DrivenData Labs

JANUARY 22, 2024

if use_LoRA : config = PeftConfig. from_pretrained ( pretrained_model_name_or_path = config. note_id ]) ) doc_index_mapping = dict ( zip ( docs , range ( len ( docs )))) # Identify union of categories in GT and PRED cats = np. from_pretrained ( CER_MODEL_PATH , model_max_length = MAX_SEQ_LEN ) if USE_LORA : config = PeftConfig.

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AWS Machine Learning Blog

NOVEMBER 17, 2023

A rules engine evaluates moderation guidelines, determining the frequency of stream sampling and the applicable moderation categories, all within predefined policies. If enabled in the config, perform a similarity check using image hash algorithms. This process involves the utilization of both ML and non-ML algorithms.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

The prompts are divided into different knowledge categories such as capitals, subsidiaries, and others. The evaluation measures the percentage of correct answers overall and per category. The above example is from the “gender/gender identity” category. Note that some predicate pairs can have more than one expected answer.

Algorithm 88

Algorithm AWS ML ML 88

Explosion

NOVEMBER 28, 2023

All these settings can be conveniently defined via the spaCy config system, which makes it easy to keep your environment reproducible and well organized. For token-level annotation we propose the pairwise F1 score, that also comes with a confusion matrix to help identify problematic pairs of categories.

Python 78

Python Algorithm Clustering Machine Learning 78

DagsHub

AUGUST 15, 2023

Next, we import all the modules we need: import yaml import torch import mlflow import ultralytics from utils.config import Config from utils.dagshub_yolo_cb import custom_callbacks_fn from utils.data import DataFunctions import dagshub from dagshub.data_engine import datasources, datasets Of the first set of modules, two are somewhat interesting.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

MAY 26, 2023

Logging and monitoring: AWS provides a range of logging and monitoring services—including Amazon CloudTrail, AWS Config and Amazon CloudWatch—that enable clients to monitor and audit their AWS environments for security events and compliance.

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AWS Machine Learning Machine Learning Cloud Computing 78

Heartbeat

MAY 9, 2023

take(1000) Let’s assign all the labels in the dataset as an array to a variable called “categories.” categories = small_train_dataset.features["label"].names take(1000) Let’s assign all the labels in the dataset as an array to a variable called “categories.” categories = small_train_dataset.features["label"].names

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PyImageSearch

MARCH 13, 2023

However, background pixels such as sky and road are often disregarded as object categories in instance segmentation tasks. Initialize a XXXModel model with the custom XXXModelConfig config object. Same as the Model and Config class, we can use the from_pretrained() method to retrieve the processor of any pre-trained model.

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AWS Machine Learning Blog

AUGUST 22, 2023

When choosing an FL framework, we usually consider its support for model category, ML framework, and device or operation system. It serializes these configuration dictionaries (or config dict for short) to their ProtoBuf representation, transports them to the client using gRPC, and then deserializes them back to Python dictionaries.

Machine Learning 71

Machine Learning Machine Learning AWS ML 71

PyImageSearch

JULY 17, 2023

Extracting Random Images # import the necessary packages import matplotlib import numpy as np import torch import torchvision from pyimagesearch import config matplotlib.use("agg") import matplotlib.cm config : This module contains various configuration parameters for our project. config , network , and utils ) are also imported.

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AWS Machine Learning Blog

JANUARY 26, 2024

Read more about architecting privacy solutions , sovereignty by design , and compliance on AWS and use services such as AWS Config , AWS Artifact , and AWS Audit Manager to support your privacy, compliance, audit, and observability needs.

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ODSC - Open Data Science

APRIL 28, 2023

For doing the actual document-level categorization, this “contextualized representation” is then mean-aggregated and passed to a classification layer that predicts the category. In our sentiment analysis example, the two categories are “positive” or “negative”.

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Deep Learning Deep Learning Data Science Natural Language Processing 98

PyImageSearch

SEPTEMBER 18, 2023

Suppose we have an image I with multiple objects, and we want to classify each object in the image into a set of categories in a zero-shot way (i.e., Finally we import the config file, which stores the initial configurations of our parameters ( Line 11 ) and the utils.py without using any data to train the model). image = cv2.imread(config.IMG_PATH[1])

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PyImageSearch

DECEMBER 19, 2022

This experiment would help you to learn how the color camera node is created and how the camera feed is then displayed on the host side via the XLinkOut node. Then, on Lines 8-30 , we define the create_color_camera_pipeline() method, which would build the color camera pipeline. For that, we will move on to the utils.py FONT_HERSHEY_TRIPLEX, 0.5,

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Snorkel AI

FEBRUARY 21, 2024

In double-blind study, human testers preferred our researchers’ version of the model in every category. While LoRA falls under the umbrella of reparameterized fine-tuning methods, there are four additional categories of methods: additive fine-tuning , hybrid fine-tuning , partial fine-tuning , and unified fine-tuning.

Data Scientist 52

Data Scientist Machine Learning Machine Learning Algorithm 52

Snorkel AI

FEBRUARY 21, 2024

In double-blind study, human testers preferred our researchers’ version of the model in every category. While LoRA falls under the umbrella of reparameterized fine-tuning methods, there are four additional categories of methods: additive fine-tuning , hybrid fine-tuning , partial fine-tuning , and unified fine-tuning.

Data Scientist 52

Data Scientist Machine Learning Machine Learning Algorithm 52

AWS Machine Learning Blog

MAY 31, 2023

For demonstration purposes, we use a pre-trained ResNet50 model that can classify images into 1,000 categories. To learn more about the config settings, refer to Model Configuration. Prerequisites You first need an AWS account and an AWS Identity and Access Management (IAM) administrator user.

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ML ML AWS Natural Language Processing 82

PyImageSearch

SEPTEMBER 11, 2023

CLIP is prompted with hand-engineered text prompts to enhance its zero-shot classification performance on object categories, etc. Furthermore, we import the config file and the visualize_and_save_segmentation function defined above in the sam.py We start by opening our config.py SAM_CHECKPOINT_PATH = "checkpoints/sam_vit_h_4b8939.pth"

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phData

NOVEMBER 17, 2023

tsm settings export --output-config-file [global options] Doing a Full Data Backup and a Settings Backup daily is recommended to ensure you have enough resources available to overcome any disaster with your infrastructure. These settings include your configuration topology about the nodes and their processes. within that Site.

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AWS Machine Learning Blog

JULY 3, 2023

We upload the Ground Truth UI template and label categories file, and create the verification job. This includes scripts for model loading, inference handling etc. We chose asynchronous inference because it can handle large payload sizes and can meet near-real-time latency requirements.

Deep Learning 81

Deep Learning Deep Learning AWS Machine Learning 81

PyImageSearch

OCTOBER 2, 2023

to(config.DEVICE) # pass the encoder and decoder to VAE class vae = network.VAE(encoder, decoder) In the above lines, Instances of the encoder and decoder are created using configurations from the config module. instantiate the encoder and decoder models encoder = network.Encoder(config.IMAGE_SIZE, config.EMBEDDING_DIM).to(

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PyImageSearch

NOVEMBER 6, 2023

Finding Unique Mask Values ( Lines 59-62 ) For segmentation tasks, each pixel in a mask corresponds to a particular class or category. These unique values represent the different classes/categories in the segmentation masks. The sorted unique values are then stored in the self.mask_values list.

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Cambridge Intelligence

DECEMBER 2, 2022

Switches, servers, hosts and services are colored by category, and sized to show their connectivity. Let’s have a look at a visualization design for a market-leading impact analysis application. This chart maps out an entire IT infrastructure.

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AWS Machine Learning Blog

OCTOBER 20, 2023

The capabilities of the ML platform are grouped into four categories, as shown in the following figure. Detective controls – A detective control detects noncompliance of resources within your accounts, such as policy violations, provides alerts through the dashboard, and is implemented using AWS Config rules.

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The MLOps Blog

JANUARY 19, 2024

Hence, our evaluation strategy falls into the `Public Benchmarks` category, as it relies on a well-known dataset to evaluate PTBR models. We’ll use the `validation` set provided along with the FaQuAD dataset. The exact match metric determines if the response given by the model precisely aligns with the target answer.

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Natural Language Processing ML ML Machine Learning 52

AWS Machine Learning Blog

MAY 9, 2023

Various use cases fall into this category, such as preprocessing or postprocessing steps composing a model ensemble. To learn more about the config settings, refer to Model Configuration. Python backend runtime architecture As the name suggests, the Python backend is for running models that are written and run in the Python language.

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Python ML ML Deep Learning 81

PyImageSearch

JANUARY 8, 2024

How can we tackle this simple problem and enhance our model so that it not only correctly predicts categories on original images but also on sketches and cartoons of cats and dogs? decode_predictions(pred_model) print('Loss for Panda Class=', loss_fn(pred_model, labelGT).numpy())

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Deep Learning Deep Learning Data Pipeline Computer Science 64

AWS Machine Learning Blog

MAY 2, 2023

With the ability to solve various problems such as classification and regression, XGBoost has become a popular option that also falls into the category of tree-based models. To learn more about the config settings, refer to Model Configuration. To learn more about the config settings, refer to Model Configuration.

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AWS Machine Learning Blog

SEPTEMBER 12, 2023

Without modifying the existing architecture , we decide to fine-tune three separate pre-trained models for each of our required categories. With the SageMaker Hugging Face Deep Learning Containers (DLCs), starting and managing NLP experiments are made simple with Hugging Face containers and the SageMaker Experiments API.

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Data Science Data Scientist AWS ML 95

The MLOps Blog

JANUARY 23, 2023

In theory, you could automatically optimize hyperparameters for every model to infinity, but in practice, you are tweaking the model config based on the results exploration. Frameworks like Kedro, ZenML, and Metaflow fall into this category. They are manual or semi-manual. Tools like Prefect, Argo, and Kubeflow help you do that.

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ML ML Data Scientist Machine Learning 59

ODSC - Open Data Science

APRIL 10, 2023

So just eight lines of config: input_features: - name: description type: text - name: profile_image_url type: image output_features: - name: account_type type: category Generates a fully functional, and state-of-the-art ML pipeline. Each customization is just one extra line to the config.

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ML ML Machine Learning Machine Learning 52

Cambridge Intelligence

NOVEMBER 13, 2023

KronoGraph exposes this time-based data in a unique way, by creating an entirely new category of visualization: visual timeline analysis. This investigation won’t work without a timeline component… Discover timeline visualization with KronoGraph Graph databases treat time as a property that can be stored on the nodes or the edges.

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AWS Machine Learning Blog

JULY 20, 2023

They have been proven to be efficient in diverse applications and learning settings such as cybersecurity [1] and fraud detection, remote sensing, predicting best next steps in financial decision-making, medical diagnosis, and even computer vision and natural language processing (NLP) tasks.

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