models (LLMs) to automate the extraction of data and insights. For many industries, data that is useful for machine learning (ML) may contain personally identifiable information (PII). Download the SageMaker Data Wrangler flow.

Machine Learning 104

Machine Learning Python ML Automation 104

AssemblyAI

JUNE 24, 2024

Today, many modern Speech-to-Text APIs and Speaker Diarization libraries apply advanced Deep Learning models to perform tasks (A) and (B) near human-level accuracy, significantly increasing the utility of Speaker Diarization APIs. An embedding is a Deep Learning model’s low-dimensional representation of an input.

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