Data Science Dojo

JUNE 14, 2023

GPT is one of the most popular machine-learning models used for text processing. I t belongs to a class of models called “ Transformers ” which are classified among deep learning models. Pegasus Transformer This is a part of the Transformers library available in Python 3. And that was just one model.

Machine Learning 195

Machine Learning Machine Learning Algorithm AI 195

Data Science Dojo

JUNE 14, 2023

GPT is one of the most popular machine-learning models used for text processing. I t belongs to a class of models called “ Transformers ” which are classified among deep learning models. Pegasus Transformer This is a part of the Transformers library available in Python 3. And that was just one model.

Machine Learning 195

Machine Learning Machine Learning Algorithm AI 195

Data Science Dojo

JUNE 14, 2023

GPT is one of the most popular machine-learning models used for text processing. I t belongs to a class of models called “ Transformers ” which are classified among deep learning models. Pegasus Transformer This is a part of the Transformers library available in Python 3. And that was just one model.

Machine Learning 195

Machine Learning Machine Learning Algorithm AI 195

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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Python ML ML Deep Learning 94

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.

Machine Learning 148

Machine Learning Machine Learning Deep Learning Deep Learning 148

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 Deep Learning Deep Learning Machine Learning 52

Dataconomy

AUGUST 15, 2024

Stable Diffusion is a deep-learning model that generates high-quality images based on text prompts. Here’s a step-by-step guide: Install Python : Ensure Python 3.8 You can download it from the official Python website. What is Stable Diffusion? or higher is installed on your system. safetensors `.

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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!

Machine Learning 148

Machine Learning Machine Learning Deep Learning Deep Learning 148

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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Deep Learning Deep Learning Python Data Scientist 98

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.

ML 121

ML ML AWS Python 121

IBM Data Science in Practice

APRIL 9, 2024

Instead, we use pre-trained deep learning models like VGG or ResNet to extract feature vectors from the images. Image retrieval search architecture The architecture follows a typical machine learning workflow for image retrieval. You can follow command below to download the data. Building the Image Search Pipeline 1.

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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,

Deep Learning 91

Deep Learning Deep Learning Python Computer Science 91

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

ML 115

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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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AWS Clustering Deep Learning Deep Learning 95

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

Deep Learning Deep Learning Python ML 52

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.

Machine Learning 106

Machine Learning Machine Learning Deep Learning Deep Learning 106

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.

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AWS Natural Language Processing Python Deep Learning 122

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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Deep Learning Deep Learning Python Data Analysis 128

Towards AI

NOVEMBER 6, 2024

But how can we harness machine learning for something as niche as rice classification? Well, this is where PyTorch, a powerful deep learning library, steps in. This hands-on tutorial is designed for anyone with a basic understanding of Python, and I’ll walk you through each step of the code so you can follow along effortlessly.

Deep Learning 112

Deep Learning Deep Learning Machine Learning Machine Learning 112

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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AWS AI AI Machine Learning 112

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.

Deep Learning 98

Deep Learning Deep Learning Natural Language Processing Python 98

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?

Deep Learning 140

Deep Learning Deep Learning Data Pipeline Computer Science 140

Explosion

OCTOBER 18, 2016

The custom pipelines are particularly exciting, because they let you hook your own deep learning models into spaCy. In this tutorial, we’ll be using Keras , as it’s the most popular deep learning library for Python. Of course, operating on single documents is inefficient, especially for deep learning models.

Deep Learning 52

Deep Learning Deep Learning Python 52

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 105

Machine Learning Machine Learning ML ML 105

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.

AWS 115

AWS Machine Learning Machine Learning Deep Learning 115

Heartbeat

FEBRUARY 9, 2023

One can build NLP projects in different ways, and one of those is by using the Python library S paCy. SpaCy is a free, open-source library written in Python for advanced Natural Language Processing. Installation of SpaCy The installation of Python on the system is a prerequisite for configuring SpaCy. What is spaCy?

Natural Language Processing 52

Natural Language Processing Python Deep Learning Deep Learning 52

Applied Data Science

AUGUST 2, 2021

Download the free, unabridged version here. They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. Download the free, unabridged version here.

Data Science 130

Data Science Data Scientist ML ML 130

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?

Data Pipeline 140

Data Pipeline Deep Learning Deep Learning Python 140

ODSC - Open Data Science

JANUARY 5, 2024

Python is still one of the most popular programming languages that developers flock to. In this blog, we’re going to take a look at some of the top Python libraries of 2023 and see what exactly makes them tick. NumPy arrays are similar to lists in Python, but they are optimized for performance.

Python 52

Python K-nearest Neighbors Data Science Data Visualization 52

Mlearning.ai

AUGUST 13, 2023

Pytesseract is one of python libraries which can help you perform OCR on documents to get all the text present in it. The initial stage involves table detection, which is facilitated by a Python library known as ultralytics. But what if you want only the tabular information? Code Let’s break down the process step by step.

Deep Learning 98

Deep Learning Deep Learning Python Machine Learning 98

AWS Machine Learning Blog

MAY 4, 2023

You can use ml.trn1 and ml.inf2 compatible AWS Deep Learning Containers (DLCs) for PyTorch, TensorFlow, Hugging Face, and large model inference (LMI) to easily get started. For the full list with versions, see Available Deep Learning Containers Images. petaflops of FP16/BF16 compute power.

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AWS Machine Learning Blog

JUNE 13, 2023

In this post, we demonstrate how to deploy Falcon for applications like language understanding and automated writing assistance using large model inference deep learning containers on SageMaker. SageMaker large model inference (LMI) deep learning containers (DLCs) can help. See the following code: %%writefile./code_falcon40b_deepspeed/serving.properties

Deep Learning 82

Deep Learning Deep Learning AWS Machine Learning 82

AssemblyAI

NOVEMBER 12, 2024

This tutorial will guide you through the process of using Google Cloud's Speech-to-Text API in your Python projects. The Google Cloud Speech-to-Text API is a service that enables developers to convert audio to text using Deep Learning models exposed through an API. This will download the JSON private key to your computer.

Python 59

Python Deep Learning Deep Learning AI 59

AWS Machine Learning Blog

MAY 30, 2023

When an On-Demand job is launched, it goes through five phases: Starting, Downloading, Training, Uploading, and Completed. From a pricing perspective, you are charged for Downloading, Training, and Uploading phases. In this post, we discuss the Downloading and Training phases.

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Flipboard

AUGUST 21, 2023

This lesson is the 3rd in our series on OAK 102 : Training the YOLOv8 Object Detector for OAK-D Hand Gesture Recognition with YOLOv8 on OAK-D in Near Real-Time People Counter on OAK (this tutorial) To learn how to implement and run people counting on OAK, just keep reading. Looking for the source code to this post? mp4 │ └── example_02.mp4

Python 123

Python Deep Learning Deep Learning Algorithm 123

AWS Machine Learning Blog

APRIL 19, 2023

The DJL is a deep learning framework built from the ground up to support users of Java and JVM languages like Scala, Kotlin, and Clojure. With the DJL, integrating this deep learning is simple. Our data scientists train the model in Python using tools like PyTorch and save the model as PyTorch scripts.

ML 77

ML ML Deep Learning Deep Learning 77

Flipboard

FEBRUARY 16, 2023

In October 2022, we launched Amazon EC2 Trn1 Instances , powered by AWS Trainium , which is the second generation machine learning accelerator designed by AWS. Trn1 instances are purpose built for high-performance deep learning model training while offering up to 50% cost-to-train savings over comparable GPU-based instances.

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